Quantum Computing

GESDA was established to explore how future science breakthroughs can most efficiently be translated into and used as tools for the benefit of humanity. GESDA interlinks the digital revolution with other disruptive fields of science and technology, and with the diplomatic world.

GESDA’s work is guided by three fundamental questions:

  • Who are we, as humans? What does it mean to be human in the era of robots, gene editing, and augmented reality?
  • How are we all going to live together? How can technologies reduce inequality and foster inclusive development?
  • How can we ensure the well-being of humankind and the sustainable future of our planet? How can we supply the world’s population with the necessary food and energy and regenerate our planet?

GESDA brings together an outstanding community of academic, diplomacy, and impact leaders to reflect and act on how to use the future to build the present. Its work is structured around three flagship instruments:

  • GESDA Science Breakthrough Radar®

This digital platform – updated continuously and released in paper copy on a yearly basis – maps impactful emerging topics currently researched in science laboratories across the world and anticipated breakthroughs at 5, 10, and 25 years. Curated by the academic community, it provides descriptions of over 300 breakthrough predictions relevant to the global community.

Geneva Science and Diplomacy Anticipation Summit accelerates the science diplomacy nexus. Bringing science to the table of multilateralism, it engages diplomacy leaders to examine the impact of future breakthroughs on people, society, and the planet, as well as their implications for future global governance and geopolitics.

GESDA’s instrument to co-construct science diplomacy solutions with relevant transdisciplinary and cross-community task forces. In 2022, GESDA has eight solutions pathways and four initiatives in the making. These propositions are communicated at the Geneva Science and Diplomacy Anticipation Summit.

GESDA structures its anticipation, acceleration, and translation work across five thematic platforms addressing potential future science and technology advances, as well as their related challenges:

  • Quantum revolution and advanced artificial intelligence (AI), with for instance the challenge of privacy.
  • Human augmentation, with for instance the challenge of advanced gene editing or neuroenhancement.
  • Eco-regeneration and geo-engineering,  with for instance the challenges of synthetic biology, decarbonisation, and regenerative agriculture.
  • Science and diplomacy, with for instance the challenge of future world geopolitics, including multilateral conflict modelling, forecasting, and prevention.
  • Knowledge foundations with for instance the challenge of the future of work and labour, including rising inequalities and inclusive growth.

From the end of 2022 onwards, the GESDA Board of Directors will choose and fund (in partnership with other foundations) a limited number of large-scale, high-impact solutions and initiatives aiming to:

  • Help the world population benefit more rapidly from the advances of science and technology as stated by Article 27 of the Universal Declaration of Human Rights (UDHR).
  • Contribute to inclusive human development by reducing poverty and inequality while increasing the number of developing and emerging economies, in line with Agenda 2030.
  • Leverage the role of Geneva and Switzerland as a hub of multilateralism capable of anticipating cutting-edge science and technologies, as well as translating them into effective tools for

GESDA was created as a global independent foundation and a public partnership in 2019, for an initial start-up phase of three years. The founders – the Swiss Federal Council and the Canton of Geneva with the City of Geneva-decided in March 2022 to prolong the Foundation for 10 years.

The ultimate objective remains to strengthen the contribution of Switzerland to multilateralism as the host country of the UN in Geneva.

Digital activities

Advanced computational tools, such as AI and high-performance computing, are reshaping all fields of science.

GESDA’s specificity is that it focuses on ‘science anticipation’. Its ambition is to comprehend the future digital disruptions and their implications for other fields of science, geopolitics, and mankind.

GESDA’s headquarters are located at the Campus Biotech in Geneva.

Digital policy issues

A Swiss foundation with a global reach and a private-public partnership working from Geneva, GESDA began in September 2019 to develop and promote anticipatory science and diplomacy for greater impact and multilateral effectiveness. 

The GESDA Science Breakthrough Radar® is a new tool for multilateralism, informed discussions, and concerted action. It is a  single point of entry to catch up with the unprecedented pace of science and technology. Providing a  factual basis for eye-opening reflections on the impacts of future scientific discoveries for people, society, and the planet(s), this interactive, evolving instrument is updated once every year.

The GESDA Science Breakthrough Radar® provides a single entry point for all communities of practice interested in becoming early adopters of scientific advances, regardless of whether they are scientists, political authorities, diplomats working in embassies or in international organizations, economic actors, non-governmental organisations (NGOs),, or citizens from anywhere in the world. 

The GESDA Science Breakthrough Radar® gives an overview of the emerging trends in five major fields of science and technology: 

1. Advanced AI & Quantum Revolution 

2. Human Augmentation

3. Eco-Regeneration and Geoengineering 

4. Science & Diplomacy 

5. Knowledge Foundations

It offers three complementary points of view on these five fields, with each point comprising a chapter of the Radar: 

  • Trends – Scientific emerging topics and possible breakthroughs at 5, 10, and 25 years as they are currently already cooking in the laboratories.

The 2023 GESDA Science Breakthrough Radar® presents 42  emerging scientific topics and 324 breakthroughs at 5, 10 and 25 years in the 5 considered fields. Its Knowledge Foundations’ portion comprises 3 lenses on philosophy, geopolitics, and science, dealing with 3 fundamental questions about the future of humanity, which are debated by 84 scholars in philosophy, social sciences, humanities, and geopolitics. 

  • Actions and Debates – What people all over the world already do with and think about these possible scientific breakthroughs.

Every edition of the GESDA Science Breakthrough Radar® includes an analysis of more than 10 million social media posts and 1.3 million articles in the mainstream media to take the pulse of society on what people do and say about emerging scientific topics presented in the trends chapter of the Radar.

  • Opportunities – Emerging initiatives worth following and joining.

The 2023 GESDA Science Breakthrough Radar® presents the Open Quantum Institute 2023 Incubation Report, GESDA’s first Solution Ideas ready for pilot implementation as well as a summary of the Proceedings of the 2022 Geneva Science and Diplomacy Anticipation Summit organised once a year by the GESDA Foundation. 

The GESDA Science Breakthrough Radar® is a collective work resulting from the collaboration of 1,542 scientists around the world who are building the Radar community within the GESDA Academic Forum chaired by Professor Michael Hengartner, a member of the GESDA Board of Directors. The briefs presented in the 2023 edition are signed off by 58 top scientists. 

The total number of contributors to the Radar: 

  • 543 scientists from 53 countries contributed to the 2021 edition. 
  • 774 scientists from 70 countries contributed to the 2022 edition. 
  • 848 scientists from 73 countries contributed to the 2023 edition.

For three days every year in October, the GESDA Foundation gathers representatives of the communities of practice interested in discussing and using the emerging scientific trends depicted in the Radar. This Geneva Science and Diplomacy Anticipation Summit is where the new annual edition of the Radar is officially presented and released.

Scouting each year for future breakthroughs and emerging trends across scientific domains, from natural and social sciences to engineering and the humanities, is more critical than ever due to the pace at which science and technology are evolving. It’s the only way to be ready for the time when some of these breakthroughs become a reality. By projecting ourselves into the future, we aim to detect in advance the major scientific and technological advances that will change the ways we live, think, and behave. 

Consequently, we give people time to prepare for these changes with the best possible transitions and empower them to develop uses of their own that can benefit everyone. As we learn from the current debates raging over this year’s rapid adoption of artificial intelligence ‒ which is changing almost every industry and starting to impact society ‒ it becomes more difficult to construct long-term solutions: the debates have begun and are creating a hurried atmosphere.

What’s new in 2023 

Zoom in on the 2023 Edition 

Compared to the previous editions released in 2021 and 2022, the 2023 GESDA Science Breakthrough Radar 2023® innovates with the following: 

– 6 Deep Dives on current and future hot topics 

– 27 Breakthroughs Briefs 

– 7 Updates of existing Briefs 

– 3 Briefs on emerging topics 

– 9 new invited contributions that will nurture the next editions of the Radar 

Deep Dives 2023 

Neuro-Augmentation

Neuro-augmentation, one of the fastest-developing fields of science, involves enhancing our brains and nervous systems by using advanced technologies, including advanced AI and quantum computing. 

Recent breakthroughs in neuroscience, neurotechnology, and brain-inspired computing are paving the way for new treatments for neurodegenerative diseases and the enhancement of our cognitive abilities. For many people, this field is the next big thing. 

To delve into these complex topics, experts from various fields gathered at the GESDA Spring Anticipation Workshop in Villars, Switzerland They discussed the current state of neuro-augmentation science and identified its short-term, mid-term, and long-term implications and ethical concerns. These discussions notably aim to guide diplomatic interventions in this rapidly advancing field, ensuring responsible and beneficial progress for everybody. 

The discussion in Villars focused on three hot topics: (1) brain hacking, (2) hybrid brain, and (3) artificial cognition (brain-inspired AI and robotics). Some examples of these advancements include brain-monitoring devices and brain-machine interfaces, which allow us to both read and write signals from our nervous system. These innovations could have wide-ranging impacts, from changes in workplace dynamics to new definitions of what it means to be human. Additionally, scientists are exploring the creation of brain organoids, interspecies chimaeras, and genetically modified primates, all of which are pushing the boundaries of our understanding of life and the human brain. Moreover, researchers are investigating the potential for applying our understanding of the human brain to the development of computing devices and robots that could someday possess a form of consciousness. 

The Future of Peace and War 

After presenting an introductory essay on the topic last year, the GESDA Geopolitical Lens of the Radar takes a deep dive into the challenges of peace and war. 

Often resulting in violence or conflict, today’s increasing tensions between countries and power blocs are aggravated by climate change and competition in the field of digital technologies. 

Anticipation informed by an understanding of science and technology is, therefore, also essential in the field of peace and war. It makes possible the creation and implementation of appropriate programmes and strategies to prevent or contain conflict and advance more promising approaches to peace. 

Applying GESDA’s anticipatory methodology to mapping the future of peace and war involves plotting social and political scientists’ anticipations of the future. 

Unlike the anticipation of breakthroughs or new applications in the field of technology, foresight in the fields of social and political sciences entails more fragile projections accompanied by greater uncertainty, unanticipated tipping points, and black swan events. 

In a series of high-level workshops held in Geneva and New York in 2023, the three convening organisations — GESDA Foundation, the Geneva Centre for Security Policy (GCSP), and the School of International and Public Affairs (SIPA) at Columbia University — brought together experts in the field of peace and war to develop and apply a methodology to anticipate how advances in science and technology will influence the distribution of power in the next 10 to 25 years. 

Breakthroughs and Opportunities of Advanced AI and Quantum Revolution

As we witness a remarkable integration of AI and advanced computing technologies into our daily lives, the 2023 edition of GESDA Science Breakthrough Radar® explores these developments, first by featuring an updated briefing on advanced AI science and introducing a new brief on unconventional computing, which highlights alternative computing technologies that are poised to outperform current state-of-the-art AI in the future.

Additionally, Radar 2023 includes two invited contributions that discuss how, on the one hand,  AI is reshaping our understanding of the past and, on the other hand, how it is increasing the potential for neuromorphic computing to create robots with genuine embodied intelligence. 

GESDA’s world, however, extends beyond being just a think tank; it actively seeks to transform knowledge into action. Building on the scientifically validated insights gathered in its first Radar released in 2021, GESDA invested the last two years in conceiving and designing solution ideas for effective multilateralism in partnership with its broad science and diplomacy community. 

The Open Quantum Institute (OQI) has emerged as the first initiative to be incubated by GESDA. An exclusive report of the incubation phase in 2023 outlines OQI’s development journey, starting from the anticipation of quantum technologies in the scientific realm to its establishment as a validated solution concept for science diplomacy. 

The report elaborates on how the OQI aims to become the premier hub for applying quantum computing to achieve the UN sustainable development goals (SDGs). 

It details collaborations with partners to broaden access to quantum computers, underscores the significance of educational and training programs associated with the institute, and presents a proposal for shaping a multilateral governance structure that empowers the use of quantum computing for the SDGs. 

Furthermore, the report emphasises the engagement of a supportive community of stakeholders in co-creating OQI’s unique value proposition, ensuring that quantum technologies benefit society as a whole rather than a select few. 

The Human Right to Science 

To mark the 2023 celebration of the 75th Anniversary of the Universal Declaration of Human Rights, the GESDA Science Lens highlights the importance of the human right to science, as mentioned in international declarations and covenants. 

Article 27 of the Universal Declaration of Human Rights specifies the right for everyone to benefit from the advances of science. Other related documents emphasise that this right includes the responsibility to use scientific progress and its applications in a manner that takes into consideration both their benefits and the potential harm they could do. 

In late 2022, GESDA convened a scientific workshop with the Brocher Foundation in Geneva to get an overview of the current status of the Human Right to Science, both generally and more specifically within the health sector. 

The resulting report presented in the 2023 Radar involves 29 experts in international and humanitarian law discussing how integrating human rights into the scientific process can lead to collaborative, holistic, and inclusive approaches. This approach goes beyond merely mitigating risks; it encourages responsible exploration of the opportunities offered by scientific and technological progress. 

The Future of People, Society, and the Planet(s) 

Since 2021 in the GESDA Philosophy Lens, a group of leading philosophers has been exploring how the advancements outlined in the Radar might reshape humanity, society, and our relationship with the planet(s)

Each edition of the Radar proposes new points of view on three fundamental questions that the GESDA Foundation is addressing: 

1. Who are we? What does it mean to be human in an age of robots, gene editing, and augmented reality? 

2. How are we going to live together? Which deployment of technologies can help reduce inequality and foster inclusive development and well-being? 

3. How can we assure humankind’s wellbeing with the sustainable health of our planet? How can we supply the world’s population with the necessary food and energy while regenerating our planet?

For example, the possible development of ‘conscious’ machines requires us to reflect on our purported uniqueness as humans, and which properties we may wish to actively preserve as the sole remit of human beings. Additionally, the group of philosophers considers how emerging digital technologies can impact fundamental aspects of society, from trust and privacy to democracy and justice. It also addresses the challenges posed by climate engineering technologies and how we perceive our control over nature in the face of environmental disruptions. 

People’s Uses and Expectations Regarding Science 

Through a detailed examination of global public sentiment as well as people’s stances on science, the Radar’s Pulse of Society delves into the influence of science and technology on humanity’s self-perception, social interactions, and relationship with the environment. It also aims to detect the early uses of advanced technology and underscores the importance of comprehending public approaches regarding present and future scientific developments. 

To achieve this, the GESDA Foundation uses AI to analyse both mainstream media and online social platforms. 

As it has done every year since its inception in 2021, GESDA’s analysis provides new insights into the extent of discussions surrounding topics mentioned in the Radar, how these topics connect with other themes both inside and outside the Radar, and what the evolving sentiment around these subjects is. 

It also identifies the actions taken by citizens in response to their interests related to each topic, spotlighting noteworthy initiatives and influential figures that have emerged over the past year. Importantly, this year’s analysis also includes a comparison of how public opinions, sentiment, and actions have evolved since the initial release of the Radar in 2021.

Future of meetings

Geneva Science and Diplomacy Anticipation Summit (annual event in October) – all sessions accessible online.

Science and Diplomacy Week (annual event in May) – most sessions accessible online.

GESDA Science Breakthrough Radar(provides a platform for online contributions).

GESDA regularly contributes to relevant global meetings across the world.

Social media channels

Facebook @GESDAglobal

LinkedIn @gesda-global

X @GESDAglobal

5G and 6G

EBU is the world’s leading alliance of public service media. It has 112 member organisations in 56 countries and an additional 30 associates in Asia, Africa, Australasia, and the Americas. EBU members operate nearly 2,000 television, radio, and online channels and services, and offer a wealth of content across other platforms.

Together they reach an audience of more than one billion people around the world, broadcasting in more than 153 languages. The EBU operates Eurovision and Euroradio services.

Digital policy issues

Artificial intelligence

AI and data are central themes for PSM today, especially when it comes to strengthening and personalising relationships with its citizens. The EBU’s AI and Data Group defines the AI and Data Initiative strategy and priorities in order to support EBU members’ data usage and AI- and data-driven strategies. It brings together EBU member delegates and EBU permanent services delegates, who are directly involved in carrying out strategic, managerial, analytical, technological, legal, content-related, or other types of activities related to data usage in their respective organisations.

A prominent example of the EBU’s use of AI is its PEACH (Personalization for EACH) initiative, which has brought together a number of public broadcasters to develop AI-powered tools to deliver the right content to the right audience in accordance with current data protection regulations.

Telecommunication infrastructure

EBU members use various types of network infrastructure for the production and distribution of PSM content and services to the entire population. In addition to traditional broadcasting networks – terrestrial, cable, or satellite – media service providers use fixed and wireless IP networks. The EBU’s activities aim to ensure that these networks are capable of meeting the requirements of PSM organisations and their audiences in a technically and economically viable way. This includes technical developments and standardisation in collaboration with industry partners as well as engagement with regulators and policymakers to ensure a suitable regulatory framework for PSM content and services.

The current focus is on broadband distribution infrastructure; distribution over internet platforms; wireless mobile technologies such as 5G; and terrestrial broadcast networks, including access to spectrum.

The governance of the EBU’s technical work is described here: https://tech.ebu.ch/about. The current Technical Committee Workplan (2022-2025) is available here: https://tech.ebu.ch/docs/workplan/EBU_TC_Strategic_Priorities_2022-2025.pdf

Further information about the EBU’s technical work, including the scope of different working groups, can be found at https://tech.ebu.ch/home/

Following the start of the war in Ukraine and the 2021 flooding in Europe, the EBU issued a recommendation to recall the crucial importance of PSM’s delivery to citizens – for this, no single resilient network will suffice.

Digital standards

Since its inception in 1950, the EBU has been mandated by its members to contribute to standardisation work in all technological fields related to media. This work ranges from TV and radio production equipment to the new broadcasting standards for transmission. This mandate has been naturally extended over the years to the field of mobile technologies, as well as online production and distribution.

The EBU hosts the digital video broadcasting (DVB) project, which has developed digital TV standards such as DVB-T/T2 and DVB-S/S2 which are the backbone of digital TV broadcasting around the world. DVB is currently working on an IP-based distribution system and on DVB-I, a new open standard for content distribution over the internet. This work is closely aligned with the 3rd Generation Partnership Project (3GPP).

The EBU is an active member of a number of other standards and industry organisations that are developing specifications relevant to media content production and distribution, including major standards developing organisations (SDOs) (e.g. the European Telecommunications Standards Institute (ETSI), 3GPP, the International Telecommunication Union (ITU), the Institute of Electrical and Electronics Engineers (IEEE) but also those with a more focused scope (e.g. Hybrid broadcast broadband TV (HbbTV), DASH Industry Forum (DASH- IF), the World Wide Web Consortium (W3C), RadioDNS1RadioDNS is an organisation that promotes the use of open technology standards to enable hybrid radio. Hybrid radio combines broadcast radio and internet technologies to create a harmonised distribution technology. It relies upon the Domain Name System (DNS)., Word Digital Audio Broadcasting (WorldDAB), Advanced Encryption Standard (AES), the Advanced Media Workflow Association (AMWA), and the Society of Motion Picture and Television Engineers (SMPTE)). In all these organisations, the EBU’s main objective is to ensure that specifications are capable of meeting the requirements of EBU members and their audiences.

In 2019, the EBU launched a 5G Media Action Group (5G-MAG), an independent non-profit cross-industry association that provides a framework for collaboration between media and information and communications technology (ICT) stakeholders on a market-driven implementation of 5G technologies in content creation, production, distribution, and consumption.

Network neutrality

The EBU’s work in the field of net neutrality focuses on assisting its members in coordinating their positions on broadband network neutrality. To this end, it provides expertise and facilitates initiatives and the drafting of documents concerning net neutrality at the EU level. The EBU also encourages its members to exchange experiences from the national level. Net neutrality is addressed as part of the EBU’s Legal and Policy Distribution Group. Net neutrality is seen as a key principle for public service broadcasters to support and advocate for, as it ensures their services are equally accessible by all internet users.

Cybercrime and network security

The EBU has developed a Strategic Programme on Media Cyber Security, aimed mainly at raising awareness among its members of the increasing cybersecurity risks and threats to broadcasting. This initiative also provides a platform for its members to exchange information on security incidents (e.g. phishing campaigns, targeted malware attacks), as well as on lessons learned, projects, and internal procedures. A dedicated working group is focused on defining information security best practices for broadcast companies – it has recently published a recommendation providing guidance on cybersecurity safeguards that media organisations and media vendors should apply when planning, designing, or sourcing their products and services. The EBU organises an annual Media Cybersecurity Forum, which brings together manufacturers, service providers, and media companies to discuss security issues in the media domain.

Convergence and OTT

In an environment increasingly characterised by digital convergence, the EBU is working on identifying viable investment solutions for over-the-top (OTT) services. The organisation has a Digital Media Steering Committee, focused on ‘defining the role of public service media in the digital era, with a special focus on how to interact with big digital companies’. It also develops a  bi-annual roadmap for technology and innovation activities and has a dedicated Project Group on OTT services.

In addition, there is an intersectoral group composed of EBU members and staff that exchange best practices for relations between internet platforms and broadcasters. During the COVID-19 crisis, a coordinated effort by the technical distribution experts of the EBU and its members monitored the state of the global broadband network to help avoid surcharges due to the increased consumption of on-demand programmes.

This work goes hand in hand with that developed by the Legal and Policy department – among others with the Content, Platform, Distribution, and Intellectual Property Expert Groups, all key in the establishment of EU rules enabling the proper availability of PSM services to people across the EU and beyond.

Capacity development

Most of the EBU’s activities are aimed at increasing the capacity of its members to address challenges and embrace opportunities brought about by the digital age. To that end, through its Digital Transformation Initiative, the EBU has developed a number of member support services, such as its expert community network that gathers over 200 experts from across its membership, and a digital knowledge hub with a repository of analyses and best practices. The EBU also offers a wide range of workshops and other sessions aimed at creating awareness about the digital transformation of the public service media, developing peer-to-peer assessment of members’ digital maturity, and initiating tailored interventions based on members’ needs.

Social media channels

Facebook @EBU.HQ

Instagram @ebu_hq

LinkedIn @ebu

Podcasts @ebu.ch/podcasts

X @EBU_HQ

YouTube @European Broadcasting Union


Cloud Computing

CERN is widely recognised as one of the world’s leading laboratories for particle physics. At CERN, physicists and engineers probe the fundamental structure of the universe. To do this, they use the world’s largest and most complex scientific instruments – particle accelerators and detectors. Technologies developed at CERN go on to have a significant impact through their applications in wider society.

Digital activities

CERN has had an important role in the history of computing and networks. The World Wide Web (WWW) was invented at CERN by Sir Tim Berners-Lee. The web was originally conceived and developed to meet the demand for automated information-sharing between scientists at universities and institutes around the world.

Grid computing was also developed at CERN with partners and thanks to funding from the European Commission. The organisation also carries out activities in the areas of cybersecurity, big data, machine learning (ML), artificial intelligence (AI), data preservation, and quantum technology.

Digital policy issues

Artificial intelligence 1AI-related projects are developed and referred to as part of the CERN openlab activities.

Through CERN openlab, CERN collaborates with leading information and communications technology (ICT) companies and research institutes. The R&D projects carried out through CERN openlab address topics related to data acquisition, computing platforms, data storage architectures, computer provisioning and management, networks and communication, ML and data analytics, and quantum technologies. CERN researchers use ML techniques as part of their efforts to maximise the potential for discovery and optimise resource usage. ML is used, for instance, to improve the performance of the Large Hadron Collider (LHC) experiments in areas such as particle detection and managing computing resources. Going one step further, at the intersection of AI and quantum computing, CERN openlab is exploring the feasibility of using quantum algorithms to track the particles produced by collisions in the LHC, and is working on developing quantum algorithms to help optimise how data is distributed for storage in the Worldwide LHC Computing Grid (WLCG). This research is part of the CERN Quantum Technology Initiative (QTI) activities, launched in 2020 to shape CERN’s role in the next quantum revolution.

–   CERN openlab: a public-private partnership in which CERN collaborates with ICT companies and other research organisations to accelerate the development of cutting-edge solutions for the research community, including ML.

CERN QTI: a comprehensive R&D, academic, and knowledge-sharing initiative to exploit quantum advantage for high-energy physics and beyond. Given CERN’s increasing ITC and computing demands, as well as the significant national and international interests in quantum-technology activities, it aims to provide dedicated mechanisms for the exchange of both knowledge and innovation.

Cloud computing 2Within its work, CERN refers to ‘cloud computing’ as ‘distributed computing.

The scale and complexity of data from the LHC, the world’s largest particle accelerator, is unprecedented. This data needs to be stored, easily retrieved, and analysed by physicists worldwide. This requires massive storage facilities, global networking, immense computing power, and funding. CERN did not initially have the computing or financial resources to crunch all of the data on-site, so in 2002 it turned to grid computing to share the burden with computer centres around the world. The WLCG builds on the ideas of grid technology initially proposed in 1999 by Ian Foster and Carl Kesselman. The WLCG relies on a distributed computing infrastructure, as data from the collisions of protons or heavy ions are distributed via the internet for processing at data centres worldwide. This approach of using virtual machines is based on the same paradigm as cloud computing. It is expected that further CERN developments in the field of data processing will continue to influence digital technologies.

Telecommunication infrastructure 3Within its work, CERN refers to ‘telecommunication infrastructure’ as ‘network infrastructure’.

In the 1970s, CERN developed CERNET, a lab-wide network to access mainframe computers in its data centre. This pioneering network eventually led CERN to become an early European adopter of Transmission Control Protocol/Internet Protocol (TCP/IP) for use in connecting systems on site. In 1989, CERN opened its first external TCP/IP connections and by 1990, CERN had become the largest internet site in Europe and was ready to host the first WWW server. Nowadays, in addition to the WLCG and its distributed computing infrastructure, CERN is also the host of the CERN Internet eXchange Point (CIXP), which optimises CERN’s internet connectivity and is also open to interested internet service providers (ISPs).

Digital standards 4Within its work, CERN addresses ‘web standards’ as ‘open science’.

Ever since releasing the World Wide Web software under an open-source model in 1994, CERN has been a pioneer in the open-source field, supporting open-source hardware (with the CERN Open Hardware Licence), open access (with the Sponsoring Consortium for Open Access Publishing in Particle Physics SCOAP3) and open data (with the CERN Open Data Portal). Several CERN technologies are being developed with open science in mind, such as Indico, InvenioRDM, REANA, and Zenodo. Open-source software, such as CERNBox, CERN Tape Archive (CTA), EOS, File Transfer Service (FTS), GeantIV, ROOT, RUCIO, and service for web-based analysis (SWAN), has been developed to handle, distribute, and analyse the huge volumes of data generated by the LHC experiments and are also made available to the wider society.

Digital tools

Data governance 5Within its work, CERN refers to ‘data governance’ as ‘data preservation’.

CERN manages vast amounts of data; not only scientific data, but also data in more common formats such as webpages, images and videos, documents, and more. For instance, the CERN Data Centre processes on average one petabyte (one million gigabytes) of data per day. As such, the organisation notes that it faces the challenge of preserving its digital memory. CERN also points to the fact that many of the tools that are used to preserve data generated by the LHC and other scientific projects are also suitable for preserving other types of data and are made available to wider society.

The CERN Open Data Policy for scientific experiments at the LHC is essential to make scientific research more reproducible, accessible, and collaborative. It reflects values that have been enshrined in the CERN Convention for more than 60 years that were reaffirmed in the European Strategy for Particle Physics (2020), and aims to empower the LHC experiments to adopt a consistent approach towards the openness and preservation of experimental data (applying FAIR standards to better share and reuse data).

EOSC Future is an EU-funded project that is contributing to establishing the European Open Science Cloud (EOSC) to provide a Web of FAIR Data and Services for science in Europe. The implementation of EOSC is based on the long-term process of alignment and coordination pursued by the Commission since 2015.

CERN joined the recently formed EOSC Association in 2020. The EOSC Association is the legal entity established to govern the EOSC and has since grown to more than 250 members and observers.

Future of meetings

More information about ongoing and upcoming events, you can find on the events page.

Social media channels

Facebook @cern

Instagram @cern

LinkedIn @cern

X @CERN

YouTube @CERN




Emerging Technologies

The GSPI is a neutral and independent platform that aims to foster engagement between the research community and Geneva-based international policy actors around some of the most pressing global challenges (including global health, climate change, and migration). 

It works to foster science-policy ecosystems by brokering collaborations and enhancing capacities across the interface between the science, policy, and implementation communities. This includes an annual call for projects, the Impact Collaboration Programme (ICP), the production of policy briefs, as well as learning opportunities and resources to advance the professionalisation and recognition of the science-policy field of practice in Geneva and beyond.

The GSPI is based at the University of Geneva. It receives support from the Swiss Federal Department of Foreign Affairs (FDFA) and the backing of leading research institutions in Switzerland and Europe.

Digital activities

As part of its activities at the interplay between science, policy, and implementation actors, the GSPI tackles a range of digital issues. With data being a centrepiece of evidence-based policies, many of the GSPI’s activities touch on digitalisation and the use of digital tools in domains such as health, migration, development, and the environment.

Digital policy issues

Artificial intelligence

The project MapMaker, a collaboration between the International Union for Conservation of Nature (IUCN) and the Swiss Federal Institute of Technology in Zürich (ETH Zurich) has enabled the development of an online visualisation tool to inform data-driven decision-making on marine biodiversity conservation at the international level.

Digital standards

Together with the Geneva Health Forum (GHF), the GSPI has established a working group including key humanitarian actors to harness knowledge and best practices around the digitisation of clinical guidelines for management of childhood illness in primary care in low and middle-income countries. In line with the efforts of the WHO, and the principles of donor alignment for digital health, the working group has developed recommendations on how digitalisation can improve the management of childhood illness. In September 2021, the results of this work were shared with experts and the public, providing a platform for discussions on the lessons learned and future trends in the field.

Emerging technologies

In 2018, the GSPI organised policy discussions on the use of drones as part of humanitarian action. The conversation centred on the practical use of drones to deliver humanitarian aid and what can be done by stakeholders such as policymakers, the private sector, and non-governmental organisations (NGOs) to maximise the opportunities and reduce the risks of such technologies.

At the 2019 Digital Day, together with the University of Geneva, the GSPI organised a discussion exploring what experience and know-how Geneva-based organisations could share to empower and protect users in the context of the digital revolution.

With a number of other partners, the GSPI co-organised a discussion at the 2019 WSIS Forum on aerial data produced by drones and satellites in the context of aid and development. The session explored the interplay between international organisations, NGOs, and scientists and how they can work together to help monitor refugee settlements, provide emergency response in case of natural disasters, and scale agriculture programmes.

Data governance

The project REDEHOPE of the University of Geneva and the UN Economic Commission for Europe (UNECE) has led to the development of an online diagnostic tool to help countries identify and visualise issues in their housing data ecology, and access appropriate datasets to formulate more robust, evidence-based housing policies at the country level.

Sustainable development

In 2020–2021, the Basel, Rotterdam and Stockholm Convention (BRS) secretariat benefitted from the support of ETH Zurich to develop an online platform to identify and signal the need for evidence and information to the scientific community in the field of chemical and waste management.

A project from ICP 2021 addressed the hurdles facing policy actors in accessing and making sense of data in migration research. The project partners (the International Organization for Migration (IOM) and the Graduate Institute) developed an interactive digital toolkit for policy officials to support them in leveraging migration research for evidence-based policymaking. The toolkit, based on IOM’s flagship publication, the World Migration Report, was launched in June 2022.

ICP 2021 brought support to the development of interactive analytical tools providing information about all UN sanctions to inform both humanitarian practitioners and sanction policy actors on practical ways to safeguard principled humanitarian action in areas under a sanction regime. This project is a collaboration between the Graduate Institute and the Norwegian Refugee Council (NRC).

ICP 2022 selected a collaboration between ETH Zurich and IOM that seeks to bring more effective policy expertise in the management of migration to address migrants’ needs and increase social cohesion between migrant and local communities. The collaboration will develop a toolbox to be used by IOM and its partners to facilitate the use of the Immigration Policy Lab (IPL) Integration Index, a survey tool for governments, nonprofits, and researchers to measure the integration of immigrants around the world.

Human rights principles

Also in the framework of its ICP, the GSPI has supported a collaboration between the Geneva Academy of International Humanitarian Law and Human Rights and OHCHR’s B-Tech project. Some of the new fast-evolving technologies, such as cloud computing, artificial intelligence (AI), facial recognition technologies, and the internet of things (IoT), can have profoundly disrupting effects on sociopolitical systems and pose significant human rights challenges. This initiative provides authoritative guidance and resources for implementing the UNGPs in the technology space and placing international human rights law (IHRL) at the centre of regulatory and policy frameworks. Aimed at policymakers, the technology sector, and all those working on the regulation of AI, the policy research carried out in this project (see resulting Working Paper, 2021) brings fresh insights into how current initiatives on the regulation of AI technologies could incorporate the protection and respect for human rights. Published by the Geneva Academy, the paper also calls on states to adopt a ‘smart mix’ of mandatory and voluntary measures to support their implementation and how this applies to the AI sector. This GSPI-supported science-policy process will formally feed the development of a ‘UN Guiding Principles check’ tool (working title), which will provide states with a roadmap to assess their regulatory efforts across different policy domains relevant to technology.

Digital tools

Social media channels

LinkedIn @genevaspi

Twitter @GenevaSPI

Satellite

ITU is the United Nations specialised agency for information and communications technologies (ICTs), driving innovation in ICTs together with 193 member states and a membership of over 900 companies, universities, research institutes, and international organisations. Established nearly 160 years ago in 1865, ITU is the intergovernmental body responsible for coordinating the shared global use of the radio spectrum, promoting international cooperation in assigning satellite orbits, improving communications infrastructure in the developing world, and establishing the worldwide standards that foster seamless interconnection of a vast range of communications systems. From broadband networks to cutting-edge wireless technologies, aeronautical and maritime navigation, intelligent transport systems, radio astronomy, oceanographic and satellite-based Earth monitoring as well as converging fixed-mobile phone, internet, cable television and broadcasting technologies, ITU is committed to connecting the world. For more information, visit www.itu.int.

See also: Africa’s participation in the International Telecommunication Union

itu landscape 1

Digital activities

Some of ITU’s key areas of action include radiocommunication services (such as satellite services, and fixed/mobile and broadcasting services), developing telecommunications networks (including future networks), standardisation of various areas and media related to telecommunications, and ensuring access to bridge the digital divide and addressing challenges in ICT accessibility. ITU’s work supports emerging technologies in fields such as 5G, artificial intelligence (AI), Intelligent Transport Systems, disaster management, agriculture, smart sustainable cities, and the internet of things (IoT); access and digital inclusion; the accessibility of ICTs to persons with disabilities; digital health; ICTs and climate change; cybersecurity; gender equality; and child online protection, among others.  These and many more ICT topics are covered both within the framework of radiocommunication, standardisation, and development work, through various projects, initiatives, and studies carried out by the organisation.

Digital policy issues

Telecommunication infrastructure

Information and communication infrastructure development is one of ITU’s priority areas. The organisation seeks to assist member states, sector members, associates, and academia in the implementation and development of broadband networks, wired (e.g. cable) and wireless technologies, international mobile telecommunications (IMT), satellite communications, the IoT, and smart grids, including next-generation networks, as well as in the provision of telecommunications networks in rural areas.

ITU’s International Telecommunication Regulations (ITRs) have as an overall aim the facilitation of global interconnection and interoperability of telecommunication facilities. Through the ITU Radiocommunication Sector (ITU-R), ITU is involved in the global management of the radio frequency spectrum and satellite orbits, used for telecommunications services, in line with the Radio Regulations.

The international standards developed by ITU’s Telecommunication Standardization Sector (ITU-T) enable the interconnection and interoperability of ICT networks, devices, and services worldwide. It has 11 technical standardisation committees called Study Groups (SGs), with mandates covering a wide range of digital technologies:

The work on standards is complemented by short-term exploration/incubation ITU-T Focus Groups (FGs) whose deliverables guide the ITU-T SGs in new areas of standardisation work:

Collaboration among various standards bodies is a high priority of ITU-T. Various platforms were established to support coordination and collaboration on various topics, for example:

The Telecommunication Development Sector (ITU-D) establishes an enabling environment and provides evidence-based policy-making through ICT indicators and regulatory and economic metrics, and implements a host of telecommunications/ICT projects.

In the immediate aftermath of the COVID-19 pandemic, ITU-D launched the Global Network Resiliency Platform (REG4COVID) to address the strain experienced by telecommunication networks, which are vital to the health and safety of people. The platform pools experiences and innovative policy and regulatory measures.

Discussions involving the World Bank, Global System for Mobile Communications (GSMA), and the World Economic Forum identified how to bring together communities to support ITU membership in their response to COVID-19. The Speedboat Initiative issued a COVID-19 Crisis Response:

Digital Development Joint Action Plan and Call for Action to better leverage digital technologies and infrastructure in support of citizens, governments, and businesses during the pandemic.

Connect2Recover provides country-specific support to reinforce digital infrastructures – using telework, e-commerce, remote learning, and telemedicine to prevent the spread of COVID-19 and to support recovery and preparedness for potential future pandemics. ITU worked with the Government of Japan and the Kingdom of Saudi Arabia on this initiative. ITU/WHO Focus Group on AI for Health worked on a standardised assessment framework for the evaluation of AI-based methods for health, diagnosis, triage, or treatment decisions and in early 2020 it created an Ad-hoc Group on Digital Technologies for COVID-19 Health Emergencies (AHG-DT4HE) to review the role of AI (and other digital technologies) in combatting COVID-19 throughout an epidemic’s life cycle; it also delivered guidance on digital technologies for COVID health emergency. The Group also developed AI guidance specifically for health on ethics, regulatory considerations, clinical evaluation, and data quality and continues work with ITU, WHO, and WIPO on the Global Initiative on AI for Health.

The impact statement for the Telecommunications Development Bureau’s (BDT) thematic priority on Network and Digital Infrastructure is ‘Reliable connectivity to everyone’.

ITU-D SG1 also focuses on various aspects related to telecommunications infrastructure, in particular, Question 1/1 on ‘Strategies and policies for the deployment of broadband in developing countries’;   Question   2/1 on ‘Strategies, policies, regulations, and methods of migration and adoption of digital broadcasting and implementation of new services’; Question 4/1 on ‘Economic aspects of national telecommunications/ICTs’; Question 5/1 on ‘Telecommunications/ICTs for rural and remote areas’; Question 6/1 on ‘Consumer information, protection and rights’; and Question 5/2 on ‘Adoption of telecommunications/ICTs and improving digital skills’.

5G

ITU plays a key role in managing the radio spectrum and developing international standards for 5G networks, devices, and services, within the framework of the so-called IMT-2020 activities. ITU-R SGs together with the mobile broadband industry and a wide range of stakeholders established the 5G standards.

The activities include the organisation of intergovernmental and multistakeholder dialogues, and the development and implementation of standards and regulations to ensure that 5G networks are secure, interoperable, and operate without interference.

ITU-T is playing a similar convening role for the technologies and architectures of non-radio elements of 5G systems. For example, ITU standards address 5G transport, with Passive Optical Network (PON), Carrier Ethernet, and Optical Transport Network (OTN), among the technologies standardised by ITU-T expected to support 5G systems. ITU  standards for 5G  networking address topics including network virtualisation, network orchestration and management, and fixed-mobile convergence. ITU standards also address ML for 5G and future networks, the environmental requirements of 5G, security and trust in 5G, and the assessment of 5G quality of service (QoS) and quality of experience (QoE).

Satellite

ITU-R manages the coordination, notification, and recording of frequency assignments for space systems, including their associated earth stations. Its main role is to process and publish data and carry out the examination of frequency assignment notices submitted by administrations towards their eventual recording in the Master International Frequency Register.

ITU-R also develops and manages space-related assignment or allotment plans and provides mechanisms for the development of new satellite services by determining how to optimise the use of available and suitable orbital resources.

Currently, the rapid pace of satellite innovation is driving an increase in the deployment of non-geostationary satellite systems (NGSO). With the availability of launch vehicles capable of supporting multiple satellite launches, mega-constellations consisting of hundreds to thousands of spacecraft are becoming a popular solution for global telecommunications.

To this end, during the 2019 World Radiocommunication Conference (WRC-19), ITU established regulatory procedures for the deployment of NGSO systems, including mega-constellations in low Earth orbit.

Regarding climate change, satellite data today is an indispensable input for weather prediction models and forecast systems used to produce safety warnings and other information in support of public and private decision-making.

ITU develops international standards contributing to the environmental sustainability of the ICT sector, as well as other industry sectors applying ICTs assembling technologies to increase efficiency and innovate their service offer. The latest ITU standards in this domain address sustainable power-feeding solutions for IMT-2020/5G networks, energy-efficient data centres capitalising on big data and AI, and smart energy management for telecom base stations.

Emergency telecommunications

Emergency telecommunications is an integral part of the ITU mandate. To mitigate the impact of disasters, the timely dissemination of authoritative information before, during, and after disasters is critical.

Emergency telecommunications play a critical role in disaster risk reduction and management. ICTs are essential for monitoring the underlying hazards and for delivering vital information to all stakeholders, including those most vulnerable, as well as in the immediate aftermath of disasters for ensuring the timely flow of vital information that is needed to co-ordinate response efforts and save lives. ITU supports its member states in the four phases of disaster management:

ITU activities in the field of radiocommunications make an invaluable contribution to disaster management. They facilitate prediction, detection, and alerting through the coordinated and effective use of the radio-frequency spectrum and the establishment of radio standards and guidelines concerning the usage of radiocommunication systems in disaster mitigation and relief operations.

ITU-T SG2 plays a role as the lead study group on telecommunications for disaster relief/early warning, network resilience, and recovery. Other study groups are working on emergency telecommunications within their mandates. Examples are shown in the following paragraphs.

ITU standards offer common formats for the exchange of all-hazard information over public networks. They ensure that networks prioritise emergency communications. And they have a long history of protecting ICT infrastructure from lightning and other environmental factors. In response to the increasing severity of extreme weather events, recent years have seen ITU standardisation experts turning their attention to ‘disaster relief, network resilience, and recovery’. This work goes well beyond traditional protection against environmental factors, focusing on technical mechanisms to prepare for disasters and respond effectively when disaster strikes.

ITU standards now offer guidance on network architectures able to contend with sudden losses of substantial volumes of network resources. They describe the network functionality required to make optimal use of the network resources still operational after a disaster. They offer techniques for the rapid repair of damaged ICT infrastructure, such as means to connect the surviving fibers of severed fiber-optic cables. And they provide for ‘movable and deployable ICT resource units’ in various sizes, such as emergency containers, vehicles, or hand-held kits housing network resources and a power source – to provide temporary replacements for destroyed ICT infrastructure.

ITU is also supporting an ambitious project to equip submarine communications cables with climate- and hazard-monitoring sensors to create a global real-time ocean observation network. This network would be capable of providing earthquake and tsunami warnings, as well as data on ocean climate change and circulation. This project to equip cable repeaters with climate and hazard-monitoring sensors – creating Science Monitoring And Reliable Telecommunications (SMART) cables – is led by the ITU/WMO/UNESCO-IOC Joint Task Force (JTF) onSMART Cable Systems, a multidisciplinary body established in 2012. Currently, several projects are ongoing to realise SMART cables.

In ITU-D, a lot of effort is directed at mainstreaming disaster management in telecommunications/ICT projects and activities as part of disaster preparedness. This includes infrastructure development, and the establishment of enabling policy, legal, and regulatory frameworks. ITU also deploys temporary telecommunications/ICT solutions to assist countries affected by disasters. After providing assistance for disaster relief and response, ITU undertakes assessment missions to affected countries aimed at determining the magnitude of damage to the network through the use of geographical information systems. On the basis of its findings, ITU and the host country embark on resuscitating the infrastructure while ensuring that disaster-resilient features are integrated to reduce network vulnerability in the event of disasters striking in the future.

ITU is also part of the Emergency Telecommunications Cluster (ETC), a global network of organisations that work together to provide shared communications services in humanitarian emergencies.

ITU-D SQ Question 3/1 ‘The use of telecommunications/ICTs for disaster risk reduction and management’ was agreed at the World Telecommunication Development Conference 2022 (WTDC-22) and will operate for the 2022–2025 study period. This Question continues the work of Question 5/2 of the 2018–2021 period.

The ITU/WMO/UNEP Focus Group on Artificial Intelligence for Natural Disaster Management (FG-AI4NDM), established by ITU-T SG2 has been developing best practices to leverage AI to assist with data collection and handling, improve modelling across spatiotemporal scales, and provide effective communication.

Work includes the following:

  • With the ETC, ITU developed the Disaster Connectivity Map (DCM), with information critical for first responders on network outages and connectivity gaps following disasters.
  • ITU joined the Crisis Connectivity Charter(CCC) in 2019, joining the satellite industry and the humanitarian community in making satellite communication more available.
  • ITU established an ITU Emergency Telecommunications Roster. ITU staff are trained on deployment of ITU telecommunications equipment and on supporting the ETC on the ground.
  • ITU, with the International Federation of Red Cross and Red Crescent Societies (IFRC) and the World Meteorological Organization (WMO), launched a Call to Action on Emergency Alerting in 2021, inviting all partners to support countries in implementing CAP. The organisations are supporting the WMO to establish a CAP HelpDesk.
  • Strengthening the Multi-Hazard Early Warning Systems, ITU partnered with the United Nations Office for Disaster Risk Reduction (UNDRR), WMO, the Intergovernmental Oceanographic Commission of UNESCO (IOC-UNESCO), and the World Broadcasting Unions in 2020 to develop Media Saves Lives to reinforce broadcasters’ role in the early warning chain.

Artificial intelligence

ITU works on the development and use of AI to ensure a sustainable future for everyone. To that end, it convenes intergovernmental and multistakeholder dialogues, develops international standards and frameworks, and helps in capacity building for the use of AI.

AI and machine learning (ML) are gaining a larger share of the ITU standardisation work programme in fields such as network orchestration and management, multimedia coding, service quality assessment, operational aspects of service provision and telecom management, cable networks, digital health, environmental efficiency, and autonomous driving.

AI for Good is organised by ITU in partnership with 40 UN sister agencies and co-convened with Switzerland. The goal of AI for Good is to identify practical applications of AI to advance the UN SDGs and scale those solutions for global impact. It’s the leading action-oriented, global, and inclusive UN platform on AI.

Various ITU-T SGs address aspects of AI and ML within their mandates. The work has so far resulted in ITU-T Recommendations and Supplements, for example, in the L-, M-, P-, and Y-series of ITU-T Recommendations.

The ITU-T AI/ML in 5G Challenge, introduced in 2020, rallies like-minded students and professionals from around the globe to study the practical application of AI and ML in emerging and future digital communications networks and sustainable development. The second Challenge (in 2021) attracted over 1,600 students and professionals from 82 countries, competing for prizes and global recognition. The 2022 Challenge covered a wide range of topics including AI/ML in 5G, GeoAI, and tinyML. By mapping emerging AI and ML solutions, the Challenge fostered a community to support the iterative evolution of ITU standards. To learn more, see the Challenge GitHub.

Several ITU-T FG are considering the use of AI and ML including:

Main activities related to ITU-R SGs and reports include:

  • ITU-R SG1 covers Spectrum Management and Monitoring. In relation to AI, Question ITU-R 241/1 ‘Methodologies for assessing or predicting spectrum availability’ was approved in 2019 and is under study.
  • ITU-R SG6 covers all aspects for the broadcasting service. SG6 deliverables and work items related to AI and ML including Question ITU-R 144/6 ‘Use of artificial intelligence (AI) for broadcasting’; and Report ITU-R BT.2447 ‘Artificial intelligence systems for programme production and exchange’.
  • AI forRoadSafetyinitiative: Launched in October 2021, the initiative promotes an AI-enhanced approach to reduce fatalities across road-safety management, safer roads and mobility, safer vehicles, safer road users, post-crash response, and speed control.

During the 40th High-Level Committee on Programmes (HLCP) session in October 2020, an Interagency Working Group on AI (IAWG-AI) was established to focus on the policy and programmatic coherence of AI activities within the UN. IAWG-AI, co-led by the United Nations Educational, Scientific and Cultural Organization (UNESCO) and ITU, aims to combine the ethical and technological parts of the UN to provide a solid foundation for current and future system-wide efforts on AI, ensuring respect for human rights and accelerating progress on the SDGs.

ITU also coordinates an annual UN Activities on AI report, a joint effort with over 45 UN agencies and entities, all partners of AI for Good or members of the IAWG-AI. The report usually presents over 250 cases and projects run by the UN system, in areas covering all 17 SDGs and ranging from smart agriculture and food systems to transportation, financial services, and healthcare. The report contains an ExecutiveSummary which presents an analysis of all the projects submitted to the report, providing a snapshot of the key tracks, trends, and gaps in AI activities within the UN system.

The UN-led initiative, United for Smart Sustainable Cities (U4SSC), coordinated by ITU, UNECE, and UN-HABITAT and supported by 19 UN agencies and programmes, has been examining how AI can be employed in the smart city domain and through its Thematic Group on Guiding Principles for Artificial Intelligence in Cities for implementing AI-based solutions in line with the SDGs.

ITU, through its Development Sector, also holds an annual meeting for all telecommunications regulators on the occasion of the Global Symposium for Regulators (GSR), which discusses and establishes a regulatory framework for all technologies including AI, and addresses this issue at its two SGs. Several areas under ITU-D SG2 explore applications of AI in various domains to support sustainable development.

Critical internet resources 1In the work of ITU the issues related to critical internet resources are dealt with as ‘internet public-policy related work’.

Over the years, ITU has adopted several resolutions that deal with internet technical resources, such as Internet Protocol-based networks (Resolution 101 (Rev. Bucharest, 2022)), IPv4 to IPv6 transition (Resolution 180 (Rev. Bucharest, 2022)), and internationalised domain names (Resolution 133 (Rev. Bucharest, 2022)). ITU has also adopted a resolution on its role regarding international public policy issues pertaining to the internet and the management of internet resources, including domain names and addresses (Resolution 102 (Rev. Bucharest, 2022)). In addition, the ITU Council has set up a Working Group on International Internet (CWG-Internet)- related Public Policy Issues, tasked with identifying, studying, and developing matters related to international internet-related public policy issues. This Working Group also holds regular online open public consultations on specific topics to give all stakeholders from all nations an opportunity to express their views with regard to the topic(s) under discussion.

ITU is also the facilitator of WSIS Action Line С2 – Information and communication infrastructure.

Digital standards 2In the work of ITU the issue of digital standards is addressed as ‘International standards’.

International standards provide the technical foundations of the global ICT ecosystem.

Presently, 95% of international traffic runs over optical infrastructure built in conformance with ITU standards. Video now accounts for over 80% of all internet traffic; this traffic relies on ITU’s Primetime Emmy-winning video-compression standards.

ICTs are enabling innovation in every industry and public-sector body. The digital transformation underway across our economies receives key support from ITU standards for smart cities, energy, transport, healthcare, financial services, agriculture, and AI and ML.

ICT networks, devices, and services interconnect and interoperate thanks to the efforts of thousands of experts who come together on the neutral ITU platform to develop international standards known as ITU-T Recommendations.

Standards create efficiencies enjoyed by all market players, efficiencies, and economies of scale that ultimately result in lower costs to producers and lower prices to consumers. Companies developing standards-based products and services gain access to global markets. And by supporting backward compatibility, ITU standards enable next-generation technologies to interwork with previous technology generations; this protects past investments while creating the confidence to continue investing in our digital future.

The ITU standardisation process is contribution-led and consensus-based. Standardisation work is driven by contributions from ITU members and consequent decisions are made by consensus. The process aims to ensure that all voices are heard and that resulting standards have the consensus-derived support of the diverse and globally representative ITU membership.

ITU members develop standards year-round in ITU-T SGs. Over 4,000 ITU-T Recommendations are currently in force, and over 300 new or revised ITU-T Recommendations are approved each year.

For more information on the responsibilities of ITU SGs, covering ITU-T SG as well as those of ITU’s radiocommunication and development sectors (ITU-R and ITU-D), see the ITU backgrounder on study groups.

The ITU World Telecommunication Standardization Assembly (WTSA) is the governing body of ITU’s standardisation arm (ITU-T). It is held every four years to review the overall direction and structure of ITU-T. This conference also approves the mandates of the Telecommunication Standardization Sector study group (ITU-T SSGs) (WTSA Resolution 2) and appoints the leadership teams of these groups.

ITU develops international standards supporting the co-ordinated development and application of IoT technologies, including standards leveraging IoT technologies to address urban-development challenges.

WR to TL recognition procedure

Based on an MoU signed by ITU-T, the International Laboratory Accreditation Cooperation (ILAC), and the International Accreditation Forum (IAF), ITU recognises the Testing Laboratories (TLs). These are accredited by an Accreditation Body (AB) that is a signatory to the ILAC Mutual Recognition Arrangement (MRA) for testing. The scope of accreditation contains ITU-T Recommendation(s). All TLs which meet the criteria are listed in the ITU TL Database, https://itu.int/go/tldb. More details are also available in the ITU C&I Portal, https://itu.int/go/citest.

Digital rights and human-centric technologies 

In February 2023, the UN High Commissioner for Human Rights emphasised the necessity of incorporating human rights into technical standards during a high-level meeting at the World Standards Cooperation (WSC). Moreover, several Human Rights Council and UN General Assembly resolutions address human rights and digital technology issues and the development of the UN Secretary-General’s Guidance on Human Rights Due Diligence for Digital Technology Use is currently underway.  

ITU has already undertaken various initiatives to ensure a rights-respecting and inclusive digital landscape such as the one to ensure gender equity in its recommendations, promote accessibility for all, ensure universal access globally, and support the ICT capacity building of girls. Moreover, ITU understands that human-centric technologies are pivotal for safeguarding individual autonomy, promoting inclusivity, and upholding the principles of equality and dignity in the digital realm. Thus, the organisation actively engages in the development of policies and technical recommendations that prioritise digital rights, encompassing privacy, freedom of expression, access to information, data protection, and non-discrimination. 

Additionally, ITU plays a crucial role in facilitating dialogue and collaboration between our members, strategic partners, and relevant entities to create awareness, share best practices, and contribute to the formulation of international standards that emphasise human-centric approaches. By championing digital rights and human-centric technologies, we underscore our commitment to building a digital future that prioritises the well-being and rights of individuals across the global digital landscape. 

Internet of things 3Within the work of ITU, the work related to the IoT also includes ‘Smart cities’.

The range of applications of the IoT is very broad – extending from smart clothing to smart cities and global monitoring systems. To meet these varied requirements, a variety of technologies, both wired and wireless, is required to provide access to the network.

Alongside ITU-T studies on the IoT and smart cities, ITU-R conducts studies on the technical and operational aspects of radiocommunication networks and systems for the IoT. The spectrum requirements and standards for IoT wireless access technologies are being addressed in ITU-R, as follows:

  • Harmonisation of frequency ranges, and technical and operating parameters used for the operation of short-range devices.
  • Standards for wide area sensor and actuator network systems.
  • Spectrum to support the implementation of narrowband and broadband machine-type communication infrastructures.
  • Support for massive machine-type communications within the framework of the standards and spectrum for IMT-Advanced (4G) and IMT-2020 (5G).
  • Use of fixed-satellite and mobile-satellite communications for the IoT.

ITU-D SG2 Question 1/2 ‘Creating smart cities and society: Employing information and communication technologies for sustainable social and economic development’ includes case studies on the application of the IoT, and identifies the trends and best practices implemented by member states as well as the challenges faced, to support sustainable development and foster smart societies in developing countries.

ITU-T SG20 is responsible for studies relating to the IoT and its applications, and smart cities and communities (SC&C). This includes studies relating to big data aspects of the IoT and SC&C, digital services for SC&C, and digital transformation of relevant IoT and SC&C aspects. ITU and the Food and Agriculture Organization of the United Nations (FAO) Focus Group on Artificial Intelligence (AI) and Internet of Things (IoT) for Digital Agriculture (FG- AI4A), established by ITU-T SG20, explores (1) how emerging technologies including AI and IoT can be leveraged for data acquisition and handling, (2) modelling from a growing volume of agricultural and geospatial data, and (3) providing communication for the optimisation of agricultural production processes.

Blockchain

New ITU standards for blockchain and distributed ledger technology (DLT) address the requirements of blockchain in next-generation network evolution and the security requirements of blockchain, both in terms of blockchain’s security capabilities and security threats to blockchain.

ITU reports provide potential blockchain adopters with a clear view of the technology and how it could best be applied. Developed by the FG DLT, these reports provide an ‘assessment framework’ to support efforts to understand the strengths and weaknesses of DLT platforms in different use cases. The Group has also produced a high-level DLT architecture – a reference framework – detailing the key elements of a DLT platform. The FG studied high-potential DLT use cases and DLT platforms said to meet the requirements of such use cases. These studies guided the Group’s abstraction of the common requirements necessary to describe a DLT architecture and associated assessment criteria. The resulting reports also offer insight into the potential of DLT to support the achievement of the SDGs.

Blockchain and DLT are also key to the work of the Digital Currency Global Initiative, a partnership between ITU and Stanford University to continue the work of an ITU Focus Group on Digital Currency including Digital Fiat Currency (FG DFC). The Digital Currency Global Initiative provides an open, neutral platform for dialogue, knowledge sharing, and research on the applications of Central Bank Digital Currency (CBDC) and other digital currency implementations. The initiative will share case studies of digital currency applications, benchmark best practices, and develop specifications to inform ITU standards.

ITU-T SG3 is studying economic and policy aspects when using distributed ledger technologies such as for the improved management of the Universal Service Fund or to handle accounting.

ITU-T SG5 is studying the environmental efficiency of digital technologies including blockchain. For example, ITU-T SG5 has developed Recommendation ITU-T L.1317 on guidelines for energy-efficient blockchain systems.

ITU-T SG16 Question 22/16 on multimedia aspects of DLT and e-services and ITU-T SG17 Question 14/17 on DLT security continue the work of the now closed ITU-T Focus Group on Distributed Ledger Technologies. Several Recommendations and Technical Papers have been produced, and more are being prepared.

Topics of interest for digital financial services (DFS) that are being studied by Q22/16 and Q7/17 include digital evidence services, digital invoices, and smart contracts.

ITU-T SG20 Question 4/20 on data analytics, sharing, processing, and management, including big data aspects, of the IoT and SC&C, is studying the role of emerging technologies such as blockchain to support data processing and management (DPM).

Cloud computing

ITU standards provide the requirements and functional architectures of the cloud ecosystem, covering inter- and intra-cloud computing and technologies supporting anything as a service (XaaS). These standards enable consistent end-to-end, multi-cloud management and the monitoring of services across different service providers’ domains and technologies. They were developed in view of the convergence of telecoms and computing technologies that characterises the cloud ecosystem.

Cloud services provide on-demand access to advanced ICT resources, enabling innovators to gain new capabilities without investing in new hardware or software. Cloud concepts are also fundamental to the evolution of ICT networking, helping networks to meet the requirements of an increasingly diverse range of ICT applications.

As innovation accelerates in fields such as IMT-2020/5G and the IoT and digital transformation takes hold in every industry sector, the cloud ecosystem will continue to grow in importance to companies large and small, in developing as well as developed countries.

ITU-D SG1 Question 3/1 of the 2018–2021 period focused on the analysis of factors influencing effective access to support cloud computing, as well as strategies, policies, and infrastructure investments to foster the emergence of a cloud-computing ecosystem in developing countries, among others. For 2022–2025, this topic will be studied under Question 2/2 ‘Enabling technologies for e-services and applications, including e-health and e-education’.

Emerging technologies

ITU’s range of work on emerging technologies in fields such as AI, 5G, IoT, SC&C, ITS, quantum information technologies, and others have been covered in various other sections.

ITU-T SG5 on Environment, Electromagnetic Fields (EMF), and the Circular Economy is responsible for ICTs related to the environment, energy efficiency, clean energy, and sustainable digitalisation for climate actions. It carries out work to study the environmental efficiency of emerging technologies.

ITU-T SG20 Question 5/20 on the study of emerging digital technologies, terminology and definitions, serves as a facilitator with the research and innovation community to identify emerging technologies requiring standardisation for the global market and the industry.

U4SSC, through its various thematic groups, explores how leveraging emerging technologies such as the IoT, AI, blockchain, and digital twin, can help create a sustainable ecosystem and improve the delivery of urban services to improve quality of life for inhabitants. In this context, U4SSC has published the following reports:

Quantum information technology

Quantum information technology (QIT) improves information processing capability by harnessing the principles of quantum mechanics. It has promoted the second quantum revolution and will profoundly impact ICT networks and digital security.

ITU’s work in the area of QIT includes developing standards. For example, several ITU-T SGs, including SGs 11, 13, and 17 are developing ITU-T Recommendations in this field. The work has so far resulted in ITU-T Recommendations and Supplements in the X-, and Y-series of ITU-T Recommendations.

The ITU-T Focus Groupon Quantum Information Technology for Networks (FG-QIT4N) provided a collaborative platform for pre-standardisation aspects of QIT for networks. It adopted nine technical reports.

A 2021 webinar series explores innovative QIT applications and their implications on security, on classical computing and ICT networks and the discussion of corresponding roadmaps for quantum networks.

Network security 4In the work of ITU the issue of network security is addressed as ‘ICT security’.

ITU and the WSIS Action Line C5 – Building confidence and security in the use of ICTs, bringing different stakeholders together to forge meaningful partnerships to help countries address the risks associated with ICTs. This includes adopting national cybersecurity strategies, facilitating the establishment of national incident response capabilities, developing international security standards, protecting children online, and building capacity.

ITU develops international standards to build confidence and security in the use of ICTs, especially for digital transformation. Topics of growing significance to this work include digital identity infrastructure, cybersecurity management, security aspects of digital financial services, intelligent transport systems, blockchain and distributed ledger technology, and quantum information technologies.

ITU-T SG17 (Security) is the lead SG on building confidence and security in the use of ICTs; facilitating more secure network infrastructure, services, and applications; and coordinating security-related work across ITU-T SGs. Providing security by ICTs and ensuring security for ICTs are both major study areas for SG17. Other ITU-T SGs, such as ITU-T SG9 (Broadband Cable and TV) and ITU-T SG13 (Future Networks, with Focus on IMT-2020, Cloud Computing and Trusted Network Infrastructures) contributed to fulfilling the ITU mandate on cybersecurity.

ITU-TSG5 (Environment, EMF, and the Circular Economy) studies the security of ICT systems concerning electromagnetic phenomena (High-Altitude Electromagnetic Pulse (HEMP), High Power Electromagnetic (HPEM), information leakage).

ITU-T SG11 (Protocols, testing & combating counterfeiting) is developing a series of new ITU-T Recommendations (e.g. ITU-T Q.3057), which define the signalling architecture and requirements for interconnection between trustable network entities in support of existing and emerging networks. This Recommendation describes the use of digital signatures (digital certificates) in the signalling exchange which may guarantee the trustworthiness of the sender. More details are available at https://itu.int/go/SIG- SECURITY.

WR to combating counterfeiting and stolen ICT devices: The issue of counterfeit and stolen ICT devices affects all stakeholders and becomes a big challenge for the entire ICT industry. ITU, as a specialised agency of the UN on ICTs, is facilitating industry to cope with such issues. Since 2013, SG11 approved 13 standards and non-normative documents and organised 11 Workshops and related events whose main aim was to promote ITU-T SG11’s current activities and find a way forward. More details about ITU-T SG11 activities on combating counterfeiting are available on a dedicated webpage https://itu.int/go/CS-ICT.

ITU-T SG20 Question 6/20 on Security, privacy, trust and identification for IoT and SC&C, is working on developing recommendations, reports, and guidelines on security and trust provisioning in IoT both at the ICT infrastructure and future heterogeneous converged service environments. ITU-R established clear security principles for IMT (3G, 4G and 5G) networks.

In 2008, ITU launched a five-pillared framework called the Global Cybersecurity Agenda (GCA) to encourage co-operation with and between various partners in enhancing cybersecurity globally. The cybersecurity programme offers its membership, particularly developing countries, the tools to increase cybersecurity capabilities at the national level in order to enhance security, and build confidence and trust in the use of ICTs. The 2022 session of the ITU Council approved guidelines for better utilisation of the GCA framework by ITU.

ITU serves as a neutral and global platform for dialogue around policy actions in the interests of cybersecurity.

ITU issues the Global Cybersecurity Index (GCI) to shed light on the commitment of ITU member states to cybersecurity at the global level. The index is a trusted reference developed as a multistakeholder effort managed by ITU. In the last iteration of the GCI, 150 member states participated.

Alongside the ITU-T’s development of technical standards in support of security and ITU-R’s establishment of security principles for 3G and 4G networks, ITU also assists in building cybersecurity capacity.

This capacity-building work helps countries to define cybersecurity strategies, assists the establishment of computer incident response teams (CIRTs), supports the protection of children online, and assists countries in building human capacity relevant to security.

For example:

Strategies: ITU assists member states in developing and improving effective national cybersecurity frameworks or strategies. At the national level, cybersecurity is a shared responsibility, which requires coordinated action for prevention, preparation, and response on the part of government agencies, authorities, the private sector, and civil society. To ensure a safe, secure, and resilient digital sphere, a comprehensive national framework or strategy is necessary.

CIRTs: Effective mechanisms and institutional structures are necessary at the national level to deal with cyberthreats and incidents reliably. ITU assists member states in establishing and enhancing national CIRTs. In response to the fast-evolving technologies and manifestation of related threats, incident response must be updated and improved continuously.

Building human capacity:

  • ITU conducts regional and national cyber drills, assisting member states in improving cybersecurity readiness, protection, and incident response capabilities at regional and national levels, and strengthening international cooperation among ITU member states against cyberthreats and cyberattacks. To date, ITU has conducted cyber drills involving over 100 countries.
  • ITU’s Development Bureau organises regional cybersecurity forums across ITU regions, helping build capacity for Telecommunication Development Bureau (BDT) programmes and facilitating cooperation at the regional and international levels.
  • Through the ITU Academy, ITU offers a number of training courses for professionals in the field of cybersecurity.
  • BitSight provided access to ITU member states for its cybersecurity scoring platform – helping address cybersecurity challenges during the COVID-19 pandemic and to support member states’ health infrastructure with timely information on cyberthreats.
  • The Women in Cyber Mentorship Programme builds skills of junior women professionals entering the field of cybersecurity.

International cooperation: In its efforts on cybersecurity, ITU works closely with partners from international organisations, the private sector, and academia, strengthened by a memorandum of understanding (MoU) with a range of organisations such as the United Nations Office on Drugs and Crime (UNODC), World Bank, Interpol, World Economic Forum, and several others.

Child safety online 5Within the work of ITU, child safety online is addressed as ‘Child online protection’.

As part of its Global Cybersecurity Agenda (GCA), ITU launched the Child Online Protection (COP) Initiative in 2008, aimed at creating an international collaborative network and promoting the protection of children globally from all kinds of risks and harms related to the online environment, all while empowering children to fully benefit from the opportunities that the internet offers. The initiative focuses on the development of child online protection strategies covering five key areas: legal measures, technical and procedural measures, organisational structures, capacity building, and international cooperation.

Approaching child online safety with a holistic child-rights-based approach, the initiative has recently added to its key objectives the participation of children in policy-making processes related to child online protection as well as the digital skills development for children and their families.

In collaboration with other organisations, ITU has produced four sets of the 2020 Child Online Protection (COP) Guidelines, aimed at children, parents, guardians, and educators, as well as industry and policymakers. The first set of COP Guidelines were produced in 2009. The ITU Council Working Group on Child Protection Online (WG- CP) guides the organisation’s activities in the area of child safety online.

ITU has launched or supported a range of COP responses specific to COVID-19, including:

Access

The need for sustained efforts to expand internet access at a global level and bring more people online has been outlined in several resolutions adopted by ITU bodies. The organisation is actively contributing to such efforts, mainly through projects targeted at developing countries and focused on aspects such as human and institutional capacity building, education, and digital literacy; deployment of telecommunications networks and establishment of Internet Exchange Points (IXPs); the creation of broadband public access points to the internet; and the development and implementation of enabling policies in areas such as universal access. The organisation is also studying access-related issues within its various study groups, and it publishes relevant papers and studies. ITU also monitors progress made by countries in addressing the digital divide, through its periodically updated statistics and studies such as the ICT Facts and Figures and the series of Measuring Digital Development reports, including its analysis of ICT prices. The ITU DataHub brings together a broad range of indicators and statistics for easy consultation and download. The Connect 2030 Agenda envisions specific targets related to internet access; for instance by 2023, 65% of households worldwide will have access to the internet; by 2023, 70% of individuals worldwide will have with access to the internet; and by 2023, internet access should be 25% more affordable.

Access is treated in most meaningful connectivity-related Questions of ITU-D SG1 including:

  • Question 1/1 on strategies and policies for the deployment of broadband in developing countries.
  • Question 2/1 on strategies, policies, regulations and methods of migration to and adoption of digital technologies for broadcasting, including to provide new services for various environments.
  • Question 4/1 on economic aspects of national telecommunications/ICTs.
  • Question 5/1 on telecommunications/ICTs for rural and remote areas.
  • Question 6/1 on consumer information, protection and rights.

ITU is the facilitator of WSIS Action Line С2 – Information and communication infrastructure.

Capacity development

ITU is heavily involved in capacity development activities, mainly aimed at assisting countries in developing their policy and regulatory frameworks in various digital policy areas, ranging from the deployment or expansion of broadband networks, to fighting cybercrime and enhancing cybersecurity. The ITU Academy provides a wide range of general and specialised courses on various aspects related to ICTs. Such courses are delivered online, face-to-face, or in a blended manner, and span a wide variety of topics, from technologies and services, to policies and regulations. ITU also develops digital skills at basic and intermediate level to citizens through its Digital Transformation Centre (DTC) Initiative.

The Digital Regulation Handbook and Platform is the result of ongoing collaboration between ITU and the World Bank, which started in 2000. Structured by thematic areas, the Digital Regulation Platform aims to provide practical guidance and best practice for policymakers and regulators across the globe concerned with harnessing the benefits of the digital economy and society for their citizens and firms. The content provides an update on the basics of ICT regulation in light of the digital transformation sweeping across sectors and also includes new regulatory aspects and tools for ICT regulators to consider when making regulatory decisions.

The inclusivity of the ITU standardisation platform is supported by ITU’s Bridging the Standardization Gap (BSG) programme as well as regional groups within ITU-T SGs. The BSG hands-on SG effectiveness training and updated guidelines for National Standardization Secretariats (NSS) assist developing countries in developing the practical skills and national procedures required to maximise the effectiveness of their participation in the ITU standardisation process.

Digital services and applications

The Digital Services and Applications programme offers member states the tools to leverage digital technology and ICT applications to address their most pressing needs and bring real impact to people, with an emphasis on increasing availability and extending services in areas such as digital health, digital agriculture, digital government, and digital learning, as well as cross-sectoral initiatives to accelerate sustainable development such as smart villages.

To effectively harness digital services and applications for socio-economic development, the programme facilitates:

  • development of national sectoral digital strategy (including toolkits, guidelines, capacity building, action plans, and evaluations);
  • deployment of innovative digital services and applications to improve the delivery of value-added services, leveraging strategic partnerships as catalysts;
  • knowledge and best practice sharing through studies, research, and awareness raising, connecting stakeholders in converging ecosystems; and
  • addressing emerging technology trends – such as big data and AI – by collecting and sharing best practices.

Digital ecosystems

ITU works on helping member states create and mature their digital innovation ecosystems. The Digital Ecosystem Thematic Priority has developed a framework to help countries develop appropriate ICT-centric innovation policies, strategies, and programmes; share evidence- based best practices; and implement bankable projects to close the digital innovation gap. Countries are empowered to develop an environment that is conducive to innovation and entrepreneurship, where advances in new technologies become a key driver for the implementation of the WSIS Action Lines, the 2030 Agenda for Sustainable Development, and the Connect 2030 agenda.

ITU assists member states through its events, courses, publications, toolkits, and provision of technical advice. Its Ecosystem Development Projects initiative, for example, provides holistic advisory services including ecosystem diagnosis, risk assessment, good practice transfer, and capacity building. Events include its National and Regional Innovation Forums, which bring ecosystem stakeholders together to equip them with the skills to build their national innovation ecosystems; the ITU Innovation Challenges, which identify the best ICT innovators from around the world and equip them with skills to scale their ideas to truly impact their communities; courses on developing and maturing ecosystems (available at the ITU Academy); and Digital Innovation Profiles, which provide a https://www.itu.int/en/mediacentre/backgrounders/Pages/connect-2030-agenda.aspxsnapshot of a country’s ecosystem status and allowing them to identify and fill the gaps using ITU tools and expertise.

Sustainable development

ITU, as the UN specialised agency for ICTs, continues to support its membership and to contribute to the worldwide efforts to advance the UN 2030 Agenda for Sustainable Development and achieve its SDGs.

The 17 SDGs and their 169 related targets offer a holistic vision for the UN system. The role and contribution of ICTs as essential catalysts to fast-forward achievement of the SDGs is clearly highlighted and has come into focus since the COVID-19 pandemic started. Infrastructure, connectivity, and ICTs have demonstrated their great contribution and potential to accelerate human progress, to bridge the digital divides, and to develop digital societies.

ITU has a key role to play, in realising its main goals of universal connectivity and sustainable digital transformation, in contributing to achieving the SDGs. ITU contributes to the achievement of the SDGs with four levels of involvement:

  • ICTs as an enabler: ITU can be seen as a contributor to all SDGs through the benefits that ICTs bring to societies and economies.
  • Focus: SDGs with no specific reference to ICTs but where ITU has demonstrated to have a clear impact through the benefits ICTs bring to specific sectors and activities (e.g. e-health, digital inclusion, smart cities, e-waste, climate change). These are SDGs 1, 3, 10, 11, 12, and 13.
  • Key focus: SDGs where ITU has a particularly strong impact due to its initiatives, and is custodian of some indicators. These are SDG 4 (Quality Education), with its Target 4b to ‘… expand globally the number of scholarships, for enrolment in higher education, including vocational training and ICTs, technical, engineering and scientific programmes…’; and SDG 5 (Gender Equality), Target 5.b on ‘…the use of enabling technology, in particular ICTs, to promote the empowerment of women’. And Indicator 5b.1 on the ownership of mobile phones, by sex.
  • Main key focus: SDGs where ITU maximises its contribution, such as SDG 9 (Industry, Innovation and Infrastructure) and SDG 17 (Partnership for the Goals). Here ITUis also custodian of related Targets 9.c on ‘…. ICTs to provide universal and affordable access to the Internet…’; and its Indicator 9c.1 on coverage by a mobile network and by technology. As well as Target 17.8 to ‘….enhance the use of enabling technology, in particular information and communications technology’; and its Indicator 17.8.1 about individuals using the internet.

The ITU Connect 2030 Agenda is specifically dedicated to leveraging telecommunications/ICTs, including broadband, for sustainable development. The agenda is built around five goals: growth, inclusiveness, sustainability, innovation, and partnership. In addition, ITU-D works on fostering international cooperation on telecommunications and ICT development issues, and enhancing environmental protection, climate change adaptation, emergency telecommunications, and disaster mitigation and management efforts through telecommunications and ICTs. These and other related issues are explored in reports, guidelines, and recommendations produced by ITU-D SGs. Additionally, ITU-T SGs such as ITU-T SG5 on Environment, EMF, and the Circular Economy is the lead SG and develops standards on circular economy and e-waste management, ICTs related to the environment, energy efficiency, clean energy, and sustainable digitalisation for climate actions, which help to achieve the SDGs.

The ITU strategic plan is aligned to the WSIS Action Lines and SDGs. Since 2015, the WSIS process has been aligned with the 2030 Agenda for Sustainable Development to ensure that ICTs play the enabling role in advancing the SDGs.

Inclusive finance 6Within the work of ITU, the issues related to inclusive finance are addressed as ‘Digital Financial Services (DFS)’.

ITU has built a substantial programme of work in support of digital financial inclusion. ITU standards for digital finance address the security of telecommunications infrastructure (Signalling System No. 7 (SS7)) vulnerabilities, SIM vulnerabilities and SIM fraud), process for managing risks, threats, and vulnerabilities for digital finance service providers, assessing the quality of service of mobile networks to improve reliability and user experience for digital financial services and methodology for auditing the security of mobile payment applications to assess their level of security assurance. They provide for a high quality service and user experience, and safeguard security to build trust in digital finance.

ITU’s work in this field has included the ITU Focus Group on Digital Financial Services (2014–2017), the ITU Focus Group on Digital Currency including Digital Fiat Currency (2017–2019), and the Financial Inclusion Global Initiative (2017–2021), a four-year programme to advance research in digital finance and accelerate digital financial inclusion in developing countries co-led by ITU, the World Bank Group, and the Committee on Payments and Market Infrastructures, and with financial support from the Bill & Melinda Gates Foundation. ITU has also set up a Digital Financial Services (DFS) Security Lab to collaborate with regulators from both the telecom and financial services sectors in emerging economies as well as regional telecom bodies such as the Communications Regulators’ Association of Southern Africa (CRASA), The East African Communications Organization (EACO), and West Africa Telecommunications Regulators Assembly (WATRA) to adopt the recommendations developed under the Financial Inclusion Global Initiative and assess the security of mobile payments applications. The methodology developed for the security audit of mobile payment applications would be developed into a digital public good standard in the future. Through the Security Lab, some 17 security clinics have been held in Africa, Latin America, and Asia regions, providing information and technical guidance to regulators, DFS providers and mobile network operators in those regions on how to adopt the security recommendations for digital finance.

ITU organised the Insights on Digital Financial Services webinar series in 2020 with the objective of providing insights on the innovative applications of telecommunications services, digital payments, and fintech in addressing COVID-triggered social distancing and lockdown and sharing lessons learned from governments and DFS stakeholders on the measures that they are implementing. Twelve webinars were held between May and December 2020 attracting over 1,000 unique participants from 105 countries. The webinars focused on topics such as digital identity, strong authentication technologies, security of digital financial transactions, handling fraud and scams, tracking digital financial crimes and fraud, digital credit technologies, mitigating telecom infrastructure vulnerabilities for digital finance and central bank digital currency.

ITU and Stanford University launched the Digital Currency Global Initiative (DCGI) in 2020 to continue the work of the ITU Focus Group on Digital Currency including Digital Fiat Currency. The DCGI provides an open and neutral platform for dialogue, knowledge sharing, and research on the applications of Central Bank Digital Currency (CBDC) and other digital currency implementations.

E-waste

ITU works in developing policies, standards, frameworks, and guidelines for the efficient disposal of e-waste to achieve a circular economy. ITU has the mandate to promote awareness of the environmental issues associated with telecommunication/ICT equipment design and encourage energy efficiency and the use of materials in the design and fabrication of telecommunication/ICT equipment that contributes to a clean and safe environment throughout its lifecycle (Res.182 (Rev. Busan, 2014));

ITU plays a key role in the UN E-waste Coalition, is a founding partner of the Global E-waste Statistics Partnership (GESP), and collaborates with the Circular Electronics Partnership.

ITU works towards achieving the 2023 targets related to waste electrical and electronic equipment (WEEE), or ‘e-waste’, established in 2018 by the Plenipotentiary Conference by: increasing the global e-waste recycling rate to 30%; and raising the percentage of countries with e-waste legislation to 50%.

ITU-D has been mandated to assist developing countries in undertaking a proper assessment of the size of e-waste and in initiating pilot projects to achieve environmentally sound management of e-waste through e-waste collection, dismantling, refurbishing, and recycling. To this end, the organisation supports countries in developing national policies on e-waste, and works together with industry partners from the public and private sectors to stimulate coordinated actions towards a circular economy model. ITU-D and ITU-T SGs also explore issues related to ICTs and the environment.

ITU-T has been mandated to pursue and strengthen the development of ITU activities in regard to handling and controlling e-waste from telecommunication and information technology equipment and methods of treating it; and to develop recommendations, methodologies, and other publications relating to sustainable management of e-waste resulting from telecommunications/ICT equipment and products, and appropriate guidelines on the implementation of these recommendations. ITU-T SG5 on Environment, EMF, and the Circular Economy is the lead ITU-T SG on the circular economy and e-waste management.

ITU-T SG5 has a dedicated Question (Q7/5) on ‘E-waste, circular economy, and sustainable supply chain management’. This Question seeks to address the e-waste challenge by identifying the environmental requirements of digital technologies including IoT, end-user equipment, and ICT infrastructures or installations, based on the circular economy principles and improving the supply chain management in line with SDG 12, target 12.5 by 2030, substantially reduce waste generation through prevention, reduction, recycling and reuse.

A case study on the Implementation of ITU-T Standards on Sustainable Management of Waste Electrical and Electronic Equipment: The Path to a Circular Economy in Costa Rica was published in 2021.

In 2021, ITU with the World Economic Forum released a toolkit on extended producer responsibility for e-waste management, with a focus on African countries.

Rights of persons with disabilities 7Within the work of ITU the rights of persons with disabilities are addressed as ‘ICT /digital accessibility for all including persons with disabilities’.

ITU works both to promote globally ICT accessibility for persons with disabilities and to make ITU a more accessible organisation for persons with disabilities – Resolution 175 (Rev. Bucharest, 2022).

Globally, ITU has continued conducting technical work in ITU-R, ITU-T, and ITU-D SGs advancing the use of telecommunications and ICTs for persons with disabilities; and developing resources to support member states in establishing environments that ensure accessible telecommunications/ICTs – work conducted with the participation of persons with disabilities and aligned with the Connect 2030 Agenda. ITU-D advanced regional initiatives linked to ICT accessibility, with projects, training, and events, and provided support to ITU administrations in almost every region, including organising Accessible Americas and Accessible events. More information is available here.

Within the second area of focus, ITU has made progress in implementing its ITU Accessibility Policy for persons with disabilities, with an updated version endorsed by ITU Council 2021.

ITU-D Study Question 7/1 continues to focus on telecommunication/ICT accessibility to enable inclusive communication, especially for persons with disabilities for 2022–2025 as has been agreed at WTDC–22.

The 2021 released SG Question 7/1 report (available free of charge in all UN official languages) with its accompanying video and the focused workshop and webinar confirm the careful attention given to this topic.

ITU’s work on accessibility includes regional events, ICT accessibility assessment, and the publication of new resources and handbooks. ITU has developed capacity-building materials to promote the adoption of accessible solutions, including 15 video tutorials on development and remediation of accessible digital content.

A range of activities is detailed below.

  • Accessible Americas: ICT for ALL, Cuba 2021, featured discussions with policymakers and stakeholders on ICT/digital accessibility in the context of COVID-19.
  • Accessible Africa, virtual, 2021. Five online, interactive workshops sought to strengthen the capacity of 175 regional Focal Points from 42 African countries on ICT/digital accessibility.
  • Accessible Europe: ICT for ALL 2021, virtual, 2021. Over 240 participants from more than 40 countries discussed how to remove barriers to enable the social inclusion of persons with disabilities, through cooperation, programmes, and training.
  • Accessible the Commonwealth of independent states (CIS): In 2021 the CIS Region has shown increased interest in ICT accessibility implementation to ensure equal digital empowerment through ICT.

Assessing and monitoring the implementation of ICT accessibility

WSIS Forum 2021: ICTs and Accessibility for Persons with Disabilities and Specific Needs

  • WSIS Forum 2021 featured ICTs and Accessibility for Persons with Disabilities and Specific Needs, with virtual workshops on innovative technologies, bringing together experts and stakeholders to discuss how to leverage ICTs to help people with blindness and vision impairment and how to provide inclusive education for all – showcasing emerging assistive technologies.

Self-paced online training courses

Other accessibility resources

Events and opportunities to support the global implementation of ICT accessibility

Making ITU a more accessible organisation for persons with disabilities

  • ITU continues to ensure accessibility to persons with disabilities, including staff, delegates, and the general public.
  • To ensure the structure and content of ITU websites, videos, publications, digital documents, and digital information are all digitally accessible, training events are under preparation (will take place in February 2022).
  • To provide fully accessible ITU events, an invitation to bid for the provision of real-time captioning was completed in November 2021. Proposals for captioning in French, Spanish, and Chinese have been submitted.
  • In 2019, ITU provided captioning across ITU events and major conferences, sign language interpretation in selected ITU-T accessibility meetings and in making ITU websites accessible. ITU has also modified internal production to generate accessible publications in the six official languages.

COVID-19: Ensuring digital information is accessible to all

Gender rights online 8Within the work of ITU, gender rights online is addressed as ‘Gender digital divide‘.

ITU is involved in activities aimed at promoting gender equality and the empowerment of women and girls through ICTs.

ITU is custodian of three gender-related SDG indicators: the proportion of individuals who (1) own a mobile phone; (2) use the internet; and (3) have ICT skills. ITU’s Measuring Digital Development: Facts and Figures 2021 shows that, in all regions, the gender Internet divide has been narrowing in recent years, and calls for more action on cultural, financial, and skills-related barriers that impede Internet uptake among women. ITU has launched several targeted efforts to bridge the gender digital divide and advance the Connect 2030 Agenda. Below are some highlights of ITU’s work on gender.

Together with the United Nations Entity for Gender Equality and the Empowerment of Women (UN Women), the United Nations University (UNU), GSMA, and the International Trade Centre (ITC), ITU launched the EQUALS Global Partnership for Gender Equality in the Digital Age with over 100 partners working together to ensure that women are given access, are equipped with skills, and develop the leadership potential to work in the ICT industry. Under this initiative, ITU contributes with the annual flagship event the EQUALS in Tech Awards. The awards are given every year to organisations and individuals working to help girls and women gain equal internet access, learn digital skills, and find opportunities in the tech industry. The initiative is dedicated to encouraging girls and young women to consider studies and careers in ICTs.

The African Girls Can Code Initiative (AGCCI) was started in Africa in collaboration with UN Women and the African Union Commission (AUC) with the aim to train and empower girls and young women aged 17 to 20 across Africa to become computer programmers, creators, and designers. The initiative has also been launched in the Americas region with a focus on equipping girls with coding skills and generating interest in the pursuit of ICT careers.

Other activities such as the Women in Technology Challenge and the EQUALS Women in Tech Network led by ITU are targeted at advancing women’s engagement with ICTs for social and economic development.

ITU WRC-19 also adopted a declaration that promotes gender equality, equity, and parity in the work of the ITU Radiocommunication Sector.

ITU is also the facilitator of WSIS Action Line C4 – Capacity building.

Network of Women (NoW): Encouraging gender balance

Encouraging and tracking gender-balanced representation and nominations of women for key roles strengthens women’s participation in ITU meetings. The aim is to build a community where female delegates can network, share their experience, and promote the participation of women – increasing their visibility, empowering them, and encouraging experienced female delegates to mentor ICT professionals in the digital space.

In 2021, BDT launched the Network of Women (NoW) at the World Telecommunication Development Conference (WTDC) to increase the number of women participating in ITU-D meetings and taking up leadership roles in preparing the WTDC itself. Within this framework, ITU launched the global mentorship programme and fireside discussions.

At the World Radiocommunication Seminar Online 2020, ITU-R launched the NoW for WRC-23 to promote gender equality, equity and parity within the ITU Radiocommunication Sector. The NoW for WRC-19 (#NOW4WRC19) efforts culminated in a Declaration on Promoting Gender Equality, Equity and Parity in the ITU Radiocommunication Sector, adopted at WRC-19 in Sharm El-Sheikh.

Capacity-building that empowers indigenous communities through technology

Capacity-building training for indigenous communities has empowered indigenous people and communities through technology. The training is tailored to needs and interests and has taken into account self-sustainability aspects and cultural legacy.

The programme has reached 70 indigenous participants throughout the Americas, 21 of whom have completed the full programme – from Argentina, Bolivia, Ecuador, Honduras, Mexico, and Peru. Thirty per cent of participants were indigenous women.

The course Technical Promoters in Telecommunications and Broadcasting in Indigenous Communities requires one year of study and trains indigenous professionals in maintaining indigenous networks from infrastructure to communication delivery. The module boosts the professional development of professionals and ability to contribute to their communities’ socio-economic development and self-sustainability.

A further course in 2021, on Innovative Communication Tools on How to Develop, Manage and Operate an Indigenous Radio Network was offered to 141 indigenous participants over two editions. Countries represented included Argentina, Bolivia, Chile, Colombia, Costa Rica, Ecuador, Guatemala, Mexico, Panama, Paraguay, Peru, and Venezuela. Thirty per cent of participants completed all five units of the course, 40.5% of whom were indigenous women.

ITU and UNESCO are developing activities for rollout at the WSIS Forum 2022 as contributions to the International Decade of Indigenous Languages (2022–2032).

Working for digital inclusion for older people-raising awareness and building resources

For the first time, ITU has addressed digital inclusion for older people by raising awareness on the topic, leveraging the capacity of ITU members and stakeholders, providing policy and strategy guidelines, and developing resources to support global efforts to overcome this socio-economic challenge.

Resources supporting older persons in the digital world.

The World Telecommunication and Information Society Day 2022 (WTISD 2022) was dedicated to the theme: Digital technologies for older persons and healthy ageing.

ITU contributing to UN work

Working for increased youth engagement

The ITU Youth Strategy ensures the participation of youth in ITU in implementing the 2030 Agenda for Sustainable Development. The strategy is built on three pillars: creating a community of young leaders, bringing young people together to engage with ITU and members, and fostering participation in ITU activities. More than 40 Youth Task Force members across ITU are coordinating efforts to implement the ITU Youth Strategy.

The initiatives detailed below have been implemented as part of the ITU Youth Strategy.

Generation Connect Initiative

Generation Connect, launched in 2020, prepared the way for the journey to World Telecommunication Development Conference 2022 and the Generation Connect Global Youth Summit in 2022.

Generation Connect Visionaries Board

The Generation Connect Visionaries Board offers guidance to ITU on its youth-related work. The Board, composed of ITU representatives, eight young leaders, and eight high- level appointees, advises on the Youth Summit and the Youth Strategy.

Road to Addis Series – Digital Inclusion and Youth Events

The ITU Road to Addis series of events has a strong youth component. An event on International Youth Day 2021 saw participation of youth as equal partners alongside the leaders of today’s digital change, while the Partner2Connect Meeting 2021 launched the Partner2Connect Coalition.

Implementation of the I-CoDI Youth Challenge

In 2020, ITU organised the International Centre of Digital Innovation (I-CoDI) Youth Challenge on connecting the unconnected. Winning pitches focused on technology and network development, cybersecurity, digital inclusion, climate change and environment, and capacity building.

Generation Connect Virtual Communities

In 2021, ITU launched on Facebook, LinkedIn, and Instagram the new Generation Connect Virtual communities, inviting youth from the regions to join.

ITU: Current co-chair of the United Nations Inter-Agency Network on Youth Development

Since March 2021, ITU has been the co-chair of the United Nations Inter-Agency Network on Youth Development (IANYD) with a one-year mandate. The Network increases the effectiveness of UN work in youth development by strengthening collaboration and exchange across UN entities.

Capacity Building on Meaningful Youth Engagement

Training on Meaningful Youth Engagement for UN staff was delivered to ITU staff in 2020; 174 ITU staff attended, including top management, members of the ITU Youth Task Force, and professional and administrative staff. This training was followed in 2020 by two Pitch for Youth workshops, where teams proposed ideas to an ITU jury on youth engagement initiatives.

Collaboration with the Office of the Secretary-General’s Envoy on Youth

ITU works with the Office of the Envoy on Youth to align the ITU Youth Strategy with the United Nations Youth Strategy: Youth 2030. ITU has engaged with the UN Youth Envoy in various ways including the co-creation of the Digital Technology session of the #YouthLead Innovation Festival and collaboration on how online efforts are helping improve children’s online safety.

Additional initiatives

ITU’s work on empowering youth through ICTs includes the Digital Skills for Jobs Campaign and the ITU Digital Skills Toolkit. In 2020, ITU mounted a Youth Engagement Survey to consult on how ITU can best engage. The results of this survey informed the ITU Youth Strategy.

The ITU Kaleidoscope academic conferences invite students and young researchers to submit original academic papers and video demonstrations of applied research, and share their studies and ideas at the University Exhibit. Kaleidoscope contributes to raising awareness of the crucial importance of investing in science, research, and innovation and to inspiring the younger generations. Young authors, up to 30 years of age, presenting papers at the conference receive Young Author Recognition certificates. For details on Kaleidoscope see Interdisciplinary approaches section.

Interdisciplinary approaches

The WSIS process was initiated by ITU in 1998 and it led the organisation of the Summits in 2003 and 2005 in coordination with the UN system. In line with its mandate and the WSIS outcome documents, ITU continues playing a key lead coordination role in WSIS implementation and follow-up.

The WSIS Forum represents the world’s largest annual gathering of the ICT for development community. Co-organised by ITU, UNESCO, the United Nations Development Programme (UNDP) and the United Nations Conference on Trade and Development (UNCTAD), and in close collaboration with all WSIS Action Line Facilitators/Co-Facilitator, the forum has proven to be an efficient mechanism for coordinating multistakeholder implementation activities, exchanging information, creating knowledge, and sharing best practices. It continues to provide assistance in developing multistakeholder and public/private partnerships to advance development goals. The forum provides structured opportunities to network, learn, and participate in multistakeholder discussions and consultations on WSIS implementation.

The ITU Contribution to the Implementation of the WSIS Outcomes is an annual comprehensive report on ITU activities in the WSIS context from all the three sectors of the organisation (radiocommunication, standardisation, and development sectors) and the General Secretariat on the activities implemented during the respective year. The report provides updates on the tasks carried out by ITU at the operational and policy levels, covering all assigned mandates with reference to the WSIS process.

ITU plays a leading facilitating role in the WSIS implementation process, in collaboration with more than 30 UN agencies in creating an environment for just and equal information and knowledge societies. As per Resolution 1332 (modified 2019) ITU membership resolved to use the WSIS framework as the foundation through which it helps the world to leverage ICTs in achieving the 2030 Agenda, within its mandate and within the allocated resources in the financial plan and biennial budget, noting the WSIS- SDG Matrix developed by UN agencies, This close interlink between the WSIS Action Lines and the SDGs and targets can serve as an important basis for work on relevant areas outlined in relevant ongoing processes, for example UN SGs Our Common Agenda and so on.

ITU’s role in the WSIS process, highlighting the varying role along the WSIS Action Lines:

  • ITU is the sole facilitator for three different WSIS Action Lines: C2 (Information and communication infrastructure), C5 (Building confidence and security in the use of ICTs), and C6 (Enabling environment).
  • ITU has also been taking the lead role in facilitating WSIS Action Line C4 (Capacity building)
  • ITU contributes to all the remaining WSIS Action Lines that are facilitated by other WSIS stakeholders.

The WSIS-SDG Matrix developed by UN WSIS Action Line Facilitators serves as the mechanism to map, analyse, and coordinate the implementation of WSIS Action Lines, and more specifically, ICTs as enablers and accelerators of the SDGs. This mapping exercise draws direct links between the WSIS Action Lines and the proposed SDGs to continue strengthening the impact of ICTs for sustainable development. Building on the Matrix, the Agenda and outcomes of the WSIS Forum are clearly linked to WSIS Action lines and the SDGs highlighting the impact and importance of ICTs on sustainable development.

The WSIS Stocktaking Process provides a register of activities – including projects, programmes, training initiatives, conferences, websites, guidelines, and toolkits – carried out by governments, international organisations, the private sector, civil society, and other entities. To that end, in accordance with paragraph 120 of the Tunis Agenda for the Information Society adopted by WSIS, ITU has been maintaining the WSIS Stocktaking Database since 2004 as a publicly accessible system providing information on ICT-related initiatives and projects with reference to the 11 WSIS action lines (Geneva Plan of Action). The principal role of the WSIS Stocktaking exercise is to leverage the activities of stakeholders working on the implementation of WSIS outcomes and share knowledge and experience of projects by replicating successful models designed to achieve the SDGs of the 2030 Agenda for Sustainable Development.

The WSIS Prizes contest was developed in response to requests from WSIS stakeholders to create an effective mechanism to evaluate projects and activities that leverage the power of ICTs to advance sustainable development. Since its inception, WSIS Prizes has attracted more than 350,000 stakeholders. Following the outcomes of the UN General Assembly Overall Review on WSIS (Res. A/70/125) that called for a close alignment between the WSIS process and the 2030 Agenda for Sustainable Development (Res. A/70/1), WSIS Prizes continues to serve as the unique global platform to identify and showcase success stories in the implementation of the WSIS Action Lines and the SDGs.

The United Nations Group on Information Society (UNGIS) is the UN system’s inter-agency mechanism for advancing policy coherence and programme co-ordination on matters related to ICTs in support of internationally agreed development goals. Established in 2006 after WSIS, its mandate includes promoting collaboration and partnerships among the members of the Chief Executives Board (CEB) to contribute to the achievement of the WSIS goals, providing guidance on issues related to inclusive information and knowledge societies, helping maintain issues related to science and technology at the top of the UN Agenda, and mainstreaming ICT for Development in the mandate of CEB members.

UNGIS remains committed and contributed to the alignment of the WSIS Action Lines and the SDGs.

Partnership on Measuring ICT for Development is an international, multistakeholder initiative to improve the availability and quality of ICT data and indicators.

ITU also works in close collaboration with the Office of the United Nations Secretary-General’s Envoy on Technology and in 2022 announced a first-ever set of targets for universal and meaningful digital connectivity to be achieved by 2030.

The universal meaningful connectivity targets were developed as part of the implementation of the UN Secretary-General’s Roadmap for Digital Cooperation and aim to provide concrete benchmarks for sustainable, inclusive global progress in specified action areas, such as (1) Universality, (2) Technology, and (3) Affordability. These 15 aspirational targets are meant to help countries and stakeholders prioritise interventions, monitor progress, evaluate policy effectiveness, and galvanise efforts around achieving universal and meaningful connectivity by 2030. They are also meant as a contribution towards the forthcoming Global Digital Compact, as proposed in the UN Secretary-General’s Our Common Agenda report. A first assessment of how the world currently stands in relation to the targets is available on ITU’s website here.

Kaleidoscope academic conferences

Kaleidoscope is the ITU flagship event for academia, which brings together a wide range of views from universities, industry, and research institutions of different fields to identify emerging trends in technologies for a digital and sustainable transformation that can benefit humanity. Selected papers are presented at the conference and published in the Conference Proceedings and IEEE Xplore Digital Library. By viewing technologies through a Kaleidoscope, these forward-looking events also seek to identify new topics for ITU’s work. The objective is to hold these events once a year in different parts of the world. Kaleidoscope 2024 on Innovation and digital transformation for a sustainable world will be held in parallel with the World Telecommunication Standardization Assembly 2024 (WTSA-24), on 21-23 October, in New Delhi, India. This 15th Kaleidoscope also aims at engaging youth and future leaders and empowering academia in India.

ITU Journal 

The scholarly ITU Journal on Future and Evolving Technologies (ITU J-FET) provides complete coverage of all communications and networking paradigms. ITU J-FETl considers yet-to-be-published papers addressing fundamental and applied research. It shares new techniques and concepts, analyses, and tutorials, as well as learning from experiments and physical and simulated testbeds. It also discusses the implications of the latest research results for policy and regulation, legal frameworks, the economy and society. This publication builds bridges between disciplines, connects theory with application, and stimulates international dialogue. Its interdisciplinary approach reflects ITU’s comprehensive field of interest and explores the convergence of ICT with other disciplines. 

ITU J-FET is a quarterly publication, free of charge for both readers and authors, which offers a platform to share research on topics of strategic relevance to ITU, such as Internet of Everything​, Terahertz communications​​, Wireless communication systems in beyond 5G era​,  ​​Internet of Bio-Nano Things for health applications,  Towards vehicular networks in the 6G era​,  ​​Emerging trends and applications in future communication networks, ​Integrated and autonomous network management and control for 6G time-critical applications, Digital continuum and next generation networks,  Future of networking beyond 2030​, ​Innovative network solutions for future services, ​​Intelligent surfaces and their applications towards wide-scale deployment​, ​​​​​​​​AI-driven security in 5G and beyond , Network virtualization, slicing, orchestration, fog and edge platforms for 5G and 6G wireless systems​, ​AI for accessibility, Metaverse: Communications, networking and computing, Intelligent technologies for future networking and distributed systems, ​Next generation computer communications and networks, Satellite constellations and connectivity from space​, and AI and machine learning solutions in 5G and future networks.

Under the umbrella of ITU J-FET, a series of webinars has been launched to feature highly cited academics, CTOs, and industry leaders, sharing their pioneering studies and visions, as well as their impactful life lessons learned over the years that might be useful for students and young researchers starting their career in the ICT field. This special series is designed to expand synergies between academia and industry R&D, placing emphasis on 5G and 6G and increasing network intelligence.​

ITU-Tsinghua University Joint Journal 

The Intel​ligent and Conver​ged Networks​​ (ICN) Journal focuses on the latest developments in communication technology. ICN is co-published by Tsinghua University Press (TUP) and ITU. The journal draws its name from the accelerating convergence of different fields of communication technology and the growing influence of AI and machine learning. An open access publication, ICN was launched in 2020. All issues can be downloaded for free at the journal’s online Library and on the IEEE Xplore

Digital tools and initiatives

  • Various platforms used for online meetings: Zoom, Microsoft Teams, and ITU’s MyMeetings platform.
  • The value of ITU-T’s advanced electronic working environment was highlighted in 2020. Virtual meetings and electronic working methods have come to form the principal platform for ITU standardisation work as part of the global response to COVID-19. ITU members engaged in standard development are making optimal use of ITU’s personalised MyWorkspace platform and associated services and tools (e.g. MyMeetings).

Giga: UNICEF-ITU global initiative

Giga is a UNICEF-ITU global initiative to connect every school to the internet and every young person to information, opportunity, and choice. Access to broadband internet and digital learning is critical to global efforts to transform education to make it more inclusive, equitable, and effective. Yet right now, the ability to leverage digital resources is far from equitably distributed: 1.3 billion children have no access to the internet at home and only around half of the world’s schools are online.  

This digital exclusion particularly affects the poorest children, girls, and those with disabilities. These learners miss out on online resources, the option to learn remotely, and the opportunity to develop digital skills. In 2019, the United Nations Children’s Fund (UNICEF) and ITU joined forces to address this new form of inequality by creating Giga, a unique global partnership with the bold ambition to connect every school in the world to the internet by 2030.  

What Giga does

  • Giga maps schools and their internet access. No one knows how many schools there are in the world (approximately 6-7 million). Giga’s Project Connect map provides a real-time display of access and gaps to guide funders and governments and to enable accountability. Giga has mapped over 2.1 million schools across 140 countries.
  • It creates models for innovative financing. It could cost over $400 billion to connect every unconnected school. Giga is working with a diverse array of partners to develop solutions for affordable, sustainable connectivity and aims to mobilise $5 billion to catalyse investment in vital connectivity infrastructure.
  • Giga supports governments contracting for connectivity. It helps governments design the regulatory frameworks, technology solutions, and competitive procurement processes needed to get schools online. Giga and its partners have connected over 2.4 million students in over 5,800 schools.  

Learn more at giga.global 

United for Smart Sustainable Cities (U4SSC) Initiative 

ITU facilitates international discussions on the public policy dimensions of people-centred smart cities, principally through the U4SSC initiative, an initiative supported by 19 UN bodies with the aim of achieving SDG 11 (sustainable cities and communities).

ITU standards have provided a basis for the development of Key Performance Indicators for Smart Sustainable Cities. More than 150 cities worldwide have adopted the indicators as part of a collaboration driven by ITU within the framework of the U4SSC initiative.

To promote the work of the U4SSC, a series of U4SSC Country Hubs has been set up globally including in Vienna, Austria, hosted by the Austrian Economic Centre (AEC), and in Kyebi, Ghana. U4SSC Hubs provide a unique platform at the national and local level to accelerate cooperation between the public and private sector and help facilitate the digital transformation in cities and communities while enabling technology and knowledge transfer.

Social media channels

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LinkedIn @International Telecommunication Union

Podcast @ITUPodcasts

TikTok @itu

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YouTube @itutelecommunication

Sustainable Development

The Commission on Science and Technology for Development (CSTD) is a subsidiary of the UN Economic and Social Council (ECOSOC). It was established to advise the UN General Assembly (UNGA) on science and technology issues through analysis and appropriate policy recommendations. It is the focal point of the UN for science, technology, and innovation for development.

Under the mandate given by ECOSOC, the CSTD leads the follow-up to the outcomes of the World Summit on the Information Society (WSIS) and advises ECOSOC accordingly, including through the elaboration of recommendations aimed at furthering the implementation of the WSIS outcomes. The UN Conference on Trade and Development (UNCTAD) is responsible for the servicing of the CSTD.

Digital activities

The CSTD reviews progress made in the implementation of and follow up to the WSIS outcomes at regional and international levels. It also discusses science, technology, and innovation (STI), including frontier technologies, many of which are digital technologies and are largely linked with digitalisation. Based on thematic reviews and discussions, the CSTD prepares draft resolutions for ECOSOC. These draft resolutions tackle issues ranging from access to the internet and information and communication technologies (ICTs) and frontier technologies to the use of these technologies in achieving sustainable development. Sustainable development is linked particularly to the 2030 Agenda and the 17 sustainable development goals (SDGs), including topics in recent years related to climate action (SDG 13), clean water and sanitation (SDG 6), affordable and clean energy (SDG 7), sustainable cities and communities (SDG 11), Industry 4.0 (under SDG 9), and partnerships (SDG 17). Digital technologies play a role in all SDGs. At each of its annual sessions and intersessional panels, the CSTD addresses two priority themes regarding the use of STI, including digital technologies, in different areas related to the various SDGs.

Digital policy issues

Artificial intelligence 1Within the work of the CSTD, AI is placed under the term ‘frontier technologies’, which also includes big data analytics, biotech and genome editing, and IoT, https://unctad.org/en/Pages/CSTD/CSTDAbout.aspx

As part of its work on assessing the impact of technological change on inclusive and sustainable development, the CSTD is also exploring the role of frontier technologies including artificial intelligence (AI). At its 22nd session, the CSTD pointed out that AI and other frontier technologies offer significant opportunities to accelerate progress in achieving the SDGs, while also posing new challenges (e.g. disrupting labour markets, exacerbating or creating new inequalities, and raising ethical questions). The CSTD focused its 2019–2020 intersessional work on digital frontier technologies, such as AI, big data, and robotics. For 2021, the CSTD chose another digital technology – blockchain for sustainable development – as a priority theme. In 2022, the CSTD deliberated on industry 4.0 technologies (such as AI, big data, IoT, and robotics) for inclusive development. For 2023, the themes were using STI solutions, especially digital technologies to achieve SDG 6 on water and sanitation, and technology and innovation for cleaner and more productive and competitive production (including digital Industry 4 technologies). The most recent themes, for 2024, are Data for Development and Global cooperation in STI for development (which includes cooperation on digital infrastructure and digital technologies).

Access 2In the CSTD’s work, disparities related to access to the internet are referred to as the ‘digital divide’.

During its annual sessions and intersessional panels, as well as in its draft resolutions for ECOSOC, the CSTD tackles aspects related to the digital divide, and outlines the need for further progress in addressing the impediments that developing countries face in accessing new technologies. It often underlines the need for coordinated efforts among all stakeholders to bridge the digital divide in its various dimensions: access to infrastructure, affordability, quality of access, digital skills, gender gap, and others. To this aim, the CSTD recommends policies and actions to improve connectivity and access to infrastructure, affordability, multilingualism and cultural preservation, digital skills and digital literacy, capacity development, and appropriate financing mechanisms. There is an annual follow-up to the progress made on WSIS implementation, which is a critical international process for evaluating progress in overcoming the digital divide in internet access within and across countries. There is also a 20-year review of WSIS that is now beginning, called WSIS+20, which will be held in 2025 in the General Assembly. The CSTD has been undertaking a series of global and regional open consultations  to gather inputs from multistakeholders for its report on WSIS+20 to be submitted, through ECOSOC, to the General Assembly in 2025. 

Sustainable development

As the UN focal point for STIfor development, the CSTD analyses the impact of digital technologies on sustainable development (assessing opportunities, risks, and challenges), including from the perspective of the principle of ‘leaving no one behind’. The CSTD also works to identify strategies, policies, and actions to foster the use of technology to empower people and ensure inclusiveness and equality. In addition, it acts as a forum for strategic planning, the sharing of good practices, and providing foresight about emerging and disruptive technologies. 

Capacity development

Capacity development is one of the recurring themes that appear in draft resolutions prepared by the CSTD on the implementation of and follow-up to the WSIS outcomes. The CSTD often emphasises the need for countries and other stakeholders to focus on capacity development policies and actions to further enhance the role of the internet as a catalyst for growth and development. Strengthening the capacity of stakeholders to participate in internet governance processes is another objective the CSTD has been calling for, especially in regard to the Internet Governance Forum (IGF). 

Interdisciplinary approaches: Internet governance

The CSTD was mandated to review the IGF process and suggest improvements. To this aim, the Working Group on Improvements to the IGF was established and a report recommending a number of action items regarding the IGF was delivered in 2012. The CSTD was also entrusted with the mandate to initiate discussions about enhanced cooperation in internet governance. It convened two working groups on enhanced cooperation (2013–2014 and 2016–2018); although consensus seemed to emerge on some issues, a divergence of views persisted on others and the Working Group could not reach consensus on recommendations on how to further implement enhanced cooperation as envisioned in the Tunis Agenda.

UNCTAD is in charge of servicing the CSTD. As such, digital tools used by UNCTAD, for example, platform for online meetings, and social media for communications purposes are also employed for CSTD-related purposes. For instance, the 23rd and 24th CSTD annual sessions as well as the intersessional panel of the 24th CSTD were purely virtual, using the Interprefy platform. The intersessional panel and the annual session of the 25th CSTD were hybrid, combining online and in-person participation. The online platforms used were Interprefy and Zoom, respectively.

Digital tools

UNCTAD is in charge of servicing the CSTD. As such, digital tools used by UNCTAD (e.g. platform for online meetings, social media for communications purposes) are also employed for CSTD-related purposes. For example, the 23rd and 24th CSTD annual sessions as well as the intersessional panel of the 24th CSTD were purely virtual, using the Interprefy platform. The intersessional panel and the annual session of the 25th CSTD were hybrid, combining online and in-person participation. The online platforms used were Interprefy and Zoom, respectively. CSTD meetings have returned to a more conventional in-person format, but digital platforms remain widely in use for the work of the CSTD.

Social media channels

Facebook @UNCTAD

Flickr @UNCTAD

Instagram @unctad

LinkedIn @UNCTAD

X @UNCTAD

YouTube @UNCTADOnline


Human Rights

The GSPI is a neutral and independent platform that aims to foster engagement between the research community and Geneva-based international policy actors around some of the most pressing global challenges (including global health, climate change, and migration). 

It works to foster science-policy ecosystems by brokering collaborations and enhancing capacities across the interface between the science, policy, and implementation communities. This includes an annual call for projects, the Impact Collaboration Programme (ICP), the production of policy briefs, as well as learning opportunities and resources to advance the professionalisation and recognition of the science-policy field of practice in Geneva and beyond.

The GSPI is based at the University of Geneva. It receives support from the Swiss Federal Department of Foreign Affairs (FDFA) and the backing of leading research institutions in Switzerland and Europe.

Digital activities

As part of its activities at the interplay between science, policy, and implementation actors, the GSPI tackles a range of digital issues. With data being a centrepiece of evidence-based policies, many of the GSPI’s activities touch on digitalisation and the use of digital tools in domains such as health, migration, development, and the environment.

Digital policy issues

Artificial intelligence

The project MapMaker, a collaboration between the International Union for Conservation of Nature (IUCN) and the Swiss Federal Institute of Technology in Zürich (ETH Zurich) has enabled the development of an online visualisation tool to inform data-driven decision-making on marine biodiversity conservation at the international level.

Digital standards

Together with the Geneva Health Forum (GHF), the GSPI has established a working group including key humanitarian actors to harness knowledge and best practices around the digitisation of clinical guidelines for management of childhood illness in primary care in low and middle-income countries. In line with the efforts of the WHO, and the principles of donor alignment for digital health, the working group has developed recommendations on how digitalisation can improve the management of childhood illness. In September 2021, the results of this work were shared with experts and the public, providing a platform for discussions on the lessons learned and future trends in the field.

Emerging technologies

In 2018, the GSPI organised policy discussions on the use of drones as part of humanitarian action. The conversation centred on the practical use of drones to deliver humanitarian aid and what can be done by stakeholders such as policymakers, the private sector, and non-governmental organisations (NGOs) to maximise the opportunities and reduce the risks of such technologies.

At the 2019 Digital Day, together with the University of Geneva, the GSPI organised a discussion exploring what experience and know-how Geneva-based organisations could share to empower and protect users in the context of the digital revolution.

With a number of other partners, the GSPI co-organised a discussion at the 2019 WSIS Forum on aerial data produced by drones and satellites in the context of aid and development. The session explored the interplay between international organisations, NGOs, and scientists and how they can work together to help monitor refugee settlements, provide emergency response in case of natural disasters, and scale agriculture programmes.

Data governance

The project REDEHOPE of the University of Geneva and the UN Economic Commission for Europe (UNECE) has led to the development of an online diagnostic tool to help countries identify and visualise issues in their housing data ecology, and access appropriate datasets to formulate more robust, evidence-based housing policies at the country level.

Sustainable development

In 2020–2021, the Basel, Rotterdam and Stockholm Convention (BRS) secretariat benefitted from the support of ETH Zurich to develop an online platform to identify and signal the need for evidence and information to the scientific community in the field of chemical and waste management.

A project from ICP 2021 addressed the hurdles facing policy actors in accessing and making sense of data in migration research. The project partners (the International Organization for Migration (IOM) and the Graduate Institute) developed an interactive digital toolkit for policy officials to support them in leveraging migration research for evidence-based policymaking. The toolkit, based on IOM’s flagship publication, the World Migration Report, was launched in June 2022.

ICP 2021 brought support to the development of interactive analytical tools providing information about all UN sanctions to inform both humanitarian practitioners and sanction policy actors on practical ways to safeguard principled humanitarian action in areas under a sanction regime. This project is a collaboration between the Graduate Institute and the Norwegian Refugee Council (NRC).

ICP 2022 selected a collaboration between ETH Zurich and IOM that seeks to bring more effective policy expertise in the management of migration to address migrants’ needs and increase social cohesion between migrant and local communities. The collaboration will develop a toolbox to be used by IOM and its partners to facilitate the use of the Immigration Policy Lab (IPL) Integration Index, a survey tool for governments, nonprofits, and researchers to measure the integration of immigrants around the world.

Human rights principles

Also in the framework of its ICP, the GSPI has supported a collaboration between the Geneva Academy of International Humanitarian Law and Human Rights and OHCHR’s B-Tech project. Some of the new fast-evolving technologies, such as cloud computing, artificial intelligence (AI), facial recognition technologies, and the internet of things (IoT), can have profoundly disrupting effects on sociopolitical systems and pose significant human rights challenges. This initiative provides authoritative guidance and resources for implementing the UNGPs in the technology space and placing international human rights law (IHRL) at the centre of regulatory and policy frameworks. Aimed at policymakers, the technology sector, and all those working on the regulation of AI, the policy research carried out in this project (see resulting Working Paper, 2021) brings fresh insights into how current initiatives on the regulation of AI technologies could incorporate the protection and respect for human rights. Published by the Geneva Academy, the paper also calls on states to adopt a ‘smart mix’ of mandatory and voluntary measures to support their implementation and how this applies to the AI sector. This GSPI-supported science-policy process will formally feed the development of a ‘UN Guiding Principles check’ tool (working title), which will provide states with a roadmap to assess their regulatory efforts across different policy domains relevant to technology.

Digital tools

Social media channels

LinkedIn @genevaspi

Twitter @GenevaSPI

Artificial Intelligence

The Commission on Science and Technology for Development (CSTD) is a subsidiary of the UN Economic and Social Council (ECOSOC). It was established to advise the UN General Assembly (UNGA) on science and technology issues through analysis and appropriate policy recommendations. It is the focal point of the UN for science, technology, and innovation for development.

Under the mandate given by ECOSOC, the CSTD leads the follow-up to the outcomes of the World Summit on the Information Society (WSIS) and advises ECOSOC accordingly, including through the elaboration of recommendations aimed at furthering the implementation of the WSIS outcomes. The UN Conference on Trade and Development (UNCTAD) is responsible for the servicing of the CSTD.

Digital activities

The CSTD reviews progress made in the implementation of and follow up to the WSIS outcomes at regional and international levels. It also discusses science, technology, and innovation (STI), including frontier technologies, many of which are digital technologies and are largely linked with digitalisation. Based on thematic reviews and discussions, the CSTD prepares draft resolutions for ECOSOC. These draft resolutions tackle issues ranging from access to the internet and information and communication technologies (ICTs) and frontier technologies to the use of these technologies in achieving sustainable development. Sustainable development is linked particularly to the 2030 Agenda and the 17 sustainable development goals (SDGs), including topics in recent years related to climate action (SDG 13), clean water and sanitation (SDG 6), affordable and clean energy (SDG 7), sustainable cities and communities (SDG 11), Industry 4.0 (under SDG 9), and partnerships (SDG 17). Digital technologies play a role in all SDGs. At each of its annual sessions and intersessional panels, the CSTD addresses two priority themes regarding the use of STI, including digital technologies, in different areas related to the various SDGs.

Digital policy issues

Artificial intelligence 1Within the work of the CSTD, AI is placed under the term ‘frontier technologies’, which also includes big data analytics, biotech and genome editing, and IoT, https://unctad.org/en/Pages/CSTD/CSTDAbout.aspx

As part of its work on assessing the impact of technological change on inclusive and sustainable development, the CSTD is also exploring the role of frontier technologies including artificial intelligence (AI). At its 22nd session, the CSTD pointed out that AI and other frontier technologies offer significant opportunities to accelerate progress in achieving the SDGs, while also posing new challenges (e.g. disrupting labour markets, exacerbating or creating new inequalities, and raising ethical questions). The CSTD focused its 2019–2020 intersessional work on digital frontier technologies, such as AI, big data, and robotics. For 2021, the CSTD chose another digital technology – blockchain for sustainable development – as a priority theme. In 2022, the CSTD deliberated on industry 4.0 technologies (such as AI, big data, IoT, and robotics) for inclusive development. For 2023, the themes were using STI solutions, especially digital technologies to achieve SDG 6 on water and sanitation, and technology and innovation for cleaner and more productive and competitive production (including digital Industry 4 technologies). The most recent themes, for 2024, are Data for Development and Global cooperation in STI for development (which includes cooperation on digital infrastructure and digital technologies).

Access 2In the CSTD’s work, disparities related to access to the internet are referred to as the ‘digital divide’.

During its annual sessions and intersessional panels, as well as in its draft resolutions for ECOSOC, the CSTD tackles aspects related to the digital divide, and outlines the need for further progress in addressing the impediments that developing countries face in accessing new technologies. It often underlines the need for coordinated efforts among all stakeholders to bridge the digital divide in its various dimensions: access to infrastructure, affordability, quality of access, digital skills, gender gap, and others. To this aim, the CSTD recommends policies and actions to improve connectivity and access to infrastructure, affordability, multilingualism and cultural preservation, digital skills and digital literacy, capacity development, and appropriate financing mechanisms. There is an annual follow-up to the progress made on WSIS implementation, which is a critical international process for evaluating progress in overcoming the digital divide in internet access within and across countries. There is also a 20-year review of WSIS that is now beginning, called WSIS+20, which will be held in 2025 in the General Assembly. The CSTD has been undertaking a series of global and regional open consultations  to gather inputs from multistakeholders for its report on WSIS+20 to be submitted, through ECOSOC, to the General Assembly in 2025. 

Sustainable development

As the UN focal point for STIfor development, the CSTD analyses the impact of digital technologies on sustainable development (assessing opportunities, risks, and challenges), including from the perspective of the principle of ‘leaving no one behind’. The CSTD also works to identify strategies, policies, and actions to foster the use of technology to empower people and ensure inclusiveness and equality. In addition, it acts as a forum for strategic planning, the sharing of good practices, and providing foresight about emerging and disruptive technologies. 

Capacity development

Capacity development is one of the recurring themes that appear in draft resolutions prepared by the CSTD on the implementation of and follow-up to the WSIS outcomes. The CSTD often emphasises the need for countries and other stakeholders to focus on capacity development policies and actions to further enhance the role of the internet as a catalyst for growth and development. Strengthening the capacity of stakeholders to participate in internet governance processes is another objective the CSTD has been calling for, especially in regard to the Internet Governance Forum (IGF). 

Interdisciplinary approaches: Internet governance

The CSTD was mandated to review the IGF process and suggest improvements. To this aim, the Working Group on Improvements to the IGF was established and a report recommending a number of action items regarding the IGF was delivered in 2012. The CSTD was also entrusted with the mandate to initiate discussions about enhanced cooperation in internet governance. It convened two working groups on enhanced cooperation (2013–2014 and 2016–2018); although consensus seemed to emerge on some issues, a divergence of views persisted on others and the Working Group could not reach consensus on recommendations on how to further implement enhanced cooperation as envisioned in the Tunis Agenda.

UNCTAD is in charge of servicing the CSTD. As such, digital tools used by UNCTAD, for example, platform for online meetings, and social media for communications purposes are also employed for CSTD-related purposes. For instance, the 23rd and 24th CSTD annual sessions as well as the intersessional panel of the 24th CSTD were purely virtual, using the Interprefy platform. The intersessional panel and the annual session of the 25th CSTD were hybrid, combining online and in-person participation. The online platforms used were Interprefy and Zoom, respectively.

Digital tools

UNCTAD is in charge of servicing the CSTD. As such, digital tools used by UNCTAD (e.g. platform for online meetings, social media for communications purposes) are also employed for CSTD-related purposes. For example, the 23rd and 24th CSTD annual sessions as well as the intersessional panel of the 24th CSTD were purely virtual, using the Interprefy platform. The intersessional panel and the annual session of the 25th CSTD were hybrid, combining online and in-person participation. The online platforms used were Interprefy and Zoom, respectively. CSTD meetings have returned to a more conventional in-person format, but digital platforms remain widely in use for the work of the CSTD.

Social media channels

Facebook @UNCTAD

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Instagram @unctad

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EU Artificial Intelligence Act

Regulation of the European Parliament and of the Council laying down harmonised rules on artificial intelligence (Artificial Intelligence Act) and amending certain union legislative acts

Introduction

THE EUROPEAN PARLIAMENT AND THE COUNCIL OF THE EUROPEAN UNION,

Having regard to the Treaty on the Functioning of the European Union, and in particular Articles 16 and 114 thereof,

Having regard to the proposal from the European Commission,

After transmission of the draft legislative act to the national parliaments,

Having regard to the opinion of the European Economic and Social Committee1 OJ C […], […], p. […],

Having regard to the opinion of the European Central Bank2Reference to ECB opinion,

Having regard to the joint opinion of the European Data Protection Board and the European Data Protection Supervisor,

Having regard to the opinion of the Committee of the Regions3OJ C […], […], p. […],

Acting in accordance with the ordinary legislative procedure,

Whereas:

(1) The purpose of this Regulation is to improve the functioning of the internal market by laying down a uniform legal framework in particular for the development, placing on the market, putting into service and the use of artificial intelligence systems in the Union in conformity with Union values, to promote the uptake of human centric and trustworthy artificial intelligence while ensuring a high level of protection of health, safety, fundamental rights enshrined in the Charter, including democracy and rule of law and environmental protection, against harmful effects of artificial intelligence systems in the Union and to support innovation. This regulation ensures the free movement of AI-based goods and services cross-border, thus preventing Member States from imposing restrictions on the development, marketing and use of Artificial Intelligence systems (AI systems), unless explicitly authorised by this Regulation.

(1a) This Regulation should be applied in conformity with the values of the Union enshrined in the Charter facilitating the protection of individuals, companies, democracy and rule of law and the environment while boosting innovation and employment and making the Union a leader in the uptake of trustworthy AI.

(2) AI systems can be easily deployed in multiple sectors of the economy and society, including cross border, and circulate throughout the Union. Certain Member States have already explored the adoption of national rules to ensure that artificial intelligence is trustworthy and safe and is developed and used in compliance with fundamental rights obligations. Differing national rules may lead to fragmentation of the internal market and decrease legal certainty for operators that develop, import or use AI systems. A consistent and high level of protection throughout the Union should therefore be ensured in order to achieve trustworthy AI, while divergences hampering the free circulation, innovation, deployment and uptake of AI systems and related products and services within the internal market should be prevented, by laying down uniform obligations for operators and guaranteeing the uniform protection of overriding reasons of public interest and of rights of persons throughout the internal market based on Article 114 of the Treaty on the Functioning of the European Union (TFEU). To the extent that this Regulation contains specific rules on the protection of individuals with regard to the processing of personal data concerning restrictions of the use of AI systems for remote biometric identification for the purpose of law enforcement, for the use of AI systems for risk assessments of natural persons for the purpose of law enforcement and for the use of AI systems of biometric categorization for the purpose of law enforcement, it is appropriate to base this Regulation, in as far as those specific rules are concerned, on Article 16 of the TFEU. In light of those specific rules and the recourse to Article 16 TFEU, it is appropriate to consult the European Data Protection Board.

(3) Artificial intelligence is a fast evolving family of technologies that contributes to a wide
array of economic, environmental and societal benefits across the entire spectrum of
industries and social activities. By improving prediction, optimising operations and
resource allocation, and personalising digital solutions available for individuals and
organisations, the use of artificial intelligence can provide key competitive advantages to
companies and support socially and environmentally beneficial outcomes, for example in
healthcare, farming, food safety, education and training, media, sports, culture,
infrastructure management, energy, transport and logistics, public services, security,
justice, resource and energy efficiency, environmental monitoring, the conservation and
restoration of biodiversity and ecosystems and climate change mitigation and adaptation.

(4) At the same time, depending on the circumstances regarding its specific application, use, and level of technological development, artificial intelligence may generate risks and cause harm to public interests and fundamental rights that are protected by Union law. Such harm might be material or immaterial, including physical, psychological, societal or economic harm.

(4a) Given the major impact that artificial intelligence can have on society and the need to build trust, it is vital for artificial intelligence and its regulatory framework to be developed according to Union values enshrined in Article 2 TEU, the fundamental rights and freedoms enshrined in the Treaties, the Charter. As a pre-requisite, artificial intelligence should be a human-centric technology. It should serve as a tool for people, with the ultimate aim of increasing human well-being.

(4aa) In order to ensure a consistent and high level of protection of public interests as regards health, safety and fundamental rights, common rules for all high-risk AI systems should be established. Those rules should be consistent with the Charter of fundamental rights of the European Union (the Charter) and should be non-discriminatory and in line with the Union’s international trade commitments. They should also take into account the European Declaration on Digital Rights and Principles for the Digital Decade (2023/C 23/01) and the Ethics Guidelines for Trustworthy Artificial Intelligence (AI) of the High-Level Expert Group on Artificial Intelligence.

(5) A Union legal framework laying down harmonised rules on artificial intelligence is therefore needed to foster the development, use and uptake of artificial intelligence in the internal market that at the same time meets a high level of protection of public interests, such as health and safety and the protection of fundamental rights, including democracy, rule of law and environmental protection as recognised and protected by Union law. To achieve that objective, rules regulating the placing on the market, putting into service and use of certain AI systems should be laid down, thus ensuring the smooth functioning of the internal market and allowing those systems to benefit from the principle of free movement of goods and services. These rules should be clear and robust in protecting fundamental rights, supportive of new innovative solutions, enabling to a European ecosystem of public and private actors creating AI systems in line with Union values and unlocking the potential of the digital transformation across all regions of the Union. By laying down those rules as well as measures in support of innovation with a particular focus on SMEs including startups, this Regulation supports the objective of promoting the European human-centric approach to AI and being a global leader in the development of secure, trustworthy and ethical artificial intelligence as stated by the European Council4European Council, Special meeting of the European Council (1 and 2 October 2020) – Conclusions, EUCO 13/20, 2020, p. 6., and it ensures the protection of ethical principles, as specifically requested by the the European Parliament5European Parliament resolution of 20 October 2020 with recommendations to the Commission on a framework of ethical aspects of artificial intelligence, robotics and related technologies, 2020/2012(INL)..

(5a) The harmonised rules on the placing on the market, putting into service and use of AI systems laid down in this Regulation should apply across sectors and, in line with its New Legislative Framework approach, should be without prejudice to existing Union law, notably on data protection, consumer protection, fundamental rights, employment, and protection of workers, and product safety, to which this Regulation is complementary. As a consequence all rights and remedies provided for by such Union law to consumers, and other persons who may be negatively impacted by AI systems, including as regards the compensation of possible damages pursuant to Council Directive 85/374/EEC of 25 July 1985 on the approximation of the laws, regulations and administrative provisions of the Member States concerning liability for defective products, remain unaffected and fully applicable. Furthermore, in the context of employment and protection of workers, this Regulation should therefore not affect Union law on social policy and national labour law, in compliance with Union law, concerning employment and working conditions, including health and safety at work and the relationship between employers and workers. This Regulation should also not affect the exercise of fundamental rights as recognised in the Member States and at Union level, including the right or freedom to strike or to take other action covered by the specific industrial relations systems in Member States as well as, the right to negotiate, to conclude and enforce collective agreements or to take collective action in accordance with national law. [This Regulation should not affect the provisions aiming to improve working conditions in platform work set out in Directive … [COD 2021/414/EC]] On top of that, this Regulation aims to strengthen the effectiveness of such existing rights and remedies by establishing specific requirements and obligations, including in respect of transparency, technical documentation and record-keeping of AI systems. Furthermore, the obligations placed on various operators involved in the AI value chain under this Regulation should apply without prejudice to national laws, in compliance with Union law, having the effect of limiting the use of certain AI systems where such laws fall outside the scope of this Regulation or pursue other legitimate public interest objectives than those pursued by this Regulation. For example, national labour law and the laws on the protection of minors (i.e. persons below the age of 18) taking into account the United Nations General Comment No 25 (2021) on children’s rights, insofar as they are not specific to AI systems and pursue other legitimate public interest objectives, should not be affected by this Regulation.

(5aa) The fundamental right to the protection of personal data is safeguarded in particular by Regulations (EU) 2016/679 and (EU) 2018/1725 and Directive 2016/680. Directive 2002/58/EC additionally protects private life and the confidentiality of communications, including by way of providing conditions for any personal and non-personal data storing in and access from terminal equipment. Those Union legal acts provide the basis for sustainable and responsible data processing, including where datasets include a mix of personal and non-personal data. This Regulation does not seek to affect the application of existing Union law governing the processing of personal data, including the tasks and powers of the independent supervisory authorities competent to monitor compliance with those instruments. It also does not affect the obligations of providers and deployers of AI systems in their role as data controllers or processors stemming from national or Union law on the protection of personal data in so far as the design, the development or the use of AI systems involves the processing of personal data. It is also appropriate to clarify that data subjects continue to enjoy all the rights and guarantees awarded to them by such Union law, including the rights related to solely automated individual decision-making, including profiling. Harmonised rules for the placing on the market, the putting into service and the use of AI systems established under this Regulation should facilitate the effective implementation and enable the exercise of the data subjects’ rights and other remedies guaranteed under Union law on the protection of personal data and of other fundamental rights.

(5ab) This Regulation should be without prejudice to the provisions regarding the liability of intermediary service providers set out in Directive 2000/31/EC of the European Parliament and of the Council [as amended by the Digital Services Act].

The notion of AI system in this Regulation should be clearly defined and closely aligned with the work of international organisations working on artificial intelligence to ensure legal certainty, facilitate international convergence and wide acceptance, while providing the flexibility to accommodate the rapid technological developments in this field. Moreover, it should be based on key characteristics of artificial intelligence systems, that distinguish it from simpler traditional software systems or programming approaches and should not cover systems that are based on the rules defined solely by natural persons to automatically execute operations. A key characteristic of AI systems is their capability to infer. This inference refers to the process of obtaining the outputs, such as predictions, content, recommendations, or decisions, which can influence physical and virtual environments and to a capability of AI systems to derive models and/or algorithms from inputs/data. The techniques that enable inference while building an AI system include machine learning approaches that learn from data how to achieve certain objectives; and logic- and knowledge-based approaches that infer from encoded knowledge or symbolic representation of the task to be solved. The capacity of an AI system to infer goes beyond basic data processing, enable learning, reasoning or modelling. The term “machine-based” refers to the fact that AI systems run on machines. The reference to explicit or implicit objectives underscores that AI systems can operate according to explicit defined objectives or to implicit objectives. The objectives of the AI system may be different from the intended purpose of the AI system in a specific context. For the purposes of this Regulation, environments should be understood as the contexts in which the AI systems operate, whereas outputs generated by the AI system, reflect different functions performed by AI systems and include predictions, content, recommendations or decisions. AI systems are designed to operate with varying levels of autonomy, meaning that they have some degree of independence of actions from human involvement and of capabilities to operate without human intervention. The adaptiveness that an AI system could exhibit after deployment, refers to self-learning capabilities, allowing the system to change while in use. AI systems can be used on a stand-alone basis or as a component of a product, irrespective of whether the system is physically integrated into the product (embedded) or serve the functionality of the product without being integrated therein (non-embedded).

(6a)  The notion of ‘deployer’ referred to in this Regulation should be interpreted as any natural or legal person, including a public authority, agency or other body, using an AI system under its authority, except where the AI system is used in the course of a personal non professional activity. Depending on the type of AI system, the use of the system may affect persons other than the deployer.

(7) The notion of biometric data used in this Regulation should be interpreted in light of the notion of biometric data as defined in Article 4(14) of Regulation (EU) 2016/679 of the European Parliament and of the Council6Regulation (EU) 2016/679 of the European Parliament and of the Council of 27 April 2016 on the protection of natural persons with regard to the processing of personal data and on the free movement of such data, and repealing Directive 95/46/EC (General Data Protection Regulation) (OJ L 119, 4.5.2016, p. 1)., Article 3(18) of Regulation (EU) 2018/1725 of the European Parliament and of the Council7Regulation (EU) 2018/1725 of the European Parliament and of the Council of 23 October 2018 on the protection of natural persons with regard to the processing of personal data by the Union institutions, bodies, offices and agencies and on the free movement of such data, and repealing Regulation (EC) No 45/2001 and Decision No 1247/2002/EC (OJ L 295, 21.11.2018, p. 39) and Article 3(13) of Directive (EU) 2016/680 of the European Parliament and of the Council8Directive (EU) 2016/680 of the European Parliament and of the Council of 27 April 2016 on the protection of natural persons with regard to the processing of personal data by competent authorities for the purposes of the prevention, investigation, detection or prosecution of criminal offences or the execution of criminal penalties, and on the free movement of such data, and repealing Council Framework Decision 2008/977/JHA (Law Enforcement Directive) (OJ L 119, 4.5.2016, p. 89)..Biometric data can allow for the authentication, identification or categorisation of natural persons and for the recognition of emotions of natural persons.

(7a)  The notion of biometric identification as used in this Regulation should be defined as the automated recognition of physical, physiological and behavioural human features such as the face, eye movement, body shape, voice, prosody, gait, posture, heart rate, blood pressure, odour, keystrokes characteristics, for the purpose of establishing an individual’s identity by comparing biometric data of that individual to stored biometric data of individuals in a reference database, irrespective of whether the individual has given its consent or not. This excludes AI systems intended to be used for biometric verification, which includes authentication, whose sole purpose is to confirm that a specific natural person is the person he or she claims to be and to confirm the identity of a natural person for the sole purpose of having access to a service, unlocking a device or having security access to premises.

(7b)  The notion of biometric categorisation as used in this Regulation should be defined as assigning natural persons to specific categories on the basis of their biometric data. Such specific categories can relate to aspects such as sex, age, hair colour, eye colour, tattoos, behavioural or personality traits, language, religion, membership of a national minority, sexual or political orientation. This does not include biometric categorization systems that are a purely ancillary feature intrinsically linked to another commercial service meaning that the feature cannot, for objective technical reasons, be used without the principal service and the integration of that feature or functionality is not a means to circumvent the applicability of the rules of this Regulation. For example, filters categorizing facial or body features used on online marketplaces could constitute such an ancillary feature as they can only be used in relation to the principal service which consists in selling a product by allowing the consumer to preview the display of the product on him or herself and help the consumer to make a purchase decision. Filters used on online social network services which categorise facial or body features to allow users to add or modify pictures or videos could also be considered as ancillary feature as such filter cannot be used without the principal service of the social network services consisting in the sharing of content online.

(8) The notion of remote biometric identification system as used in this Regulation should be defined functionally, as an AI system intended for the identification of natural persons without their active involvement, typically at a distance, through the comparison of a person’s biometric data with the biometric data contained in a reference database, irrespectively of the particular technology, processes or types of biometric data used. Such remote biometric identification systems are typically used to perceive multiple persons or their behaviour simultaneously in order to facilitate significantly the identification of natural persons without their active involvement. This excludes AI systems intended to be used for biometric verification, which includes authentication, whose sole purpose is to confirm that a specific natural person is the person he or she claims to be and to confirm the identity of a natural person for the sole purpose of having access to a service, unlocking a device or having security access to premises. This exclusion is justified by the fact that such systems are likely to have a minor impact on fundamental rights of natural persons compared to the remote biometric identification systems which may be used for the processing of the biometric data of a large number of persons without their active involvement. In the case of ‘real-time’ systems, the capturing of the biometric data, the comparison and the identification occur all instantaneously, near-instantaneously or in any event without a significant delay. In this regard, there should be no scope for circumventing the rules of this Regulation on the ‘real-time’ use of the AI systems in question by providing for minor delays. ‘Real-time’ systems involve the use of ‘live’ or ‘near-‘live’ material, such as video footage, generated by a camera or other device with similar functionality. In the case of ‘post’ systems, in contrast, the biometric data have already been captured and the comparison and identification occur only after a significant delay. This involves material, such as pictures or video footage generated by closed circuit television cameras or private devices, which has been generated before the use of the system in respect of the natural persons concerned. The notion of remote biometric identification system as used in this Regulation should be defined functionally, as an AI system intended for the identification of natural persons without their active involvement, typically at a distance, through the comparison of a person’s biometric data with the biometric data contained in a reference database, irrespectively of the particular technology, processes or types of biometric data used. Such remote biometric identification systems are typically used to perceive multiple persons or their behaviour simultaneously in order to facilitate significantly the identification of natural persons without their active involvement. This excludes AI systems intended to be used for biometric verification, which includes authentication, whose sole purpose is to confirm that a specific natural person is the person he or she claims to be and to confirm the identity of a natural person for the sole purpose of having access to a service, unlocking a device or having security access to premises. This exclusion is justified by the fact that such systems are likely to have a minor impact on fundamental rights of natural persons compared to the remote biometric identification systems which may be used for the processing of the biometric data of a large number of persons without their active involvement. In the case of ‘real-time’ systems, the capturing of the biometric data, the comparison and the identification occur all instantaneously, near-instantaneously or in any event without a significant delay. In this regard, there should be no scope for circumventing the rules of this Regulation on the ‘real-time’ use of the AI systems in question by providing for minor delays. ‘Real-time’ systems involve the use of ‘live’ or ‘near-‘live’ material, such as video footage, generated by a camera or other device with similar functionality. In the case of ‘post’ systems, in contrast, the biometric data have already been captured and the comparison and identification occur only after a significant delay. This involves material, such as pictures or video footage generated by closed circuit television cameras or private devices, which has been generated before the use of the system in respect of the natural persons concerned.

(8a)  The notion of emotion recognition system for the purpose of this regulation should be defined as an AI system for the purpose of identifying or inferring emotions or intentions of natural persons on the basis of their biometric data. This refers to emotions or intentions such as happiness, sadness, anger, surprise, disgust, embarrassment, excitement, shame, contempt, satisfaction and amusement. It does not include physical states, such as pain or fatigue. It does not refer for example to systems used in detecting the state of fatigue of professional pilots or drivers for the purpose of preventing accidents. It does also not include the mere detection of readily apparent expressions, gestures or movements, unless they are used for identifying or inferring emotions. These expressions can be basic facial expressions such as a frown or a smile, or gestures such as the movement of hands, arms or head, or characteristics of a person’s voice, for example a raised voice or whispering.

(9) For the purposes of this Regulation the notion of publicly accessible space should be understood as referring to any physical place that is accessible to an undetermined number of natural persons, and irrespective of whether the place in question is privately or publicly owned and irrespective of the activity for which the place may be used, such as commerce (for instance, shops, restaurants, cafés), services (for instance, banks, professional activities, hospitality), sport (for instance, swimming pools, gyms, stadiums), transport (for instance, bus, metro and railway stations, airports, means of transport ), entertainment (for instance, cinemas, theatres, museums, concert and conference halls) leisure or otherwise (for instance, public roads and squares, parks, forests, playgrounds). A place should be classified as publicly accessible also if, regardless of potential capacity or security restrictions, access is subject to certain predetermined conditions, which can be fulfilled by an undetermined number of persons, such as purchase of a ticket or title of transport, prior registration or having a certain age. By contrast, a place should not be considered publicly accessible if access is limited to specific and defined natural persons through either Union or national law directly related to public safety or security or through the clear manifestation of will by the person having the relevant authority on the place. The factual possibility of access alone (e.g. an unlocked door, an open gate in a fence) does not imply that the place is publicly accessible in the presence of indications or circumstances suggesting the contrary (e.g. signs prohibiting or restricting access). Company and factory premises as well as offices and workplaces that are intended to be accessed only by relevant employees and service providers are places that are not publicly accessible. Publicly accessible spaces should not include prisons or border control. Some other areas may be composed of both not publicly accessible and publicly accessible areas, such as the hallway of a private residential building necessary to access a doctor’s office or an airport. Online spaces are not covered either, as they are not physical spaces. Whether a given space is accessible to the public should however be determined on a case-by-case basis, having regard to the specificities of the individual situation at hand.

(9b) In order to obtain the greatest benefits from AI systems while protecting fundamental rights, health and safety and to enable democratic control, AI literacy should equip providers, deployers and affected persons with the necessary notions to make informed decisions regarding AI systems. These notions may vary with regard to the relevant context and can include understanding the correct application of technical elements during the AI system’s development phase, the measures to be applied during its use, the suitable ways in which to interpret the AI system’s output, and, in the case of affected persons, the knowledge necessary to understand how decisions taken with the assistance of AI will impact them. In the context of the application this Regulation, AI literacy should provide all relevant actors in the AI value chain with the insights required to ensure the appropriate compliance and its correct enforcement. Furthermore, the wide implementation of AI literacy measures and the introduction of appropriate follow-up actions could contribute to improving working conditions and ultimately sustain the consolidation, and innovation path of trustworthy AI in the Union. The European Artificial Intelligence Board should support the Commission, to promote AI literacy tools, public awareness and understanding of the benefits, risks, safeguards, rights and obligations in relation to the use of AI systems. In cooperation with the relevant stakeholders, the Commission and the Member States should facilitate the drawing up of voluntary codes of conduct to advance AI literacy among persons dealing with the development, operation and use of AI.

(10) In order to ensure a level playing field and an effective protection of rights and freedoms of individuals across the Union, the rules established by this Regulation should apply to providers of AI systems in a non-discriminatory manner, irrespective of whether they are established within the Union or in a third country, and to deployers of AI systems established within the Union.

(11) In light of their digital nature, certain AI systems should fall within the scope of this Regulation even when they are neither placed on the market, nor put into service, nor used in the Union. This is the case for example of an operator established in the Union that contracts certain services to an operator established outside the Union in relation to an activity to be performed by an AI system that would qualify as high-risk. In those circumstances, the AI system used by the operator outside the Union could process data lawfully collected in and transferred from the Union, and provide to the contracting operator in the Union the output of that AI system resulting from that processing, without that AI system being placed on the market, put into service or used in the Union. To prevent the circumvention of this Regulation and to ensure an effective protection of natural persons located in the Union, this Regulation should also apply to providers and deployers of AI systems that are established in a third country, to the extent the output produced by those systems is intended to be used in the Union. Nonetheless, to take into account existing arrangements and special needs for future cooperation with foreign partners with whom information and evidence is exchanged, this Regulation should not apply to public authorities of a third country and international organisations when acting in the framework of cooperation or international agreements concluded at national or European level for law enforcement and judicial cooperation with the Union or with its Member States, under the condition that this third country or international organisations provide adequate safeguards with respect to the protection of fundamental rights and freedoms of individuals. Where relevant, this may also cover activities of entities entrusted by the third countries to carry out specific tasks in support of such law enforcement and judicial cooperation. Such framework for cooperation or agreements have been established bilaterally between Member States and third countries or between the European Union, Europol and other EU agencies and third countries and international organisations. The authorities competent for supervision of the law enforcement and judicial authorities under the AI Act should assess whether these frameworks for cooperation or international agreements include adequate safeguards with respect to the protection of fundamental rights and freedoms of individuals. Recipient Member States authorities and Union institutions, offices and bodies making use of such outputs in the Union remain accountable to ensure their use complies with Union law. When those international agreements are revised or new ones are concluded in the future, the contracting parties should undertake the utmost effort to align those agreements with the requirements of this Regulation.

(12) This Regulation should also apply to Union institutions, offices, bodies and agencies when acting as a provider or deployer of an AI system.

(12a) If and insofar AI systems are placed on the market, put into service, or used with or without modification of such systems for military, defence or national security purposes, those should be excluded from the scope of this Regulation regardless of which type of entity is carrying out those activities, such as whether it is a public or private entity. As regards military and defence purposes, such exclusion is justified both by Article 4(2) TEU and by the specificities of the Member States’ and the common Union defence policy covered by Chapter 2 of Title V of the Treaty on European Union (TEU) that are subject to public international law, which is therefore the more appropriate legal framework for the regulation of AI systems in the context of the use of lethal force and other AI systems in the context of military and defence activities. As regards national security purposes, the exclusion is justified both by the fact that national security remains the sole responsibility of Member States in accordance with Article 4(2) TEU and by the specific nature and operational needs of national security activities and specific national rules applicable to those activities. Nonetheless, if an AI system developed, placed on the market, put into service or used for military, defence or national security purposes is used outside those temporarily or permanently for other purposes (for example, civilian or humanitarian purposes, law enforcement or public security purposes), such a system would fall within the scope of this Regulation. In that case, the entity using the system for other than military, defence or national security purposes should ensure compliance of the system with this Regulation, unless the system is already compliant with this Regulation. AI systems placed on the market or put into service for an excluded (i.e. military, defence or national security) and one or more non excluded purposes (e.g. civilian purposes, law enforcement, etc.), fall within the scope of this Regulation and providers of those systems should ensure compliance with this Regulation. In those cases, the fact that an AI system may fall within the scope of this Regulation should not affect the possibility of entities carrying out national security, defence and military activities, regardless of the type of entity carrying out those activities, to use AI systems for national security, military and defence purposes, the use of which is excluded from the scope of this Regulation. An AI system placed on the market for civilian or law enforcement purposes which is used with or without modification for military, defence or national security purposes should not fall within the scope of this Regulation, regardless of the type of entity carrying out those activities.

(12c)  This Regulation should support innovation, respect freedom of science, and should not undermine research and development activity. It is therefore necessary to exclude from its scope AI systems and models specifically developed and put into service for the sole purpose of scientific research and development. Moreover, it is necessary to ensure that the Regulation does not otherwise affect scientific research and development activity on AI systems or models prior to being placed on the market or put into service. As regards product oriented research, testing and development activity regarding AI systems or models, the provisions of this Regulation should also not apply prior to these systems and models being put into service or placed on the market. This is without prejudice to the obligation to comply with this Regulation when an AI system falling into the scope of this Regulation is placed on the market or put into service as a result of such research and development activity and to the application of provisions on regulatory sandboxes and testing in real world conditions. Furthermore, without prejudice to the foregoing regarding AI systems specifically developed and put into service for the sole purpose of scientific research and development, any other AI system that may be used for the conduct of any research and development activity should remain subject to the provisions of this Regulation. Under all circumstances, any research and development activity should be carried out in accordance with recognised ethical and professional standards for scientific research and should be conducted according to applicable Union law.

(14) In order to introduce a proportionate and effective set of binding rules for AI systems, a clearly defined risk-based approach should be followed. That approach should tailor the type and content of such rules to the intensity and scope of the risks that AI systems can generate. It is therefore necessary to prohibit certain unacceptable artificial intelligence practices, to lay down requirements for high-risk AI systems and obligations for the relevant operators, and to lay down transparency obligations for certain AI systems.

(14a) While the risk-based approach is the basis for a proportionate and effective set of binding rules, it is important to recall the 2019 Ethics Guidelines for Trustworthy AI developed by the independent High-Level Expert Group on AI (HLEG) appointed by the Commission. In those Guidelines the HLEG developed seven non-binding ethical principles for AI which should help ensure that AI is trustworthy and ethically sound. The seven principles include: human agency and oversight; technical robustness and safety; privacy and data governance; transparency; diversity, non-discrimination and fairness; societal and environmental well-being and accountability. Without prejudice to the legally binding requirements of this Regulation and any other applicable Union law, these Guidelines contribute to the design of a coherent, trustworthy and human-centric Artificial Intelligence, in line with the Charter and with the values on which the Union is founded. According to the Guidelines of HLEG, human agency and oversight means that AI systems are developed and used as a tool that serves people, respects human dignity and personal autonomy, and that is functioning in a way that can be appropriately controlled and overseen by humans. Technical robustness and safety means that AI systems are developed and used in a way that allows robustness in case of problems and resilience against attempts to alter the use or performance of the AI system so as to allow unlawful use by third parties, and minimise unintended harm. Privacy and data governance means that AI systems are developed and used in compliance with existing privacy and data protection rules, while processing data that meets high standards in terms of quality and integrity. Transparency means that AI systems are developed and used in a way that allows appropriate traceability and explainability, while making humans aware that they communicate or interact with an AI system, as well as duly informing deployers of the capabilities and limitations of that AI system and affected persons about their rights. Diversity, non-discrimination and fairness means that AI systems are developed and used in a way that includes diverse actors and promotes equal access, gender equality and cultural diversity, while avoiding discriminatory impacts and unfair biases that are prohibited by Union or national law. Social and environmental well-being means that AI systems are developed and used in a sustainable and environmentally friendly manner as well as in a way to benefit all human beings, while monitoring and assessing the long-term impacts on the individual, society and democracy. The application of these principles should be translated, when possible, in the design and use of AI models. They should in any case serve as a basis for the drafting of codes of conduct under this Regulation. All stakeholders, including industry, academia, civil society and standardisation organisations, are encouraged to take into account as appropriate the ethical principles for the development of voluntary best practices and standards.

(15) Aside from the many beneficial uses of artificial intelligence, that technology can also be misused and provide novel and powerful tools for manipulative, exploitative and social control practices. Such practices are particularly harmful and abusive and should be prohibited because they contradict Union values of respect for human dignity, freedom, equality, democracy and the rule of law and Union fundamental rights, including the right to non-discrimination, data protection and privacy and the rights of the child.

(16) AI-enabled manipulative techniques can be used to persuade persons to engage in unwanted behaviours, or to deceive them by nudging them into decisions in a way that subverts and impairs their autonomy, decision-making and free choices. The placing on the market, putting into service or use of certain AI systems with the objective to or the effect of materially distorting human behaviour, whereby significant harms, in particular having sufficiently important adverse impacts on physical, psychological health or financial interests are likely to occur, are particularly dangerous and should therefore be forbidden. Such AI systems deploy subliminal components such as audio, image, video stimuli that persons cannot perceive as those stimuli are beyond human perception or other manipulative or deceptive techniques that subvert or impair person’s autonomy, decision[1]making or free choices in ways that people are not consciously aware of, or even if aware they are still deceived or not able to control or resist. This could be for example, facilitated by machine-brain interfaces or virtual reality as they allow for a higher degree of control of what stimuli are presented to persons, insofar as they may be materially distorting their behaviour in a significantly harmful manner. In addition, AI systems may also otherwise exploit vulnerabilities of a person or a specific group of persons due to their age, disability within the meaning of Directive (EU) 2019/882, or a specific social or economic situation that is likely to make those persons more vulnerable to exploitation such as persons living in extreme poverty, ethnic or religious minorities. Such AI systems can be placed on the market, put into service or used with the objective to or the effect of materially distorting the behaviour of a person and in a manner that causes or is reasonably likely to cause significant harm to that or another person or groups of persons, including harms that may be accumulated over time and should therefore be prohibited. The intention to distort the behaviour may not be presumed if the distortion results from factors external to the AI system which are outside of the control of the provider or the deployer, meaning factors that may not be reasonably foreseen and mitigated by the provider or the deployer of the AI system. In any case, it is not necessary for the provider or the deployer to have the intention to cause significant harm, as long as such harm results from the manipulative or exploitative AI-enabled practices. The prohibitions for such AI practices are complementary to the provisions contained in Directive 2005/29/EC, notably unfair commercial practices leading to economic or financial harms to consumers are prohibited under all circumstances, irrespective of whether they are put in place through AI systems or otherwise. The prohibitions of manipulative and exploitative practices in this Regulation should not affect lawful practices in the context of medical treatment such as psychological treatment of a mental disease or physical rehabilitation, when those practices are carried out in accordance with the applicable legislation and medical standards, for example explicit consent of the individuals or their legal representatives. In addition, common and legitimate commercial practices, for example in the field of advertising, that are in compliance with the applicable law should not in themselves be regarded as constituting harmful manipulative AI practices.

(16a)   Biometric categorisation systems that are based on individuals’ biometric data, such as an individual person’s face or fingerprint, to deduce or infer an individuals’ political opinions, trade union membership, religious or philosophical beliefs, race, sex life or sexual orientation should be prohibited. This prohibition does not cover the lawful labelling, filtering or categorisation of biometric datasets acquired in line with Union or national law according to biometric data, such as the sorting of images according to hair colour or eye colour, which can for example be used in the area of law enforcement.

(17) AI systems providing social scoring of natural persons by public or private actors may lead to discriminatory outcomes and the exclusion of certain groups. They may violate the right to dignity and non-discrimination and the values of equality and justice. Such AI systems evaluate or classify natural persons or groups thereof based on multiple data points related to their social behaviour in multiple contexts or known, inferred or predicted personal or personality characteristics over certain periods of time. The social score obtained from such AI systems may lead to the detrimental or unfavourable treatment of natural persons or whole groups thereof in social contexts, which are unrelated to the context in which the data was originally generated or collected or to a detrimental treatment that is disproportionate or unjustified to the gravity of their social behaviour. AI systems entailing such unacceptable scoring practices leading to such detrimental or unfavourable outcomes should be therefore prohibited. This prohibition should not affect lawful evaluation practices of natural persons done for a specific purpose in compliance with national and Union law.

(18) The use of AI systems for ‘real-time’ remote biometric identification of natural persons in publicly accessible spaces for the purpose of law enforcement is particularly intrusive to the rights and freedoms of the concerned persons, to the extent that it may affect the private life of a large part of the population, evoke a feeling of constant surveillance and indirectly dissuade the exercise of the freedom of assembly and other fundamental rights. Technical inaccuracies of AI systems intended for the remote biometric identification of natural persons can lead to biased results and entail discriminatory effects. This is particularly relevant when it comes to age, ethnicity, race, sex or disabilities. In addition, the immediacy of the impact and the limited opportunities for further checks or corrections in relation to the use of such systems operating in ‘real-time’ carry heightened risks for the rights and freedoms of the persons that are concerned by law enforcement activities.

(19) The use of those systems for the purpose of law enforcement should therefore be prohibited, except in exhaustively listed and narrowly defined situations, where the use is strictly necessary to achieve a substantial public interest, the importance of which outweighs the risks. Those situations involve the search for certain victims of crime including missing people; certain threats to the life or physical safety of natural persons or of a terrorist attack; and the localisation or identification of perpetrators or suspects of the criminal offences referred to in Annex IIa if those criminal offences are punishable in the Member State concerned by a custodial sentence or a detention order for a maximum period of at least four years and as they are defined in the law of that Member State. Such threshold for the custodial sentence or detention order in accordance with national law contributes to ensure that the offence should be serious enough to potentially justify the use of ‘real-time’ remote biometric identification systems. Moreover, the list of criminal offences as referred in Annex IIa is based on the 32 criminal offences listed in the Council Framework Decision 2002/584/JHA9Council Framework Decision 2002/584/JHA of 13 June 2002 on the European arrest warrant and the surrender procedures between Member States (OJ L 190, 18.7.2002, p. 1)., taking into account that some are in practice likely to be more relevant than others, in that the recourse to ‘real-time’ remote biometric identification will foreseeably be necessary and proportionate to highly varying degrees for the practical pursuit of the localisation or identification of a perpetrator or suspect of the different criminal offences listed and having regard to the likely differences in the seriousness, probability and scale of the harm or possible negative consequences. An imminent threat to life or physical safety of natural persons could also result from a serious disruption of critical infrastructure, as defined in Article 2, point (a) of Directive 2008/114/EC, where the disruption or destruction of such critical infrastructure would result in an imminent threat to life or physical safety of a person, including through serious harm to the provision of basic supplies to the population or to the exercise of the core function of the State. In addition, this Regulation should preserve the ability for law enforcement, border control, immigration or asylum authorities to carry out identity checks in the presence of the person that is concerned in accordance with the conditions set out in Union and national law for such checks. In particular, law enforcement, border control, immigration or asylum authorities should be able to use information systems, in accordance with Union or national law, to identify a person who, during an identity check, either refuses to be identified or is unable to state or prove his or her identity, without being required by this Regulation to obtain prior authorisation. This could be, for example, a person involved in a crime, being unwilling, or unable due to an accident or a medical condition, to disclose their identity to law enforcement authorities.

(20) In order to ensure that those systems are used in a responsible and proportionate manner, it is also important to establish that, in each of those exhaustively listed and narrowly defined situations, certain elements should be taken into account, in particular as regards the nature of the situation giving rise to the request and the consequences of the use for the rights and freedoms of all persons concerned and the safeguards and conditions provided for with the use. In addition, the use of ‘real-time’ remote biometric identification systems in publicly accessible spaces for the purpose of law enforcement should only be deployed to confirm the specifically target individual’s identity and should be limited to what is strictly necessary concerning the period of time as well as geographic and personal scope, having regard in particular to the evidence or indications regarding the threats, the victims or perpetrator. The use of the ‘real-time’ remote biometric identification system in publicly accessible spaces should only be authorised if the law enforcement authority has completed a fundamental rights impact assessment and, unless provided otherwise in this Regulation, has registered the system in the database as set out in this Regulation. The reference database of persons should be appropriate for each use case in each of the situations mentioned above.

(21) Each use of a ‘real-time’ remote biometric identification system in publicly accessible spaces for the purpose of law enforcement should be subject to an express and specific authorisation by a judicial authority or by an independent administrative authority whose decision is binding of a Member State. Such authorisation should in principle be obtained prior to the use of the system with a view to identify a person or persons. Exceptions to this rule should be allowed in duly justified situations of urgency, that is, situations where the need to use the systems in question is such as to make it effectively and objectively impossible to obtain an authorisation before commencing the use. In such situations of urgency, the use should be restricted to the absolute minimum necessary and be subject to appropriate safeguards and conditions, as determined in national law and specified in the context of each individual urgent use case by the law enforcement authority itself. In addition, the law enforcement authority should in such situations request such authorisation whilst providing the reasons for not having been able to request it earlier, without undue delay and, at the latest within 24 hours. If such authorisation is rejected, the use of real-time biometric identification systems linked to that authorisation should be stopped with immediate effect and all the data related to such use should be discarded and deleted. Such data includes input data directly acquired by an AI system in the course of the use of such system as well as the results and outputs of the use linked to that authorisation. It should not include input legally acquired in accordance with another national or Union law. In any case, no decision producing an adverse legal effect on a person may be taken solely based on the output of the remote biometric identification system.

(21a)  In order to carry out their tasks in accordance with the requirements set out in this Regulation as well as in national rules, the relevant market surveillance authority and the national data protection authority should be notified of each use of the ‘real-time biometric identification system’. National market surveillance authorities and the national data protection authorities that have been notified should submit to the Commission an annual report on the use of ‘real-time biometric identification systems’.

(22) Furthermore, it is appropriate to provide, within the exhaustive framework set by this Regulation that such use in the territory of a Member State in accordance with this Regulation should only be possible where and in as far as the Member State in question has decided to expressly provide for the possibility to authorise such use in its detailed rules of national law. Consequently, Member States remain free under this Regulation not to provide for such a possibility at all or to only provide for such a possibility in respect of some of the objectives capable of justifying authorised use identified in this Regulation. These national rules should be notified to the Commission at the latest 30 days following their adoption.

(23) The use of AI systems for ‘real-time’ remote biometric identification of natural persons in publicly accessible spaces for the purpose of law enforcement necessarily involves the processing of biometric data. The rules of this Regulation that prohibit, subject to certain exceptions, such use, which are based on Article 16 TFEU, should apply as lex specialis in respect of the rules on the processing of biometric data contained in Article 10 of Directive (EU) 2016/680, thus regulating such use and the processing of biometric data involved in an exhaustive manner. Therefore, such use and processing should only be possible in as far as it is compatible with the framework set by this Regulation, without there being scope, outside that framework, for the competent authorities, where they act for purpose of law enforcement, to use such systems and process such data in connection thereto on the grounds listed in Article 10 of Directive (EU) 2016/680. In this context, this Regulation is not intended to provide the legal basis for the processing of personal data under Article 8 of Directive 2016/680. However, the use of ‘real-time’ remote biometric identification systems in publicly accessible spaces for purposes other than law enforcement, including by competent authorities, should not be covered by the specific framework regarding such use for the purpose of law enforcement set by this Regulation. Such use for purposes other than law enforcement should therefore not be subject to the requirement of an authorisation under this Regulation and the applicable detailed rules of national law that may give effect to it.

(24) Any processing of biometric data and other personal data involved in the use of AI systems for biometric identification, other than in connection to the use of ‘real-time’ remote biometric identification systems in publicly accessible spaces for the purpose of law enforcement as regulated by this Regulation, should continue to comply with all requirements resulting from Article 10 of Directive (EU) 2016/680. For purposes other than law enforcement, Article 9(1) of Regulation (EU) 2016/679 and Article 10(1) of Regulation (EU) 2018/1725 prohibit the processing of biometric data subject to limited exceptions as provided in those articles. In application of Article 9(1) of Regulation (EU) 2016/679, the use of remote biometric identification for purposes other than law enforcement has already been subject to prohibition decisions by national data protection authorities.

(25) In accordance with Article 6a of Protocol No 21 on the position of the United Kingdom and Ireland in respect of the area of freedom, security and justice, as annexed to the TEU and to the TFEU, Ireland is not bound by the rules laid down in Article 5(1), point (d), (2), (3), (3a), (4) and (5), Article 5(1)(ba) to the extent it applies to the use of biometric categorisation systems for activities in the field of police cooperation and judicial cooperation in criminal matters, Article 5(1)(da) to the extent it applies to the use of AI systems covered by that provision and Article 29(6a) of this Regulation adopted on the basis of Article 16 of the TFEU which relate to the processing of personal data by the Member States when carrying out activities falling within the scope of Chapter 4 or Chapter 5 of Title V of Part Three of the TFEU, where Ireland is not bound by the rules governing the forms of judicial cooperation in criminal matters or police cooperation which require compliance with the provisions laid down on the basis of Article 16 of the TFEU.

(26) In accordance with Articles 2 and 2a of Protocol No 22 on the position of Denmark, annexed to the TEU and TFEU, Denmark is not bound by rules laid down in Article 5(1), point (d), (2), (3), (3a), (4) and (5), Article 5(1)(ba) to the extent it applies to the use of biometric categorisation systems for activities in the field of police cooperation and judicial cooperation in criminal matters, Article 5(1)(da) to the extent it applies to the use of AI systems covered by that provision and Article 29(6a) of this Regulation adopted on the basis of Article 16 of the TFEU, or subject to their application, which relate to the processing of personal data by the Member States when carrying out activities falling within the scope of Chapter 4 or Chapter 5 of Title V of Part Three of the TFEU.

(26a) In line with the presumption of innocence, natural persons in the EU should always be judged on their actual behaviour. Natural persons should never be judged on AI-predicted behaviour based solely on their profiling, personality traits or characteristics, such as nationality, place of birth, place of residence, number of children, debt, their type of car, without a reasonable suspicion of that person being involved in a criminal activity based on objective verifiable facts and without human assessment thereof. Therefore, risk assessments of natural persons in order to assess the risk of them offending or for predicting the occurrence of an actual or potential criminal offence solely based on the profiling of a natural person or on assessing their personality traits and characteristics should be prohibited. In any case, this prohibition does not refer to nor touch upon risk analytics that are not based on the profiling of individuals or on the personality traits and characteristics of individuals, such as AI systems using risk analytics to assess the risk of financial fraud by undertakings based on suspicious transactions or risk analytic tools to predict the likelihood of localisation of narcotics or illicit goods by customs authorities, for example based on known trafficking routes.

(26b)  The placing on the market, putting into service for this specific purpose, or use of AI systems that create or expand facial recognition databases through the untargeted scraping of facial images from the internet or CCTV footage should be prohibited, as this practice adds to the feeling of mass surveillance and can lead to gross violations of fundamental rights, including the right to privacy.

(26c)  There are serious concerns about the scientific basis of AI systems aiming to identify or infer emotions, particularly as expression of emotions vary considerably across cultures and situations, and even within a single individual. Among the key shortcomings of such systems are the limited reliability, the lack of specificity and the limited generalizability. Therefore, AI systems identifying or inferring emotions or intentions of natural persons on the basis of their biometric data may lead to discriminatory outcomes and can be intrusive to the rights and freedoms of the concerned persons. Considering the imbalance of power in the context of work or education, combined with the intrusive nature of these systems, such systems could lead to detrimental or unfavourable treatment of certain natural persons or whole groups thereof. Therefore, the placing on the market, putting into service, or useof AI systems intended to be used to detect the emotional state of individuals in situationsrelated to the workplace and education should be prohibited. This prohibition should not cover AI systems placed on the market strictly for medical or safety reasons, such as systems intended for therapeutical use.

(26d)  Practices that are prohibited by Union legislation, including data protection law, non-discrimination law, consumer protection law, and competition law, should not be affected by this Regulation.

(27) High-risk AI systems should only be placed on the Union market, put into service or used if they comply with certain mandatory requirements. Those requirements should ensure that high-risk AI systems available in the Union or whose output is otherwise used in the Union do not pose unacceptable risks to important Union public interests as recognised and protected by Union law. Following the New Legislative Framework approach, as clarified in Commission notice the ‘Blue Guide’ on the implementation of EU product rules 2022 (C/2022/3637) the general rule is that several pieces of the EU legislation, such as Regulation (EU) 2017/745 on Medical Devices and Regulation (EU) 2017/746 on In Vitro Diagnostic Devices or Directive 2006/42/EC on Machinery, may have to be taken into consideration for one product, since the making available or putting into service can only take place when the product complies with all applicable Union harmonisation legislation. To ensure consistency and avoid unnecessary administrative burden or costs, providers of a product that contains one or more high-risk artificial intelligence system, to which the requirements of this Regulation as well as requirements of the Union harmonisation legislation listed in Annex II, Section A apply, should have a flexibility on operational decisions on how to ensure compliance of a product that contains one or more artificial intelligence systems with all applicable requirements of the Union harmonised legislation in a best way. AI systems identified as high-risk should be limited to those that have a significant harmful impact on the health, safety and fundamental rights of persons in the Union and such limitation minimises any potential restriction to international trade, if any.

(28) AI systems could have an adverse impact to health and safety of persons, in particular when such systems operate as safety components of products. Consistently with the objectives of Union harmonisation legislation to facilitate the free movement of products in the internal market and to ensure that only safe and otherwise compliant products find their way into the market, it is important that the safety risks that may be generated by a product as a whole due to its digital components, including AI systems, are duly prevented and mitigated. For instance, increasingly autonomous robots, whether in the context of manufacturing or personal assistance and care should be able to safely operate and performs their functions in complex environments. Similarly, in the health sector where the stakes for life and health are particularly high, increasingly sophisticated diagnostics systems and systems supporting human decisions should be reliable and accurate.

(28a)  The extent of the adverse impact caused by the AI system on the fundamental rights protected by the Charter is of particular relevance when classifying an AI system as high[1]risk. Those rights include the right to human dignity, respect for private and family life, protection of personal data, freedom of expression and information, freedom of assembly and of association, and non-discrimination, right to education consumer protection, workers’ rights, rights of persons with disabilities, gender equality, intellectual property rights, right to an effective remedy and to a fair trial, right of defence and the presumption of innocence, right to good administration. In addition to those rights, it is important to highlight that children have specific rights as enshrined in Article 24 of the EU Charter and in the United Nations Convention on the Rights of the Child (further elaborated in the UNCRC General Comment No. 25 as regards the digital environment), both of which require consideration of the children’s vulnerabilities and provision of such protection and care as necessary for their well-being. The fundamental right to a high level of environmental protection enshrined in the Charter and implemented in Union policies should also be considered when assessing the severity of the harm that an AI system can cause, including in relation to the health and safety of persons.

(29) As regards high-risk AI systems that are safety components of products or systems, or which are themselves products or systems falling within the scope of Regulation (EC) No 300/2008 of the European Parliament and of the Council10Regulation (EC) No 300/2008 of the European Parliament and of the Council of 11 March 2008 on common rules in the field of civil aviation security and repealing Regulation (EC) No 2320/2002 (OJ L 97, 9.4.2008, p. 72)., Regulation (EU) No 167/2013 of the European Parliament and of the Council11Regulation (EU) No 167/2013 of the European Parliament and of the Council of 5 February 2013 on the approval and market surveillance of agricultural and forestry vehicles (OJ L 60, 2.3.2013, p. 1)., Regulation (EU) No 168/2013 of the European Parliament and of the Council12Regulation (EU) No 168/2013 of the European Parliament and of the Council of 15 January 2013 on the approval and market surveillance of two- or three-wheel vehicles and quadricycles (OJ L 60, 2.3.2013, p. 52)., Directive 2014/90/EU of the European Parliament and of the Council13Directive 2014/90/EU of the European Parliament and of the Council of 23 July 2014 on marine equipment and repealing Council Directive 96/98/EC (OJ L 257, 28.8.2014, p. 146)., Directive (EU) 2016/797 of the European Parliament and of the Council14Directive (EU) 2016/797 of the European Parliament and of the Council of 11 May 2016 on the interoperability of the rail system within the European Union (OJ L 138, 26.5.2016, p. 44)., Regulation (EU) 2018/858 of the European Parliament and of the Council15Regulation (EU) 2018/858 of the European Parliament and of the Council of 30 May 2018 on the approval and market surveillance of motor vehicles and their trailers, and of systems, components and separate technical units intended for such vehicles, amending Regulations (EC) No 715/2007 and (EC) No 595/2009 and repealing Directive 2007/46/EC (OJ L 151, 14.6.2018, p. 1)., Regulation (EU) 2018/1139 of the European Parliament and of the Council16Regulation (EU) 2018/1139 of the European Parliament and of the Council of 4 July 2018 on common rules in the field of civil aviation and establishing a European Union Aviation Safety Agency, and amending Regulations (EC) No 2111/2005, (EC) No 1008/2008, (EU) No 996/2010, (EU) No 376/2014 and Directives 2014/30/EU and 2014/53/EU of the European Parliament and of the Council, and repealing Regulations (EC) No 552/2004 and (EC) No 216/2008 of the European Parliament and of the Council and Council Regulation (EEC) No 3922/91 (OJ L 212, 22.8.2018, p. 1)., and Regulation (EU) 2019/2144 of the European Parliament and of the Council17Regulation (EU) 2019/2144 of the European Parliament and of the Council of 27 November 2019 on type-approval requirements for motor vehicles and their trailers, and systems, components and separate technical units intended for such vehicles, as regards their general safety and the protection of vehicle occupants and vulnerable road users, amending Regulation (EU) 2018/858 of the European Parliament and of the Council and repealing Regulations (EC) No 78/2009, (EC) No 79/2009 and (EC) No 661/2009 of the European Parliament and of the Council and Commission Regulations (EC) No 631/2009, (EU) No 406/2010, (EU) No 672/2010, (EU) No 1003/2010, (EU) No 1005/2010, (EU) No 1008/2010, (EU) No 1009/2010, (EU) No 19/2011, (EU) No 109/2011, (EU) No 458/2011, (EU) No 65/2012, (EU) No 130/2012, (EU) No 347/2012, (EU) No 351/2012, (EU) No 1230/2012 and (EU) 2015/166 (OJ L 325, 16.12.2019, p. 1)., it is appropriate to amend those acts to ensure that the Commission takes into account, on the basis of the technical and regulatory specificities of each sector, and without interfering with existing governance, conformity assessment and enforcement mechanisms and authorities established therein, the mandatory requirements for high-risk AI systems laid down in this Regulation when adopting any relevant future delegated or implementing acts on the basis of those acts.

(30) As regards AI systems that are safety components of products, or which are themselves products, falling within the scope of certain Union harmonisation legislation listed in Annex II, it is appropriate to classify them as high-risk under this Regulation if the product in question undergoes the conformity assessment procedure with a third-party conformity assessment body pursuant to that relevant Union harmonisation legislation. In particular, such products are machinery, toys, lifts, equipment and protective systems intended for use in potentially explosive atmospheres, radio equipment, pressure equipment, recreational craft equipment, cableway installations, appliances burning gaseous fuels, medical devices, and in vitro diagnostic medical devices.

(31) The classification of an AI system as high-risk pursuant to this Regulation should not necessarily mean that the product whose safety component is the AI system, or the AI system itself as a product, is considered ‘high-risk’ under the criteria established in the relevant Union harmonisation legislation that applies to the product. This is notably the case for Regulation (EU) 2017/745 of the European Parliament and of the Council18Regulation (EU) 2017/745 of the European Parliament and of the Council of 5 April 2017 on medical devices, amending Directive 2001/83/EC, Regulation (EC) No 178/2002 and Regulation (EC) No 1223/2009 and repealing Council Directives 90/385/EEC and 93/42/EEC (OJ L 117, 5.5.2017, p. 1). and Regulation (EU) 2017/746 of the European Parliament and of the Council19Regulation (EU) 2017/746 of the European Parliament and of the Council of 5 April 2017 on in vitro diagnostic medical devices and repealing Directive 98/79/EC and Commission Decision 2010/227/EU (OJ L 117, 5.5.2017, p. 176)., where a third- party conformity assessment is provided for medium-risk and high-risk products.

(32) As regards stand-alone AI systems, meaning high-risk AI systems other than those that are safety components of products, or which are themselves products, it is appropriate to classify them as high-risk if, in the light of their intended purpose, they pose a high risk of harm to the health and safety or the fundamental rights of persons, taking into account both the severity of the possible harm and its probability of occurrence and they are used in a number of specifically pre-defined areas specified in the Regulation. The identification of those systems is based on the same methodology and criteria envisaged also for any future amendments of the list of high-risk AI systems that the Commission should be empowered to adopt, via delegated acts, to take into account the rapid pace of technological development, as well as the potential changes in the use of AI systems.

(32a) It is also important to clarify that there may be specific cases in which AI systems referred to pre-defined areas specified in this Regulation do not lead to a significant risk of harm to the legal interests protected under those areas, because they do not materially influence the decision-making or do not harm those interests substantially. For the purpose of this Regulation an AI system not materially influencing the outcome of decision-making should be understood as an AI system that does not impact the substance, and thereby the outcome, of decision-making, whether human or automated. This could be the case if one or more of the following conditions are fulfilled. The first criterion should be that the AI system is intended to perform a narrow procedural task, such as an AI system that transforms unstructured data into structured data, an AI system that classifies incoming documents into categories or an AI system that is used to detect duplicates among a large number of applications. These tasks are of such narrow and limited nature that they pose only limited risks which are not increased through the use in a context listed in Annex III. The second criterion should be that the task performed by the AI system is intended to improve the result of a previously completed human activity that may be relevant for the purpose of the use case listed in Annex III. Considering these characteristics, the AI system only provides an additional layer to a human activity with consequently lowered risk. For example, this criterion would apply to AI systems that are intended to improve the language used in previously drafted documents, for instance in relation to professional tone, academic style of language or by aligning text to a certain brand messaging. The third criterion should be that the AI system is intended to detect decision-making patterns or deviations from prior decision-making patterns. The risk would be lowered because the use of the AI system follows a previously completed human assessment which it is not meant to replace or influence, without proper human review. Such AI systems include for instance those that, given a certain grading pattern of a teacher, can be used to check ex post whether the teacher may have deviated from the grading pattern so as to flag potential inconsistencies or anomalies. The fourth criterion should be that the AI system is intended to perform a task that is only preparatory to an assessment relevant for the purpose of the use case listed in Annex III, thus making the possible impact of the output of the system very low in terms of representing a risk for the assessment to follow. For example, this criterion covers smart solutions for file handling, which include various functions from indexing, searching, text and speech processing or linking data to other data sources, or AI systems used for translation of initial documents. In any case, AI systems referred to in Annex III should be considered to pose significant risks of harm to the health, safety or fundamental rights of natural persons if the AI system implies profiling within the meaning of Article 4(4) of Regulation (EU) 2016/679 and Article 3(4) of Directive (EU) 2016/680 and Article 3(5) of Regulation 2018/1725. To ensure traceability and transparency, a provider who considers that an AI system referred to in Annex III is not high-risk on the basis of the aforementioned criteria should draw up documentation of the assessment before that system is placed on the market or put into service and should provide this documentation to national competent authorities upon request. Such provider should be obliged to register the system in the EU database established under this Regulation. With a view to provide further guidance for the practical implementation of the criteria under which AI systems referred to in Annex III are exceptionally not high-risk, the Commission should, after consulting the AI Board, provide guidelines specifying this practical implementation completed by a comprehensive list of practical examples of high risk and non-high risk use cases of AI systems.

(33a) As biometric data constitutes a special category of sensitive personal data, it is appropriate to classify as high-risk several critical use-cases of biometric systems, insofar as their use is permitted under relevant Union and national law. Technical inaccuracies of AI systems intended for the remote biometric identification of natural persons can lead to biased results and entail discriminatory effects. This is particularly relevant when it comes to age, ethnicity, race, sex or disabilities. Therefore, remote biometric identification systems should be classified as high-risk in view of the risks that they pose. This excludes AI systems intended to be used for biometric verification, which includes authentication, whose sole purpose is to confirm that a specific natural person is the person he or she claims to be and to confirm the identity of a natural person for the sole purpose of having access to a service, unlocking a device or having secure access to premises. In addition, AI systems intended to be used for biometric categorisation according to sensitive attributes or characteristics protected under Article 9(1) of Regulation (EU) 2016/679 based on biometric data, in so far as these are not prohibited under this Regulation, and emotion recognition systems that are not prohibited under this Regulation, should be classified as high-risk. Biometric systems which are intended to be used solely for the purpose of enabling cybersecurity and personal data protection measures should not be considered as high-risk systems.

(34) As regards the management and operation of critical infrastructure, it is appropriate to classify as high-risk the AI systems intended to be used as safety components in the management and operation of critical digital infrastructure as listed in Annex I point 8 of the Directive on the resilience of critical entities, road traffic and the supply of water, gas, heating and electricity, since their failure or malfunctioning may put at risk the life and health of persons at large scale and lead to appreciable disruptions in the ordinary conduct of social and economic activities. Safety components of critical infrastructure, including critical digital infrastructure, are systems used to directly protect the physical integrity of critical infrastructure or health and safety of persons and property but which are not necessary in order for the system to function. Failure or malfunctioning of such components might directly lead to risks to the physical integrity of critical infrastructure and thus to risks to health and safety of persons and property. Components intended to be used solely for cybersecurity purposes should not qualify as safety components. Examples of safety components of such critical infrastructure may include systems for monitoring water pressure or fire alarm controlling systems in cloud computing centres.

(35) Deployment of AI systems in education is important to promote high-quality digital education and training and to allow all learners and teachers to acquire and share the necessary digital skills and competences, including media literacy, and critical thinking, to take an active part in the economy, society, and in democratic processes. However, AI systems used in education or vocational training, notably for determining access or admission, for assigning persons to educational and vocational training institutions or programmes at all levels, for evaluating learning outcomes of persons, for assessing the appropriate level of education for an individual and materially influencing the level of education and training that individuals will receive or be able to access or for monitoring and detecting prohibited behaviour of students during tests should be classified as high-risk AI systems, since they may determine the educational and professional course of a person’s life and therefore affect their ability to secure their livelihood. When improperly designed and used, such systems can be particularly intrusive and may violate the right to education and training as well as the right not to be discriminated against and perpetuate historical patterns of discrimination, for example against women, certain age groups, persons with disabilities, or persons of certain racial or ethnic origins or sexual orientation.

(36) AI systems used in employment, workers management and access to self-employment, notably for the recruitment and selection of persons, for making decisions affecting terms of the work related relationship promotion and termination of work-related contractual relationships for allocating tasks based on individual behaviour, personal traits or characteristics and for monitoring or evaluation of persons in work-related contractual relationships, should also be classified as high-risk, since those systems may appreciably impact future career prospects, livelihoods of these persons and workers’ rights. Relevant work-related contractual relationships should meaningfully involve employees and persons providing services through platforms as referred to in the Commission Work Programme 2021. Throughout the recruitment process and in the evaluation, promotion, or retention of persons in work-related contractual relationships, such systems may perpetuate historical patterns of discrimination, for example against women, certain age groups, persons with disabilities, or persons of certain racial or ethnic origins or sexual orientation. AI systems used to monitor the performance and behaviour of these persons may also undermine their fundamental rights to data protection and privacy.

(37) Another area in which the use of AI systems deserves special consideration is the access to and enjoyment of certain essential private and public services and benefits necessary for people to fully participate in society or to improve one’s standard of living. In particular, natural persons applying for or receiving essential public assistance benefits and services from public authorities namely healthcare services, social security benefits, social services providing protection in cases such as maternity, illness, industrial accidents, dependency or old age and loss of employment and social and housing assistance, are typically dependent on those benefits and services and in a vulnerable position in relation to the responsible authorities. If AI systems are used for determining whether such benefits and services should be granted, denied, reduced, revoked or reclaimed by authorities, including whether beneficiaries are legitimately entitled to such benefits or services, those systems may have a significant impact on persons’ livelihood and may infringe their fundamental rights, such as the right to social protection, non-discrimination, human dignity or an effective remedy and should therefore be classified as high-risk. Nonetheless, this Regulation should not hamper the development and use of innovative approaches in the public administration, which would stand to benefit from a wider use of compliant and safe AI systems, provided that those systems do not entail a high risk to legal and natural persons. In addition, AI systems used to evaluate the credit score or creditworthiness of natural persons should be classified as high-risk AI systems, since they determine those persons’ access to financial resources or essential services such as housing, electricity, and telecommunication services. AI systems used for this purpose may lead to discrimination of persons or groups and perpetuate historical patterns of discrimination, for example based on racial or ethnic origins, gender, disabilities, age, sexual orientation, or create new forms of discriminatory impacts. However, AI systems provided for by Union law for the purpose of detecting fraud in the offering of financial services and for prudential purposes to calculate credit institutions’ and insurances undertakings’ capital requirements should not be considered as high-risk under this Regulation. Moreover, AI systems intended to be used for risk assessment and pricing in relation to natural persons for health and life insurance can also have a significant impact on persons’ livelihood and if not duly designed, developed and used, can infringe their fundamental rights and can lead to serious consequences for people’s life and health, including financial exclusion and discrimination. Finally, AI systems used to evaluate and classify emergency calls by natural persons or to dispatch or establish priority in the dispatching of emergency first response services, including by police, firefighters and medical aid, as well as of emergency healthcare patient triage systems, should also be classified as high-risk since they make decisions in very critical situations for the life and health of persons and their property.

(38) Given their role and responsibility, actions by law enforcement authorities involving certain uses of AI systems are characterised by a significant degree of power imbalance and may lead to surveillance, arrest or deprivation of a natural person’s liberty as well as other adverse impacts on fundamental rights guaranteed in the Charter. In particular, if the AI system is not trained with high quality data, does not meet adequate requirements in terms of its performance, its accuracy or robustness, or is not properly designed and tested before being put on the market or otherwise put into service, it may single out people in a discriminatory or otherwise incorrect or unjust manner. Furthermore, the exercise of important procedural fundamental rights, such as the right to an effective remedy and to a fair trial as well as the right of defence and the presumption of innocence, could be hampered, in particular, where such AI systems are not sufficiently transparent, explainable and documented. It is therefore appropriate to classify as high-risk, insofar as their use is permitted under relevant Union and national law, a number of AI systems intended to be used in the law enforcement context where accuracy, reliability and transparency is particularly important to avoid adverse impacts, retain public trust and ensure accountability and effective redress. In view of the nature of the activities in question and the risks relating thereto, those high-risk AI systems should include in particular AI systems intended to be used by or on behalf of law enforcement authorities or by Union agencies, offices or bodies in support of law enforcement authorities for assessing the risk of a natural person to become a victim of criminal offences, as polygraphs and similar tools , for the evaluation of the reliability of evidence in in the course of investigation or prosecution of criminal offences, and, insofar not prohibited under this regulation, for assessing the risk of a natural person of offending or reoffending not solely based on profiling of natural persons nor based on assessing personality traits and characteristics or past criminal behaviour of natural persons or groups, for profiling in the course of detection, investigation or prosecution of criminal offences, . AI systems specifically intended to be used for administrative proceedings by tax and customs authorities as well as by financial intelligence units carrying out administrative tasks analysing information pursuant to Union anti-money laundering legislation should not be classified as high-risk AI systems used by law enforcement authorities for the purposes of prevention, detection, investigation and prosecution of criminal offences. The use of AI tools by law enforcement and authorities should not become a factor of inequality, or exclusion. The impact of the use of AI tools on the defence rights of suspects should not be ignored, notably the difficulty in obtaining meaningful information on the functioning of these systems and the consequent difficulty in challenging their results in court, in particular by individuals under investigation.

(39) AI systems used in migration, asylum and border control management affect people who are often in particularly vulnerable position and who are dependent on the outcome of the actions of the competent public authorities. The accuracy, non-discriminatory nature and transparency of the AI systems used in those contexts are therefore particularly important to guarantee the respect of the fundamental rights of the affected persons, notably their rights to free movement, non-discrimination, protection of private life and personal data, international protection and good administration. It is therefore appropriate to classify as high-risk, insofar as their use is permitted under relevant Union and national law AI systems intended to be used by or on behalf of competent public authorities or by Union agencies, offices or bodies charged with tasks in the fields of migration, asylum and border control management as polygraphs and similar tools, for assessing certain risks posed by natural persons entering the territory of a Member State or applying for visa or asylum, for assisting competent public authorities for the examination, including related assessment of the reliability of evidence, of applications for asylum, visa and residence permits and associated complaints with regard to the objective to establish the eligibility of the natural persons applying for a status, for the purpose of detecting, recognising or identifying natural persons in the context of migration, asylum and border control management with the exception of travel documents. AI systems in the area of migration, asylum and border control management covered by this Regulation should comply with the relevant procedural requirements set by the Directive 2013/32/EU of the European Parliament and of the Council20Directive 2013/32/EU of the European Parliament and of the Council of 26 June 2013 on common procedures for granting and withdrawing international protection (OJ L 180, 29.6.2013, p. 60)., the Regulation (EC) No 810/2009 of the European Parliament and of the Council21Regulation (EC) No 810/2009 of the European Parliament and of the Council of 13 July 2009 establishing a Community Code on Visas (Visa Code) (OJ L 243, 15.9.2009, p. 1). and other relevant legislation. The use of AI systems in migration, asylum and border control management should in no circumstances be used by Member States or Union institutions, agencies or bodies as a means to circumvent their international obligations under the Convention of 28 July 1951 relating to the Status of Refugees as amended by the Protocol of 31 January 1967, nor should they be used to in any way infringe on the principle of non-refoulement, or deny safe and effective legal avenues into the territory of the Union, including the right to international protection.

(40) Certain AI systems intended for the administration of justice and democratic processes should be classified as high-risk, considering their potentially significant impact on democracy, rule of law, individual freedoms as well as the right to an effective remedy and to a fair trial. In particular, to address the risks of potential biases, errors and opacity, it is appropriate to qualify as high-risk AI systems intended to be used by a judicial authority or on its behalf to assist judicial authorities in researching and interpreting facts and the law and in applying the law to a concrete set of facts. AI systems intended to be used by alternative dispute resolution bodies for those purposes should also be considered high-risk when the outcomes of the alternative dispute resolution proceedings produce legal effects for the parties. The use of artificial intelligence tools can support the decision-making power of judges or judicial independence, but should not replace it, as the final decision-making must remain a human-driven activity and decision. Such qualification should not extend, however, to AI systems intended for purely ancillary administrative activities that do not affect the actual administration of justice in individual cases, such as anonymisation or pseudonymisation of judicial decisions, documents or data, communication between personnel, administrative tasks.

(40a)      Without prejudice to the rules provided for in [Regulation xxx on the transparency and targeting of political advertising], and in order to address the risks of undue external interference to the right to vote enshrined in Article 39 of the Charter, and of adverse effects on democracy, and the rule of law, AI systems intended to be used to influence the outcome of an election or referendum or the voting behaviour of natural persons in the exercise of their vote in elections or referenda should be classified as high-risk AI systems with the exception of AI systems whose output natural persons are not directly exposed to, such as tools used to organise, optimise and structure political campaigns from an administrative and logistical point of view.

(41) The fact that an AI system is classified as a high-risk AI system under this Regulation should not be interpreted as indicating that the use of the system is lawful under other acts of Union law or under national law compatible with Union law, such as on the protection of personal data, on the use of polygraphs and similar tools or other systems to detect the emotional state of natural persons. Any such use should continue to occur solely in accordance with the applicable requirements resulting from the Charter and from the applicable acts of secondary Union law and national law. This Regulation should not be understood as providing for the legal ground for processing of personal data, including special categories of personal data, where relevant, unless it is specifically provided for otherwise in this Regulation.

To mitigate the risks from high-risk AI systems placed on the market or put into service and to ensure a high level of trustworthiness, certain mandatory requirements should apply to high-risk AI systems, taking into account the intended purpose and the context of use of the AI system and according to the risk management system to be established by the provider. The measures adopted by the providers to comply with the mandatory requirements of this Regulation should take into account the generally acknowledge state of the art on artificial intelligence, be proportionate and effective to meet the objectives of this Regulation. Following the New Legislative Framework approach, as clarified in Commission notice the ‘Blue Guide’ on the implementation of EU product rules 2022 (C/2022/3637), the general rule is that several pieces of the EU legislation may have to be taken into consideration for one product, since the making available or putting into service can only take place when the product complies with all applicable Union harmonisation legislation. Hazards of AI systems covered by the requirements of this Regulation concern different aspects than the existing Union harmonisation acts and therefore the requirements of this Regulation would complement the existing body of the Union harmonisation acts. For example, machinery or medical devices products incorporating an AI system might present risks not addressed by the essential health and safety requirements set out in the relevant Union harmonised legislation, as this sectoral legislation does not deal with risks specific to AI systems. This calls for a simultaneous and complementary application of the various legislative acts. To ensure consistency and avoid unnecessary administrative burden or costs, providers of a product that contains one or more high-risk artificial intelligence system, to which the requirements of this Regulation as well as requirements of the Union harmonisation legislation listed in Annex II, Section A apply, should have a flexibility on operational decisions on how to ensure compliance of a product that contains one or more artificial intelligence systems with all applicable requirements of the Union harmonised legislation in a best way. This flexibility could mean, for example a decision by the provider to integrate a part of the necessary testing and reporting processes, information and documentation required under this Regulation into already existing documentation and procedures required under the existing Union harmonisation legislation listed in Annex II, Section A. This however should not in any way undermine the obligation of the provider to comply with all the applicable requirements.

(42a)      The risk management system should consist of a continuous, iterative process that is planned and run throughout the entire lifecycle of a high-risk AI system. This process should be aimed at identifying and mitigating the relevant risks of artificial intelligence systems on health, safety and fundamental rights. The risk management system should be regularly reviewed and updated to ensure its continuing effectiveness, as well as justification and documentation of any significant decisions and actions taken subject to this Regulation. This process should ensure that the provider identifies risks or adverse impacts and implements mitigation measures for the known and reasonably foreseeable risks of artificial intelligence systems to the health, safety and fundamental rights in light of its intended purpose and reasonably foreseeable misuse, including the possible risks arising from the interaction between the AI system and the environment within which it operates. The risk management system should adopt the most appropriate risk management measures in the light of the state of the art in AI. When identifying the most appropriate risk management measures, the provider should document and explain the choices made and, when relevant, involve experts and external stakeholders. In identifying reasonably foreseeable misuse of high-risk AI systems the provider should cover uses of the AI systems which, while not directly covered by the intended purpose and provided for in the instruction for use may nevertheless be reasonably expected to result from readily predictable human behaviour in the context of the specific characteristics and use of the particular AI system. Any known or foreseeable circumstances, related to the use of the high-risk AI system in accordance with its intended purpose or under conditions of reasonably foreseeable misuse, which may lead to risks to the health and safety or fundamental rights should be included in the instructions for use provided by the provider. This is to ensure that the deployer is aware and takes them into account when using the high-risk AI system. Identifying and implementing risk mitigation measures for foreseeable misuse under this Regulation should not require specific additional training measures for the high-risk AI system by the provider to address them. The providers however are encouraged to consider such additional training measures to mitigate reasonable foreseeable misuses as necessary and appropriate.

(43) Requirements should apply to high-risk AI systems as regards risk management, the quality and relevance of data sets used, technical documentation and record-keeping, transparency and the provision of information to deployers, human oversight, and robustness, accuracy and cybersecurity. Those requirements are necessary to effectively mitigate the risks for health, safety and fundamental rights, and no other less trade restrictive measures are reasonably available, thus avoiding unjustified restrictions to trade.

(44) High quality data and access to high quality data plays a vital role in providing structure and in ensuring the performance of many AI systems, especially when techniques involving the training of models are used, with a view to ensure that the high-risk AI system performs as intended and safely and it does not become a source of discrimination prohibited by Union law. High quality datasets for training, validation and testing require the implementation of appropriate data governance and management practices. Datasets for training, validation and testing, including the labels, should be relevant, sufficiently representative, and to the best extent possible free of errors and complete in view of the intended purpose of the system. In order to facilitate compliance with EU data protection law, such as Regulation (EU) 2016/679, data governance and management practices should include, in the case of personal data, transparency about the original purpose of the data collection, The datasets should also have the appropriate statistical properties, including as regards the persons or groups of persons in relation to whom the high-risk AI system is intended to be used, with specific attention to the mitigation of possible biases in the datasets, that are likely to affect the health and safety of persons, negatively impact fundamental rights or lead to discrimination prohibited under Union law, especially where data outputs influence inputs for future operations (‘feedback loops’) . Biases can for example be inherent in underlying datasets, especially when historical data is being used, or generated when the systems are implemented in real world settings. Results provided by AI systems could be influenced by such inherent biases that are inclined to gradually increase and thereby perpetuate and amplify existing discrimination, in particular for persons belonging to certain vulnerable groups including racial or ethnic groups. The requirement for the datasets to be to the best extent possible complete and free of errors should not affect the use of privacy-preserving techniques in the context of the development and testing of AI systems. In particular, datasets should take into account, to the extent required by their intended purpose, the features, characteristics or elements that are particular to the specific geographical, contextual, behavioural or functional setting which the AI system is intended to be used. The requirements related to data governance can be complied with by having recourse to third parties that offer certified compliance services including verification of data governance, data set integrity, and data training, validation and testing practices, as far as compliance with the data requirements of this Regulation are ensured.

(45) For the development and assessment of high-risk AI systems, certain actors, such as providers, notified bodies and other relevant entities, such as digital innovation hubs, testing experimentation facilities and researchers, should be able to access and use high quality datasets within their respective fields of activities which are related to this Regulation. European common data spaces established by the Commission and the facilitation of data sharing between businesses and with government in the public interest will be instrumental to provide trustful, accountable and non-discriminatory access to high quality data for the training, validation and testing of AI systems. For example, in health, the European health data space will facilitate non-discriminatory access to health data and the training of artificial intelligence algorithms on those datasets, in a privacy-preserving, secure, timely, transparent and trustworthy manner, and with an appropriate institutional governance. Relevant competent authorities, including sectoral ones, providing or supporting the access to data may also support the provision of high-quality data for the training, validation and testing of AI systems.

(45a)  The right to privacy and to protection of personal data must be guaranteed throughout the entire lifecycle of the AI system. In this regard, the principles of data minimisation and data protection by design and by default, as set out in Union data protection law, are applicable when personal data are processed. Measures taken by providers to ensure compliance with those principles may include not only anonymisation and encryption, but also the use of technology that permits algorithms to be brought to the data and allows training of AI systems without the transmission between parties or copying of the raw or structured data themselves, without prejudice to the requirements on data governance provided for in this Regulation.

(44c)   In order to protect the right of others from the discrimination that might result from the bias in AI systems, the providers should, exceptionally, to the extent that it is strictly necessary for the purposes of ensuring bias detection and correction in relation to the high[1]risk AI systems, subject to appropriate safeguards for the fundamental rights and freedoms of natural persons and following the application of all applicable conditions laid down under this Regulation in addition to the conditions laid down in Regulation (EU) 2016/679, Directive (EU) 2016/680 and Regulation (EU) 2018/1725,be able to process also special categories of personal data, as a matter of substantial public interest within the meaning of Article 9(2)(g) of Regulation (EU) 2016/679 and Article 10(2)g) of Regulation (EU) 2018/1725.

(46) Having comprehensible information on how high-risk AI systems have been developed and how they perform throughout their lifetime is essential to enable traceability of those systems, verify compliance with the requirements under this Regulation, as well as monitoring of their operations and post market monitoring. This requires keeping records and the availability of a technical documentation, containing information which is necessary to assess the compliance of the AI system with the relevant requirements and facilitate post market monitoring. Such information should include the general characteristics, capabilities and limitations of the system, algorithms, data, training, testing and validation processes used as well as documentation on the relevant risk management system and drawn in a clear and comprehensive form. The technical documentation should be kept up to date, appropriately throughout the lifetime of the AI system. Furthermore, high risk AI systems should technically allow for automatic recording of events (logs) over the duration of the lifetime of the system.

(47) To address concerns related to opacity and complexity of certain AI systems and help deployers to fulfil their obligations under this Regulation, transparency should be required for high-risk AI systems before they are placed on the market or put it into service. High- risk AI systems should be designed in a manner to enable deployers to understand how the AI system works, evaluate its functionality, and comprehend its strengths and limitations. High-risk AI systems should be accompanied by appropriate information in the form of instructions of use. Such information should include the characteristics, capabilities and limitations of performance of the AI system. These would cover information on possible known and foreseeable circumstances related to the use of the high-risk AI system, including deployer action that may influence system behaviour and performance, under which the AI system can lead to risks to health, safety, and fundamental rights, on the changes that have been pre-determined and assessed for conformity by the provider and on the relevant human oversight measures, including the measures to facilitate the interpretation of the outputs of the AI system by the deployers. Transparency, including the accompanying instructions for use, should assist deployers in the use of the system and support informed decision making by them. Among others, deployers should be in a better position to make the correct choice of the system they intend to use in the light of the obligations applicable to them, be educated about the intended and precluded uses, and use the AI system correctly and as appropriate. In order to enhance legibility and accessibility of the information included in the instructions of use, where appropriate, illustrative examples, for instance on the limitations and on the intended and precluded uses of the AI system, should be included. Providers should ensure that all documentation, including the instructions for use, contains meaningful, comprehensive, accessible and understandable information, taking into account the needs and foreseeable knowledge of the target deployers. Instructions for use should be made available in a language which can be easily understood by target deployers, as determined by the Member State concerned.

(48) High-risk AI systems should be designed and developed in such a way that natural persons can oversee their functioning, ensure that they are used as intended and that their impacts are addressed over the system’s lifecycle. For this purpose, appropriate human oversight measures should be identified by the provider of the system before its placing on the market or putting into service. In particular, where appropriate, such measures should guarantee that the system is subject to in-built operational constraints that cannot be overridden by the system itself and is responsive to the human operator, and that the natural persons to whom human oversight has been assigned have the necessary competence, training and authority to carry out that role. It is also essential, as appropriate, to ensure that high-risk AI systems include mechanisms to guide and inform a natural person to whom human oversight has been assigned to make informed decisions if, when and how to intervene in order to avoid negative consequences or risks, or stop the system if it does not perform as intended. Considering the significant consequences for persons in case of incorrect matches by certain biometric identification systems, it is appropriate to provide for an enhanced human oversight requirement for those systems so that no action or decision may be taken by the deployer on the basis of the identification resulting from the system unless this has been separately verified and confirmed by at least two natural persons. Those persons could be from one or more entities and include the person operating or using the system. This requirement should not pose unnecessary burden or delays and it could be sufficient that the separate verifications by the different persons are automatically recorded in the logs generated by the system. Given the specificities of the areas of law enforcement, migration, border control and asylum, this requirement should not apply in cases where Union or national law considers the application of this requirement to be disproportionate.

(49) High-risk AI systems should perform consistently throughout their lifecycle and meet an appropriate level of accuracy, robustness and cybersecurity, in the light of their intended purpose and in accordance with the generally acknowledged state of the art. The Commission and relevant organisations and stakeholders are encouraged to take due consideration of mitigation of risks and negative impacts of the AI system. The expected level of performance metrics should be declared in the accompanying instructions of use. Providers are urged to communicate this information to deployers in a clear and easily understandable way, free of misunderstandings or misleading statements. The EU legislation on legal metrology, including on Measuring Instruments Directive (MID) and Non-automatic weighing instruments (NAWI) Directive, aims to ensure the accuracy of measurements and to help the transparency and fairness of commercial transactions. In this context, in cooperation with relevant stakeholders and organisation, such as metrology and benchmarking authorities, the Commission should encourage, as appropriate, the development of benchmarks and measurement methodologies for AI systems. In doing so, the Commission should take note and collaborate with international partners working on metrology and relevant measurement indicators relating to Artificial Intelligence.

(50) The technical robustness is a key requirement for high-risk AI systems. They should be resilient in relation to harmful or otherwise undesirable behaviour that may result from limitations within the systems or the environment in which the systems operate (e.g. errors, faults, inconsistencies, unexpected situations). Therefore, technical and organisational measures should be taken to ensure robustness of high-risk AI systems, for example by designing and developing appropriate technical solutions to prevent or minimize harmful or otherwise undesirable behaviour. Those technical solution may include for instance mechanisms enabling the system to safely interrupt its operation (fail-safe plans) in the presence of certain anomalies or when operation takes place outside certain predetermined boundaries. Failure to protect against these risks could lead to safety impacts or negatively affect the fundamental rights, for example due to erroneous decisions or wrong or biased outputs generated by the AI system.

(51) Cybersecurity plays a crucial role in ensuring that AI systems are resilient against attempts to alter their use, behaviour, performance or compromise their security properties by malicious third parties exploiting the system’s vulnerabilities. Cyberattacks against AI systems can leverage AI specific assets, such as training data sets (e.g. data poisoning) or trained models (e.g. adversarial attacks or membership inference), or exploit vulnerabilities in the AI system’s digital assets or the underlying ICT infrastructure. To ensure a level of cybersecurity appropriate to the risks, suitable measures, such as security controls, should therefore be taken by the providers of high-risk AI systems, also taking into account as appropriate the underlying ICT infrastructure.

(51a) Without prejudice to the requirements related to robustness and accuracy set out in this Regulation, high-risk AI systems which fall within the scope of the Regulation 2022/0272, in accordance with Article 8 of the Regulation 2022/0272 may demonstrate compliance with the cybersecurity requirement of this Regulation by fulfilling the essential cybersecurity requirements set out in Article 10 and Annex I of the Regulation 2022/0272.When high-risk AI systems fulfil the essential requirements of Regulation 2022/0272, they should be deemed compliant with the cybersecurity requirements set out in this Regulation in so far as the achievement of those requirements is demonstrated in the EU declaration of conformity or parts thereof issued under Regulation 2022/0272. For this purpose, the assessment of the cybersecurity risks, associated to a product with digital elements classified as high-risk AI system according to this Regulation, carried out under Regulation 2022/0272, should consider risks to the cyber resilience of an AI system as regards attempts by unauthorised third parties to alter its use, behaviour or performance, including AI specific vulnerabilities such as data poisoning or adversarial attacks, as well as, as relevant, risks to fundamental rights as required by this Regulation. The conformity assessment procedure provided by this Regulation should apply in relation to the essential cybersecurity requirements of a product with digital elements covered by Regulation 2022/0272 and classified as a high-risk AI system under this Regulation. However, this rule should not result in reducing the necessary level of assurance for critical products with digital elements covered by Regulation 2022/0272. Therefore, by way of derogation from this rule, high-risk AI systems that fall within the scope of this Regulation and are also qualified as important and critical products with digital elements pursuant to Regulation 2022/0272 and to which the conformity assessment procedure based on internal control referred to in Annex VI of this Regulation applies, are subject to the conformity assessment provisions of Regulation 2022/0272 insofar as the essential cybersecurity requirements of Regulation 2022/0272 are concerned. In this case, for all the other aspects covered by this Regulation the respective provisions on conformity assessment based on internal control set out in Annex VI of this Regulation should apply. Building on the knowledge and expertise of ENISA on the cybersecurity policy and tasks assigned to ENISA under the Regulation 2019/1020 the European Commission should cooperate with ENISA on issues related to cybersecurity of AI systems

(52) As part of Union harmonisation legislation, rules applicable to the placing on the market, putting into service and use of high-risk AI systems should be laid down consistently with Regulation (EC) No 765/2008 of the European Parliament and of the Council22Regulation (EC) No 765/2008 of the European Parliament and of the Council of 9 July 2008 setting out the requirements for accreditation and market surveillance relating to the marketing of products and repealing Regulation (EEC) No 339/93 (OJ L 218, 13.8.2008, p. 30) setting out the requirements for accreditation and the market surveillance of products, Decision No 768/2008/EC of the European Parliament and of the Council23Decision No 768/2008/EC of the European Parliament and of the Council of 9 July 2008 on a common framework for the marketing of products, and repealing Council Decision 93/465/EEC (OJ L 218, 13.8.2008, p. 82). on a common framework for the marketing of products and Regulation (EU) 2019/1020 of the European Parliament and of the Council24Regulation (EU) 2019/1020 of the European Parliament and of the Council of 20 June 2019 on market surveillance and compliance of products and amending Directive 2004/42/EC and Regulations (EC) No 765/2008 and (EU) No 305/2011 (Text with EEA relevance) (OJ L 169, 25.6.2019, p. 1–44). on market surveillance and compliance of products (‘New Legislative Framework for the marketing of products’).

(53) It is appropriate that a specific natural or legal person, defined as the provider, takes the responsibility for the placing on the market or putting into service of a high-risk AI system, regardless of whether that natural or legal person is the person who designed or developed the system.

As signatories to the United Nations Convention on the Rights of Persons with Disabilities (UNCRPD), the Union and the Member States are legally obliged to protect persons with disabilities from discrimination and promote their equality, to ensure that persons with disabilities have access, on an equal basis with others, to information and communications technologies and systems, and to ensure respect for privacy for persons with disabilities. Given the growing importance and use of AI systems, the application of universal design principles to all new technologies and services should ensure full and equal access for everyone potentially affected by or using AI technologies, including persons with disabilities, in a way that takes full account of their inherent dignity and diversity. It is therefore essential that Providers ensure full compliance with accessibility requirements, including Directive (EU) 2016/2102 and Directive (EU) 2019/882. Providers should ensure compliance with these requirements by design. Therefore, the necessary measures should be integrated as much as possible into the design of the high-risk AI system.

Given the growing importance and use of AI systems, the application of universal design principles to all new technologies and services should ensure full and equal access for everyone potentially affected by or using AI technologies, including persons with disabilities, in a way that takes full account of their inherent dignity and diversity. It is therefore essential that Providers ensure full compliance with accessibility requirements, including Directive (EU) 2016/2102 and Directive (EU) 2019/882. Providers should ensure compliance with these requirements by design. Therefore, the necessary measures should be integrated as much as possible into the design of the high-risk AI system.

(54) The provider should establish a sound quality management system, ensure the accomplishment of the required conformity assessment procedure, draw up the relevant documentation and establish a robust post-market monitoring system. Providers of high[1]risk AI systems that are subject to obligations regarding quality management systems under relevant sectorial Union law should have the possibility to include the elements of the quality management system provided for in this Regulation as part of the existing quality management system provided for in that other sectorial Union legislation. The complementarity between this Regulation and existing sectorial Union law should also be taken into account in future standardization activities or guidance adopted by the Commission. Public authorities which put into service high-risk AI systems for their own use may adopt and implement the rules for the quality management system as part of the quality management system adopted at a national or regional level, as appropriate, taking into account the specificities of the sector and the competences and organisation of the public authority in question.

(56) To enable enforcement of this Regulation and create a level-playing field for operators, and taking into account the different forms of making available of digital products, it is important to ensure that, under all circumstances, a person established in the Union can provide authorities with all the necessary information on the compliance of an AI system. Therefore, prior to making their AI systems available in the Union, providers established outside the Union shall, by written mandate, appoint an authorised representative established in the Union. This authorised representative plays a pivotal role in ensuring the compliance of the high-risk AI systems placed on the market or put into service in the Union by those providers who are not established in the Union and in serving as their contact person established in the Union.

(56a)      In the light of the nature and complexity of the value chain for AI systems and in line with New Legislative Framework principles, it is essential to ensure legal certainty and facilitate the compliance with this Regulation. Therefore, it is necessary to clarify the role and the specific obligations of relevant operators along the value chain, such as importers and distributors who may contribute to the development of AI systems. In certain situations those operators could act in more than one role at the same time and should therefore fulfil cumulatively all relevant obligations associated with those roles. For example, an operator could act as a distributor and an importer at the same time.

(57) To ensure legal certainty, it is necessary to clarify that, under certain specific conditions, any distributor, importer, deployer or other third-party should be considered a provider of a high-risk AI system and therefore assume all the relevant obligations. This would be the case if that party puts its name or trademark on a high-risk AI system already placed on the market or put into service, without prejudice to contractual arrangements stipulating that the obligations are allocated otherwise, or if that party make a substantial modification to a high-risk AI system that has already been placed on the market or has already been put into service and in a way that it remains a high-risk AI system in accordance with Article 6, or if it modifies the intended purpose of an AI system, including a general purpose AI system, which has not been classified as high-risk and has already been placed on the market or put into service, in a way that the AI system becomes a high-risk AI system in accordance with Article 6. These provisions should apply without prejudice to more specific provisions established in certain New Legislative Framework sectorial legislation with which this Regulation should apply jointly. For example, Article 16, paragraph 2 of Regulation 745/2017, establishing that certain changes should not be considered modifications of a device that could affect its compliance with the applicable requirements, should continue to apply to high-risk AI systems that are medical devices within the meaning of that Regulation.

(57a)      General purpose AI systems may be used as high-risk AI systems by themselves or be components of other high risk AI systems. Therefore, due to their particular nature and in order to ensure a fair sharing of responsibilities along the AI value chain, the providers of such systems should, irrespective of whether they may be used as high-risk AI systems as such by other providers or as components of high-risk AI systems and unless provided otherwise under this Regulation, closely cooperate with the providers of the respective high-risk AI systems to enable their compliance with the relevant obligations under this Regulation and with the competent authorities established under this Regulation.

(57b)     Where, under the conditions laid down in this Regulation, the provider that initially placed the AI system on the market or put it into service should no longer be considered the provider for the purposes of this Regulation, and when that provider has not expressly excluded the change of the AI system into a high-risk AI system, the former provider should nonetheless closely cooperate and make available the necessary information and provide the reasonably expected technical access and other assistance that are required for the fulfilment of the obligations set out in this Regulation, in particular regarding the compliance with the conformity assessment of high-risk AI systems.

(57c)     In addition, where a high-risk AI system that is a safety component of a product which is covered by a relevant New Legislative Framework sectorial legislation is not placed on the market or put into service independently from the product, the product manufacturer as defined under the relevant New Legislative Framework legislation should comply with the obligations of the provider established in this Regulation and notably ensure that the AI system embedded in the final product complies with the requirements of this Regulation.

(57d)     Within the AI value chain multiple parties often supply AI systems, tools and services but also components or processes that are incorporated by the provider into the AI system with various objectives, including the model training, model retraining, model testing and evaluation, integration into software, or other aspects of model development. These parties have an important role in the value chain towards the provider of the high-risk AI system into which their AI systems, tools, services, components or processes are integrated, and should provide by written agreement this provider with the necessary information, capabilities, technical access and other assistance based on the generally acknowledged state of the art, in order to enable the provider to fully comply with the obligations set out in this Regulation, without compromising their own intellectual property rights or trade secrets.

(57e)      Third parties making accessible to the public tools, services, processes, or AI components other than general-purpose AI models, shall not be mandated to comply with requirements targeting the responsibilities along the AI value chain, in particular towards the provider that has used or integrated them, when those tools, services, processes, or AI components are made accessible under a free and open licence. Developers of free and open-source tools, services, processes, or AI components other than general-purpose AI models should be encouraged to implement widely adopted documentation practices, such as model cards and data sheets, as a way to accelerate information sharing along the AI value chain, allowing the promotion of trustworthy AI systems in the Union.

(57f)      The Commission could develop and recommend voluntary model contractual terms between providers of high-risk AI systems and third parties that supply tools, services, components or processes that are used or integrated in high-risk AI systems, to facilitate the cooperation along the value chain. When developing voluntary model contractual terms, the Commission should also take into account possible contractual requirements applicable in specific sectors or business cases.

(58) Given the nature of AI systems and the risks to safety and fundamental rights possibly associated with their use, including as regards the need to ensure proper monitoring of the performance of an AI system in a real-life setting, it is appropriate to set specific responsibilities for deployers. Deployers should in particular take appropriate technical and organisational measures to ensure they use high-risk AI systems in accordance with the instructions of use and certain other obligations should be provided for with regard to monitoring of the functioning of the AI systems and with regard to record-keeping, as appropriate. Furthermore, deployers should ensure that the persons assigned to implement the instructions for use and human oversight as set out in this Regulation have the necessary competence, in particular an adequate level of AI literacy, training and authority to properly fulfil those tasks. These obligations should be without prejudice to other deployer obligations in relation to high-risk AI systems under Union or national law.

(58b) This Regulation is without prejudice to obligations for employers to inform or to inform and consult workers or their representatives under Union or national law and practice, including directive 2002/14/EC on a general framework for informing and consulting employees, on decisions to put into service or use AI systems. It remains necessary to ensure information of workers and their representatives on the planned deployment of high-risk AI systems at the workplace in cases where the conditions for those information or information and consultation obligations in other legal instruments are not fulfilled. Moreover, such information right is ancillary and necessary to the objective of protecting fundamental rights that underlies this Regulation. Therefore, an information requirement to that effect should be laid down in this regulation, without affecting any existing rights of workers.

(58b)     Whilst risks related to AI systems can result from the way such systems are designed, risks can as well stem from how such AI systems are used. Deployers of high-risk AI system therefore play a critical role in ensuring that fundamental rights are protected, complementing the obligations of the provider when developing the AI system. Deployers are best placed to understand how the high-risk AI system will be used concretely and can therefore identify potential significant risks that were not foreseen in the development phase, due to a more precise knowledge of the context of use, the people or groups of people likely to be affected, including vulnerable groups. Deployers of high-risk AI systems referred to in Annex III also play a critical role in informing natural persons and should, when they make decisions or assist in making decisions related to natural persons, where applicable, inform the natural persons that they are subject to the use of the high risk AI system. This information should include the intended purpose and the type of decisions it makes. The deployer should also inform the natural person about its right to an explanation provided under this Regulation. With regard to high-risk AI systems used for law enforcement purposes, this obligation should be implemented in accordance with Article 13 of Directive 2016/680.

(58d)     Any processing of biometric data involved in the use of AI systems for biometric identification for the purpose of law enforcement needs to comply with Article 10 of Directive (EU) 2016/680, that allows such processing only where strictly necessary, subject to appropriate safeguards for the rights and freedoms of the data subject, and where authorised by Union or Member State law. Such use, when authorized, also needs to respect the principles laid down in Article 4 paragraph 1 of Directive (EU) 2016/680 including lawfulness, fairness and transparency, purpose limitation, accuracy and storage limitation

(58e)      Without prejudice to applicable Union law, notably the GDPR and Directive (EU) 2016/680 (the Law Enforcement Directive), considering the intrusive nature of post remote biometric identification systems, the use of post remote biometric identification systems shall be subject to safeguards. Post biometric identification systems should always be used in a way that is proportionate, legitimate and strictly necessary, and thus targeted, in terms of the individuals to be identified, the location, temporal scope and based on a closed dataset of legally acquired video footage. In any case, post remote biometric identification systems should not be used in the framework of law enforcement to lead to indiscriminate surveillance. The conditions for post remote biometric identification should in any case not provide a basis to circumvent the conditions of the prohibition and strict exceptions for real time remote biometric identification.

In order to efficiently ensure that fundamental rights are protected, deployers of high-risk AI systems that are bodies governed by public law, or private operators providing public services and operators deploying certain high-risk AI system referred to in Annex III, such as banking or insurance entities, should carry out a fundamental rights impact assessment prior to putting it into use. Services important for individuals that are of public nature may also be provided by private entities. Private operators providing such services of public nature are linked to tasks in the public interest such as in the area of education, healthcare, social services, housing, administration of justice. The aim of the fundamental rights impact assessment is for the deployer to identify the specific risks to the rights of individuals or groups of individuals likely to be affected, identify measures to be taken in case of the materialisation of these risks. The impact assessment should apply to the first use of the high-risk AI system, and should be updated when the deployer considers that any of the relevant factors have changed. The impact assessment should identify the deployer’s relevant processes in which the high-risk AI system will be used in line with its intended purpose, and should include a description of the period of time and frequency in which the system is intended to be used as well as of specific categories of natural persons and groups who are likely to be affected in the specific context of use. The assessment should also include the identification of specific risks of harm likely to impact the fundamental rights of these persons or groups. While performing this assessment, the deployer should take into account information relevant to a proper assessment of impact, including but not limited to the information given by the provider of the high-risk AI system in the instructions for use. In light of the risks identified, deployers should determine measures to be taken in case of the materialization of these risks, including for example governance arrangements in that specific context of use, such as arrangements for human oversight according to the instructions of use or, complaint handling and redress procedures, as they could be instrumental in mitigating risks to fundamental rights in concrete use-cases. After performing this impact assessment, the deployer should notify the relevant market surveillance authority. Where appropriate, to collect relevant information necessary to perform the impact assessment, deployers of high-risk AI system, in particular when AI systems are used in the public sector, could involve relevant stakeholders, including the representatives of groups of persons likely to be affected by the AI system, independent experts, and civil society organisations in conducting such impact assessments and designing measures to be taken in the case of materialization of the risks. The AI Office should develop a template for a questionnaire in order to facilitate compliance and reduce the administrative burden for deployers.

(60a)      The notion of general purpose AI models should be clearly defined and set apart from the notion of AI systems to enable legal certainty. The definition should be based on the key functional characteristics of a general-purpose AI model, in particular the generality and the capability to competently perform a wide range of distinct tasks. These models are typically trained on large amounts of data, through various methods, such as self-supervised, unsupervised or reinforcement learning. General purpose AI models may be placed on the market in various ways, including through libraries, application programming interfaces (APIs), as direct download, or as physical copy. These models may be further modified or fine-tuned into new models. Although AI models are essential components of AI systems, they do not constitute AI systems on their own. AI models require the addition of further components, such as for example a user interface, to become AI systems. AI models are typically integrated into and form part of AI systems. This Regulation provides specific rules for general purpose AI models and for general purpose AI models that pose systemic risks, which should apply also when these models are integrated or form part of an AI system. It should be understood that the obligations for the providers of general purpose AI models should apply once the general purpose AI models are placed on the market. When the provider of a general purpose AI model integrates an own model into its own AI system that is made available on the market or put into service, that model should be considered as being placed on the market and, therefore, the obligations in this Regulation for models should continue to apply in addition to those for AI systems. The obligations foreseen for models should in any case not apply when an own model is used for purely internal processes that are not essential for providing a product or a service to third parties and the rights of natural persons are not affected. Considering their potential significantly negative effects, the general-purpose AI models with systemic risk should always be subject to the relevant obligations under this Regulation. The definition should not cover AI models used before their placing on the market for the sole purpose of research, development and prototyping activities. This is without prejudice to the obligation to comply with this Regulation when, following such activities, a model is placed on the market.

(60b)     Whereas the generality of a model could, among other criteria, also be determined by a number of parameters, models with at least a billion of parameters and trained with a large amount of data using self-supervision at scale should be considered as displaying significant generality and competently performing a wide range of distinctive tasks.

(60c)      Large generative AI models are a typical example for a general-purpose AI model, given that they allow for flexible generation of content (such as in the form of text, audio, images or video) that can readily accommodate a wide range of distinctive tasks.

(60d)     When a general-purpose AI model is integrated into or forms part of an AI system, this system should be considered a general-purpose AI system when, due to this integration, this system has the capability to serve a variety of purposes. A general-purpose AI system can be used directly, or it may be integrated into other AI systems.

(60e)      Providers of general purpose AI models have a particular role and responsibility in the AI value chain, as the models they provide may form the basis for a range of downstream systems, often provided by downstream providers that necessitate a good understanding of the models and their capabilities, both to enable the integration of such models into their products, and to fulfil their obligations under this or other regulations. Therefore, proportionate transparency measures should be foreseen, including the drawing up and keeping up to date of documentation, and the provision of information on the general purpose AI model for its usage by the downstream providers. Technical documentation should be prepared and kept up to date by the general purpose AI model provider for the purpose of making it available, upon request, to the AI Office and the national competent authorities. The minimal set of elements contained in such documentations should be outlined, respectively, in Annex (IXb) and Annex (IXa). The Commission should be enabled to amend the Annexes by delegated acts in the light of the evolving technological developments.

(60i)      Software and data, including models, released under a free and open-source licence that allows them to be openly shared and where users can freely access, use, modify and redistribute them or modified versions thereof, can contribute to research and innovation in the market and can provide significant growth opportunities for the Union economy. General purpose AI models released under free and open-source licences should be considered to ensure high levels of transparency and openness if their parameters, including the weights, the information on the model architecture, and the information on model usage are made publicly available. The licence should be considered free and open[1]source also when it allows users to run, copy, distribute, study, change and improve software and data, including models under the condition that the original provider of the model is credited, the identical or comparable terms of distribution are respected.

(60i+1) Free and open-source AI components covers the software and data, including models and general purpose AI models, tools, services or processes of an AI system. Free and open[1]source AI components can be provided through different channels, including their development on open repositories. For the purpose of this Regulation, AI components that are provided against a price or otherwise monetised, including through the provision of technical support or other services, including through a software platform, related to the AI component, or the use of personal data for reasons other than exclusively for improving the security, compatibility or interoperability of the software, with the exception of transactions between micro enterprises, should not benefit from the exceptions provided to free and open source AI components. The fact of making AI components available through open repositories should not, in itself, constitute a monetisation.

(60f) The providers of general purpose AI models that are released under a free and open source license, and whose parameters, including the weights, the information on the model architecture, and the information on model usage, are made publicly available should be subject to exceptions as regards the transparency-related requirements imposed on general purpose AI models, unless they can be considered to present a systemic risk, in which case the circumstance that the model is transparent and accompanied by an open source license should not be considered a sufficient reason to exclude compliance with the obligations under this Regulation. In any case, given that the release of general purpose AI models under free and open source licence does not necessarily reveal substantial information on the dataset used for the training or fine-tuning of the model and on how thereby the respect of copyright law was ensured, the exception provided for general purpose AI models from compliance with the transparency-related requirements should not concern the obligation to produce a summary about the content used for model training and the obligation to put in place a policy to respect Union copyright law in particular to identify and respect the reservations of rights expressed pursuant to Article 4(3) of Directive (EU) 2019/790.

(60i)      General purpose models, in particular large generative models, capable of generating text, images, and other content, present unique innovation opportunities but also challenges to artists, authors, and other creators and the way their creative content is created, distributed, used and consumed. The development and training of such models require access to vast amounts of text, images, videos, and other data. Text and data mining techniques may be used extensively in this context for the retrieval and analysis of such content, which may be protected by copyright and related rights. Any use of copyright protected content requires the authorization of the rightholder concerned unless relevant copyright exceptions and limitations apply. Directive (EU) 2019/790 introduced exceptions and limitations allowing reproductions and extractions of works or other subject matter, for the purposes of text and data mining, under certain conditions. Under these rules, rightholders may choose to reserve their rights over their works or other subject matter to prevent text and data mining, unless this is done for the purposes of scientific research. Where the rights to opt out has been expressly reserved in an appropriate manner, providers of general-purpose AI models need to obtain an authorisation from rightholders if they want to carry out text and data mining over such works.

(60j)      Providers that place general purpose AI models on the EU market should ensure compliance with the relevant obligations in this Regulation. For this purpose, providers of general purpose AI models should put in place a policy to respect Union law on copyright and related rights, in particular to identify and respect the reservations of rights expressed by rightholders pursuant to Article 4(3) of Directive (EU) 2019/790. Any provider placing a general purpose AI model on the EU market should comply with this obligation, regardless of the jurisdiction in which the copyright-relevant acts underpinning the training of these general purpose AI models take place. This is necessary to ensure a level playing field among providers of general purpose AI models where no provider should be able to gain a competitive advantage in the EU market by applying lower copyright standards than those provided in the Union.

(60k)     In order to increase transparency on the data that is used in the pre-training and training of general purpose AI models, including text and data protected by copyright law, it is adequate that providers of such models draw up and make publicly available a sufficiently detailed summary of the content used for training the general purpose model. While taking into due account the need to protect trade secrets and confidential business information, this summary should be generally comprehensive in its scope instead of technically detailed to facilitate parties with legitimate interests, including copyright holders, to exercise and enforce their rights under Union law, for example by listing the main data collections or sets that went into training the model, such as large private or public databases or data archives, and by providing a narrative explanation about other data sources used. It is appropriate for the AI Office to provide a template for the summary, which should be simple, effective, and allow the provider to provide the required summary in narrative form.

(60ka)    With regard to the obligations imposed on providers of general purpose AI models to put in place a policy to respect Union copyright law and make publicly available a summary of the content used for the training, the AI Office should monitor whether the provider has fulfilled those obligations without verifying or proceeding to a work-by-work assessment of the training data in terms of copyright compliance. This Regulation does not affect the enforcement of copyright rules as provided for under Union law.

(60g)     Compliance with the obligations foreseen for the providers of general purpose AI models should be commensurate and proportionate to the type of model provider, excluding the need for compliance for persons who develop or use models for non-professional or scientific research purposes, who should nevertheless be encouraged to voluntarily comply with these requirements. Without prejudice to Union Copyright law, compliance with these obligations should take due account of the size of the provider and allow simplified ways of compliance for SMEs including start-ups, that should not represent an excessive cost and not discourage the use of such models. In case of a modification or fine-tuning of a model, the obligations for providers should be limited to that modification or fine-tuning, for example by complementing the already existing technical documentation with information on the modifications, including new training data sources, as a means to comply with the value chain obligations provided in this Regulation.

(60m)    General purpose AI models could pose systemic risks which include, but are not limited to, any actual or reasonably foreseeable negative effects in relation to major accidents, disruptions of critical sectors and serious consequences to public health and safety; any actual or reasonably foreseeable negative effects on democratic processes, public and economic security; the dissemination of illegal, false, or discriminatory content. Systemic risks should be understood to increase with model capabilities and model reach, can arise along the entire lifecycle of the model, and are influenced by conditions of misuse, model reliability, model fairness and model security, the degree of autonomy of the model, its access to tools, novel or combined modalities, release and distribution strategies, the potential to remove guardrails and other factors. In particular, international approaches have so far identified the need to devote attention to risks from potential intentional misuse or unintended issues of control relating to alignment with human intent; chemical, biological, radiological, and nuclear risks, such as the ways in which barriers to entry can be lowered, including for weapons development, design acquisition, or use; offensive cyber capabilities, such as the ways in vulnerability discovery, exploitation, or operational use can be enabled; the effects of interaction and tool use, including for example the capacity to control physical systems and interfere with critical infrastructure; risks from models of making copies of themselves or “self-replicating” or training other models; the ways in which models can give rise to harmful bias and discrimination with risks to individuals, communities or societies; the facilitation of disinformation or harming privacy with threats to democratic values and human rights; risk that a particular event could lead to a chain reaction with considerable negative effects that could affect up to an entire city, an entire domain activity or an entire community.

(60n)    It is appropriate to establish a methodology for the classification of general purpose AI models as general purpose AI model with systemic risks. Since systemic risks result from particularly high capabilities, a general-purpose AI models should be considered to present systemic risks if it has high-impact capabilities, evaluated on the basis of appropriate technical tools and methodologies, or significant impact on the internal market due to its reach. High-impact capabilities in general purpose AI models means capabilities that match or exceed the capabilities recorded in the most advanced general-purpose AI models. The full range of capabilities in a model could be better understood after its release on the market or when users interact with the model. According to the state of the art at the time of entry into force of this Regulation, the cumulative amount of compute used for the training of the general purpose AI model measured in floating point operations (FLOPs) is one of the relevant approximations for model capabilities. The amount of compute used for training cumulates the compute used across the activities and methods that are intended to enhance the capabilities of the model prior to deployment, such as pre-training, synthetic data generation and fine-tuning. Therefore, an initial threshold of FLOPs should be set, which, if met by a general-purpose AI model, leads to a presumption that the model is a general-purpose AI model with systemic risks. This threshold should be adjusted over time to reflect technological and industrial changes, such as algorithmic improvements or increased hardware efficiency, and should be supplemented with benchmarks and indicators for model capability. To inform this, the AI Office should engage with the scientific community, industry, civil society and other experts. Thresholds, as well as tools and benchmarks for the assessment of high-impact capabilities, should be strong predictors of generality, its capabilities and associated systemic risk of general-purpose AI models, and could take into taking into account the way the model will be placed on the market or the number of users it may affect. To complement this system, there should be a possibility for the Commission to take individual decisions designating a general-purpose AI model as a general-purpose AI model with systemic risk if it is found that such model has capabilities or impact equivalent to those captured by the set threshold. This decision should be taken on the basis of an overall assessment of the criteria set out in Annex YY, such as quality or size of the training data set, number of business and end users, its input and output modalities, its degree of autonomy and scalability, or the tools it has access to. Upon a reasoned request of a provider whose model has been designated as a general[1]purpose AI model with systemic risk, the Commission should take the request into account and may decide to reassess whether the general-purpose AI model can still be considered to present systemic risks.

(60o)    It is also necessary to clarify a procedure for the classification of a general purpose AI model with systemic risks. A general purpose AI model that meets the applicable threshold for high-impact capabilities should be presumed to be a general purpose AI models with systemic risk. The provider should notify the AI Office at the latest two weeks after the requirements are met or it becomes known that a general purpose AI model will meet the requirements that lead to the presumption. This is especially relevant in relation to the FLOP threshold because training of general purpose AI models takes considerable planning which includes the upfront allocation of compute resources and, therefore, providers of general purpose AI models are able to know if their model would meet the threshold before the training is completed. In the context of this notification, the provider should be able to demonstrate that because of its specific characteristics, a general purpose AI model exceptionally does not present systemic risks, and that it thus should not be classified as a general purpose AI model with systemic risks. This information is valuable for the AI Office to anticipate the placing on the market of general purpose AI models with systemic risks and the providers can start to engage with the AI Office early on. This is especially important with regard to general-purpose AI models that are planned to be released as open-source, given that, after open-source model release, necessary measures to ensure compliance with the obligations under this Regulation may be more difficult to implement.

(60p)    If the Commission becomes aware of the fact that a general purpose AI model meets the requirements to classify as a general purpose model with systemic risk, which previously had either not been known or of which the relevant provider has failed to notify the Commission, the Commission should be empowered to designate it so. A system of qualified alerts should ensure that the AI Office is made aware by the scientific panel of general-purpose AI models that should possibly be classified as general purpose AI models with systemic risk, in addition to the monitoring activities of the AI Office.

(60q)     The providers of general-purpose AI models presenting systemic risks should be subject, in addition to the obligations provided for providers of general purpose AI models, to obligations aimed at identifying and mitigating those risks and ensuring an adequate level of cybersecurity protection, regardless of whether it is provided as a standalone model or embedded in an AI system or a product. To achieve these objectives, the Regulation should require providers to perform the necessary model evaluations, in particular prior to its first placing on the market, including conducting and documenting adversarial testing of models, also, as appropriate, through internal or independent external testing. In addition, providers of general-purpose AI models with systemic risks should continuously assess and mitigate systemic risks, including for example by putting in place risk management policies, such as accountability and governance processes, implementing post-market monitoring, taking appropriate measures along the entire model’s lifecycle and cooperating with relevant actors across the AI value chain.

(60r)      Providers of general purpose AI models with systemic risks should assess and mitigate possible systemic risks. If, despite efforts to identify and prevent risks related to a general purpose AI model that may present systemic risks, the development or use of the model causes a serious incident, the general purpose AI model provider should without undue delay keep track of the incident and report any relevant information and possible corrective measures to the Commission and national competent authorities. Furthermore, providers should ensure an adequate level of cybersecurity protection for the model and its physical infrastructure, if appropriate, along the entire model lifecycle. Cybersecurity protection related to systemic risks associated with malicious use of or attacks should duly consider accidental model leakage, unsanctioned releases, circumvention of safety measures, and defence against cyberattacks, unauthorised access or model theft. This protection could be facilitated by securing model weights, algorithms, servers, and datasets, such as through operational security measures for information security, specific cybersecurity policies, adequate technical and established solutions, and cyber and physical access controls, appropriate to the relevant circumstances and the risks involved.

(60s)      The Codes of Practice should represent a central tool for the proper compliance with the obligations foreseen under this Regulation for providers of general-purpose AI models. Providers should be able to rely on Codes of Practice to demonstrate compliance with the obligations. By means of implementing acts, the Commission may decide to approve a code of practice and give it a general validity within the Union, or, alternatively, to provide common rules for the implementation of the relevant obligations, if, by the time the Regulation becomes applicable, a Code of Practice cannot be finalised or is not deemed adequate by the AI Office. Once a harmonised standard is published and assessed as suitable to cover the relevant obligations by the AI Office, the compliance with a European harmonised standard should grant providers the presumption of conformity. Providers of general purpose AI models should furthermore be able to demonstrate compliance using alternative adequate means, if codes of practice or harmonized standards are not available, or they choose not to rely on those.

(60t)      The Codes of Practice should represent a central tool for the proper compliance with the obligations foreseen under this Regulation for providers of general-purpose AI models. Providers should be able to rely on Codes of Practice to demonstrate compliance with the obligations. By means of implementing acts, the Commission may decide to approve a code of practice and give it a general validity within the Union, or, alternatively, to provide common rules for the implementation of the relevant obligations, if, by the time the Regulation becomes applicable, a Code of Practice cannot be finalised or is not deemed adequate by the AI Office. Once a harmonised standard is published and assessed as suitable to cover the relevant obligations by the AI Office, the compliance with a European harmonised standard should grant providers the presumption of conformity. Providers of general-purpose AI models should furthermore be able to demonstrate compliance using alternative adequate means, if codes of practice or harmonized standards are not available, or they choose not to rely on those.

(60u) This Regulation regulates AI systems and models by imposing certain requirements and obligations for relevant market actors that are placing them on the market, putting into service or use in the Union, thereby complementing obligations for providers of intermediary services that embed such systems or models into their services regulated by Regulation (EU) 2022/2065. To the extent that such systems or models are embedded into designated very large online platforms or very large online search engines, they are subject to the risk management framework provided for in Regulation (EU) 2022/2065. Consequently, the corresponding obligations of the AI Act should be presumed to be fulfilled, unless significant systemic risks not covered by Regulation (EU) 2022/2065 emerge and are identified in such models. Within this framework, providers of very large online platforms and very large search engines are obliged to assess potential systemic risks stemming from the design, functioning and use of their services, including how the design of algorithmic systems used in the service may contribute to such risks, as well as systemic risks stemming from potential misuses. Those providers are also obliged to take appropriate mitigating measures in observance of fundamental rights.

(60aa)    Considering the quick pace of innovation and the technological evolution of digital services in scope of different instruments of Union law in particular having in mind the usage and the perception of their recipients, the AI systems subject to this Regulation may be provided as intermediary services or parts thereof within the meaning of Regulation (EU) 2022/2065, which should be interpreted in a technology-neutral manner. For example, AI systems may be used to provide online search engines, in particular, to the extent that an AI system such as an online chatbot performs searches of, in principle, all websites, then incorporates the results into its existing knowledge and uses the updated knowledge to generate a single output that combines different sources of information.

(60v)     Furthermore, obligations placed on providers and deployers of certain AI systems in this Regulation to enable the detection and disclosure that the outputs of those systems are artificially generated or manipulated are particularly relevant to facilitate the effective implementation of Regulation (EU) 2022/2065. This applies in particular as regards the obligations of providers of very large online platforms or very large online search engines to identify and mitigate systemic risks that may arise from the dissemination of content that has been artificially generated or manipulated, in particular risk of the actual or foreseeable negative effects on democratic processes, civic discourse and electoral processes, including through disinformation.

(61) Standardisation should play a key role to provide technical solutions to providers to ensure compliance with this Regulation, in line with the state of the art, to promote innovation as well as competitiveness and growth in the single market. Compliance with harmonised standards as defined in Regulation (EU) No 1025/2012 of the European Parliament and of the Council25Regulation (EU) No 1025/2012 of the European Parliament and of the Council of 25 October 2012 on European standardisation, amending Council Directives 89/686/EEC and 93/15/EEC and Directives 94/9/EC, 94/25/EC, 95/16/EC, 97/23/EC, 98/34/EC, 2004/22/EC, 2007/23/EC, 2009/23/EC and 2009/105/EC of the European Parliament and of the Council and repealing Council Decision 87/95/EEC and Decision No 1673/2006/EC of the European Parliament and of the Council (OJ L 316, 14.11.2012, p. 12)., which are normally expected to reflect the state of the art, should be a means for providers to demonstrate conformity with the requirements of this Regulation. A balanced representation of interests involving all relevant stakeholders in the development of standards, in particular SME’s, consumer organisations and environmental and social stakeholders in accordance with Article 5 and 6 of Regulation 1025/2012 should therefore be encouraged. In order to facilitate compliance, the standardisation requests should be issued by the Commission without undue delay. When preparing the standardisation request, the Commission should consult the AI advisory Forum and the Board in order to collect relevant expertise. However, in the absence of relevant references to harmonised standards, the Commission should be able to establish, via implementing acts, and after consultation of the AI Advisory forum, common specifications for certain requirements under this Regulation. The common specification should be an exceptional fall back solution to facilitate the provider’s obligation to comply with the requirements of this Regulation, when the standardisation request has not been accepted by any of the European standardisation organisations, or when the relevant harmonized standards insufficiently address fundamental rights concerns, or when the harmonised standards do not comply with the request, or when there are delays in the adoption of an appropriate harmonised standard. If such delay in the adoption of a harmonised standard is due to the technical complexity of the standard in question, this should be considered by the Commission before contemplating the establishment of common specifications. When developing common specifications, the Commission is encouraged to cooperate with international partners and international standardisation bodies.

(61a) It is appropriate that, without prejudice to the use of harmonised standards and common specifications, providers of high-risk AI system that has been trained and tested on data reflecting the specific geographical, behavioural, contextual or functional setting within which the AI system is intended to be used, should be presumed to be in compliance with the respective measure provided for under the requirement on data governance set out in this Regulation. Without prejudice to the requirements related to robustness and accuracy set out in this Regulation, in line with Article 54(3) of Regulation (EU) 2019/881 of the European Parliament and of the Council, high-risk AI systems that have been certified or for which a statement of conformity has been issued under a cybersecurity scheme pursuant to that Regulation and the references of which have been published in the Official Journal of the European Union should be presumed to be in compliance with the cybersecurity requirement of this Regulation in so far as the cybersecurity certificate or statement of conformity or parts thereof cover the cybersecurity requirement of this Regulation This remains without prejudice to the voluntary nature of that cybersecurity scheme.

(62) In order to ensure a high level of trustworthiness of high-risk AI systems, those systems should be subject to a conformity assessment prior to their placing on the market or putting into service

(63) It is appropriate that, in order to minimise the burden on operators and avoid any possible duplication, for high-risk AI systems related to products which are covered by existing Union harmonisation legislation following the New Legislative Framework approach, the compliance of those AI systems with the requirements of this Regulation should be assessed as part of the conformity assessment already foreseen under that legislation. The applicability of the requirements of this Regulation should thus not affect the specific logic, methodology or general structure of conformity assessment under the relevant specific New Legislative Framework legislation

(64) Given the complexity of high-risk AI systems and the risks that are associated to them, it is important to develop an adequate system of conformity assessment procedure for high risk AI systems involving notified bodies, so called third party conformity assessment. However, given the current experience of professional pre-market certifiers in the field of product safety and the different nature of risks involved, it is appropriate to limit, at least in an initial phase of application of this Regulation, the scope of application of third-party conformity assessment for high-risk AI systems other than those related to products. Therefore, the conformity assessment of such systems should be carried out as a general rule by the provider under its own responsibility, with the only exception of AI systems intended to be used for biometrics.

(65) In order to carry out third-party conformity assessments when so required, notified bodies should be notified under this Regulation by the national competent authorities, provided they are compliant with a set of requirements, notably on independence, competence, absence of conflicts of interests and suitable cybersecurity requirements. Notification of those bodies should be sent by national competent authorities to the Commission and the other Member States by means of the electronic notification tool developed and managed by the Commission pursuant to Article R23 of Decision 768/2008.

(65a)      In line with Union commitments under the World Trade Organization Agreement on Technical Barriers to Trade, it is adequate to facilitate the mutual recognition of conformity assessment results produced by competent conformity assessment bodies, independent of the territory in which they are established, provided that those conformity assessment bodies established under the law of a third country meet the applicable requirements of the Regulation and the Union has concluded an agreement to that extent. In this context, the Commission should actively explore possible international instruments for that purpose and in particular pursue the conclusion of mutual recognition agreements with third countries.

(66) In line with the commonly established notion of substantial modification for products regulated by Union harmonisation legislation, it is appropriate that whenever a change occurs which may affect the compliance of a high risk AI system with this Regulation (e.g. change of operating system or software architecture), or when the intended purpose of the system changes, that AI system should be considered a new AI system which should undergo a new conformity assessment. However, changes occuring to the algorithm and the performance of AI systems which continue to ‘learn’ after being placed on the market or put into service (i.e. automatically adapting how functions are carried out) should not constitute a substantial modification, provided that those changes have been pre- determined by the provider and assessed at the moment of the conformity assessment.

(67) High-risk AI systems should bear the CE marking to indicate their conformity with this Regulation so that they can move freely within the internal market. For high-risk AI systems embedded in a product, a physical CE marking should be affixed, and may be complemented by a digital CE marking. For high-risk AI systems only provided digitally, a digital CE marking should be used. Member States should not create unjustified obstacles to the placing on the market or putting into service of high-risk AI systems that comply with the requirements laid down in this Regulation and bear the CE marking.

(68) Under certain conditions, rapid availability of innovative technologies may be crucial for health and safety of persons, the protection of the environment and climate change and for society as a whole. It is thus appropriate that under exceptional reasons of public security or protection of life and health of natural persons, environmental protection and the protection of key industrial and infrastructural assets , Market Surveillance Authorities could authorise the placing on the market or putting into service of AI systems which have not undergone a conformity assessment. In a duly justified situations as provided under this regulations, law enforcement authorities or civil protection authorities may put a specific high-risk AI system into service without the authorisation of the market surveillance authority, provided that such authorisation is requested during or after the use without undue delay.

(69) In order to facilitate the work of the Commission and the Member States in the artificial intelligence field as well as to increase the transparency towards the public, providers of high-risk AI systems other than those related to products falling within the scope of relevant existing Union harmonisation legislation, as well as providers who consider that an AI system referred to in annex III is by derogation not high-risk, should be required to register themselves and information about their AI system in a EU database, to be established and managed by the Commission. Before using a high-risk AI system listed in Annex III, deployers of high-risk AI systems that are public authorities, agencies or bodies, shall register themselves in such database and select the system that they envisage to use.. Other deployers should be entitled to do so voluntarily. This section of the database should be publicly accessible, free of charge, the information should be easily navigatable, understandable and machine-readable. The database should also be user-friendly, for example by providing search functionalities, including through keywords, allowing the general public to find relevant information included in Annex VIII and on the areas of risk under Annex III to which the high-risk AI systems correspond. . Any substantial modification of high-risk AI systems should also be registered in the EU database. For high risk AI systems in the area of law enforcement, migration, asylum and border control management, the registration obligations should be fulfilled in a secure non-public section of the database. Access to the secure non-public section should be strictly limited to the Commission as well as to market surveillance authorities with regard to their national section of that database. High risk AI systems in the area of critical infrastructure should only be registered at national level. The Commission should be the controller of the EU database, in accordance with Regulation (EU) 2018/1725 of the European Parliament and of the Council26Regulation (EU) 2016/679 of the European Parliament and of the Council of 27 April 2016 on the protection of natural persons with regard to the processing of personal data and on the free movement of such data, and repealing Directive 95/46/EC (General Data Protection Regulation) (OJ L 119, 4.5.2016, p. 1).. In order to ensure the full functionality of the database, when deployed, the procedure for setting the database should include the elaboration of functional specifications by the Commission and an independent audit report. The Commission should take into account cybersecurity and hazard-related risks when carrying out its tasks as data controller on the EU database. In order to maximise the availability and use of the database by the public, the database, including the information made available through it, should comply with requirements under the Directive 2019/882.

(70) Certain AI systems intended to interact with natural persons or to generate content may pose specific risks of impersonation or deception irrespective of whether they qualify as high-risk or not. In certain circumstances, the use of these systems should therefore be subject to specific transparency obligations without prejudice to the requirements and obligations for high-risk AI systems and subject to targeted exceptions to take into account the special need of law enforcement. In particular, natural persons should be notified that they are interacting with an AI system, unless this is obvious from the point of view of a natural person who is reasonably well-informed, observant and circumspect taking into account the circumstances and the context of use. When implementing such obligation, the characteristics of individuals belonging to vulnerable groups due to their age or disability should be taken into account to the extent the AI system is intended to interact with those groups as well. Moreover, natural persons should be notified when they are exposed to systems that, by processing their biometric data, can identify or infer the emotions or intentions of those persons or assign them to specific categories. Such specific categories can relate to aspects such as sex, age, hair colour, eye colour, tattoos, personal traits, ethnic origin, personal preferences and interests. Such information and notifications should be provided in accessible formats for persons with disabilities.

(70a)      A variety of AI systems can generate large quantities of synthetic content that becomes increasingly hard for humans to distinguish from human-generated and authentic content. The wide availability and increasing capabilities of those systems have a significant impact on the integrity and trust in the information ecosystem, raising new risks of misinformation and manipulation at scale, fraud, impersonation and consumer deception. In the light of those impacts, the fast technological pace and the need for new methods and techniques to trace origin of information, it is appropriate to require providers of those systems to embed technical solutions that enable marking in a machine readable format and detection that the output has been generated or manipulated by an AI system and not a human. Such techniques and methods should be sufficiently reliable, interoperable, effective and robust as far as this is technically feasible, taking into account available techniques or a combination of such techniques, such as watermarks, metadata identifications, cryptographic methods for proving provenance and authenticity of content, logging methods, fingerprints or other techniques, as may be appropriate. When implementing this obligation, providers should also take into account the specificities and the limitations of the different types of content and the relevant technological and market developments in the field, as reflected in the generally acknowledged state-of-the-art. Such techniques and methods can be implemented at the level of the system or at the level of the model, including general-purpose AI models generating content, thereby facilitating fulfilment of this obligation by the downstream provider of the AI system. To remain proportionate, it is appropriate to envisage that this marking obligation should not cover AI systems performing primarily an assistive function for standard editing or AI systems not substantially altering the input data provided by the deployer or the semantics thereof.

(70b)     Further to the technical solutions employed by the providers of the system, deployers , who use an AI system to generate or manipulate image, audio or video content that appreciably resembles existing persons, places or events and would falsely appear to a person to be authentic (‘deep fakes’), should also clearly and distinguishably disclose that the content has been artificially created or manipulated by labelling the artificial intelligence output accordingly and disclosing its artificial origin The compliance with this transparency obligation should not be interpreted as indicating that the use of the system or its output impedes the right to freedom of expression and the right to freedom of the arts and sciences guaranteed in the Charter of Fundamental Rights of the EU, in particular where the content is part of an evidently creative, satirical, artistic or fictional work or programme, subject to appropriate safeguards for the rights and freedoms of third parties. In those cases, the transparency obligation for deep fakes set out in this Regulation is limited to disclosure of the existence of such generated or manipulated content in an appropriate manner that does not hamper the display or enjoyment of the work, including its normal exploitation and use, while maintaining the utility and quality of the work. In addition, it is also appropriate to envisage a similar disclosure obligation in relation to AI-generated or manipulated text to the extent it is published with the purpose of informing the public on matters of public interest unless the AI-generated content has undergone a process of human review or editorial control and a natural or legal person holds editorial responsibility for the publication of the content.

(70c)      To ensure consistent implementation, it is appropriate to empower the Commission to adopt implementing acts on the application of the provisions on the labelling and detection of artificially generated or manipulated content. Without prejudice to the mandatory nature and full applicability of these obligations, the Commission may also encourage and facilitate the drawing up of codes of practice at Union level to facilitate the effective implementation of the obligations regarding the detection and labelling of artificially generated or manipulated content, including to support practical arrangements for making, as appropriate, the detection mechanisms accessible and facilitating cooperation with other actors in the value chain, disseminating content or checking its authenticity and provenance to enable the public to effectively distinguish AI-generated content.

(70d)     The obligations placed on providers and deployers of certain AI systems in this Regulation to enable the detection and disclosure that the outputs of those systems are artificially generated or manipulated are particularly relevant to facilitate the effective implementation of Regulation (EU) 2022/2065. This applies in particular as regards the obligations of providers of very large online platforms or very large online search engines to identify and mitigate systemic risks that may arise from the dissemination of content that has been artificially generated or manipulated, in particular risk of the actual or foreseeable negative effects on democratic processes, civic discourse and electoral processes, including through disinformation. The requirement to label content generated by AI systems under this Regulation is without prejudice to the obligation in Article 16(6) of Regulation 2022/2065 for providers of hosting services to process notices on illegal content received pursuant to Article 16(1) and should not influence the assessment and the decision on the illegality of the specific content. That assessment should be performed solely with reference to the rules governing the legality of the content.

(70e)      The compliance with the transparency obligations for the AI systems coved by this Regulation should not be interpreted as indicating that the use of the system or its output is lawful under this Regulation or other Union and Member State law and should be without prejudice to other transparency obligations for deployers of AI systems laid down in Union or national law.

(71) Artificial intelligence is a rapidly developing family of technologies that requires regulatory oversight and a safe and controlled space for experimentation, while ensuring responsible innovation and integration of appropriate safeguards and risk mitigation measures. To ensure a legal framework that promotes innovation, is future-proof and resilient to disruption, Member States should ensure that their national competent authorities establish at least one artificial intelligence regulatory sandboxes at national level to facilitate the development and testing of innovative AI systems under strict regulatory oversight before these systems are placed on the market or otherwise put into service. Member States could also fulfill this obligation through participating in already existing regulatory sandboxes or establishing jointly a sandbox with one or several Member States’ competent authorities, insofar as this participation provides equivalent level of national coverage for the participating Member States. Regulatory sandboxes could be established in physical, digital or hybrid form and may accommodate physical as well as digital products. Establishing authorities should also ensure that the regulatory sandboxes have the adequate resources for their functioning, including financial and human resources.

(72) The objectives of the AI regulatory sandboxes should be to foster AI innovation by establishing a controlled experimentation and testing environment in the development and pre-marketing phase with a view to ensuring compliance of the innovative AI systems with this Regulation and other relevant Union and Member States legislation, to enhance legal certainty for innovators and the competent authorities’ oversight and understanding of the opportunities, emerging risks and the impacts of AI use, to facilitate regulatory learning for authorities and companies, including with a view to future adaptions of the legal framework, to support cooperation and the sharing of best practices with the authorities involved in the AI regulatory sandbox, and to accelerate access to markets, including by removing barriers for small and medium enterprises (SMEs), including start-ups. Regulatory sandboxes should be widely available throughout the Union, and particular attention should be given to their accessibility for SMEs, including startups. The participation in the AI regulatory sandbox should focus on issues that raise legal uncertainty for providers and prospective providers to innovate, experiment with AI in the Union and contribute to evidence-based regulatory learning. The supervision of the AI systems in the AI regulatory sandbox should therefore cover their development, training, testing and validation before the systems are placed on the market or put into service, as well as the notion and occurrence of substantial modification that may require a new conformity assessment procedure. Any significant risks identified during the development and testing of such AI systems should result in adequate mitigation and, failing that, in the suspension of the development and testing process Where appropriate, national competent authorities establishing AI regulatory sandboxes should cooperate with other relevant authorities, including those supervising the protection of fundamental rights,, and could allow for the involvement of other actors within the AI ecosystem such as national or European standardisation organisations, notified bodies, testing and experimentation facilities, research and experimentation labs, European Digital innovation hubs and relevant stakeholder and civil society organisations. To ensure uniform implementation across the Union and economies of scale, it is appropriate to establish common rules for the regulatory sandboxes’ implementation and a framework for cooperation between the relevant authorities involved in the supervision of the sandboxes. AI regulatory sandboxes established under this Regulation should be without prejudice to other legislation allowing for the establishment of other sandboxes aiming at ensuring compliance with legislation other that this Regulation. Where appropriate, relevant competent authorities in charge of those other regulatory sandboxes should consider the benefits of using those sandboxes also for the purpose of ensuring compliance of AI systems with this Regulation. Upon agreement between the national competent authorities and the participants in the AI regulatory sandbox, testing in real world conditions may also be operated and supervised in the framework of the AI regulatory sandbox.

(72a)      This Regulation should provide the legal basis for the providers and prospective providers in the AI regulatory sandbox to use personal data collected for other purposes for developing certain AI systems in the public interest within the AI regulatory sandbox, only under specified conditions, in line with Article 6(4) and 9(2)(g) of Regulation (EU) 2016/679, and Article 5, 6 and 10 of Regulation (EU) 2018/1725, and without prejudice to Articles 4(2) and 10 of Directive (EU) 2016/680. All other obligations of data controllers and rights of data subjects under Regulation (EU) 2016/679, Regulation (EU) 2018/1725 and Directive (EU) 2016/680 remain applicable. In particular, this Regulation should not provide a legal basis in the meaning of Article 22(2)(b) of Regulation (EU) 2016/679 and Article 24(2)(b) of Regulation (EU) 2018/1725. Providers and prospective providers in the sandbox should ensure appropriate safeguards and cooperate with the competent authorities, including by following their guidance and acting expeditiously and in good faith to adequately mitigate any identified – significant risks to safety, health, and fundamental rights that may arise during the development, testing and experimentation in the sandbox.

(72b)     In order to accelerate the process of development and placing on the market of high-risk AI systems listed in Annex III, it is important that providers or prospective providers of such systems may also benefit from a specific regime for testing those systems in real world conditions, without participating in an AI regulatory sandbox. However, in such cases and taking into account the possible consequences of such testing on individuals, it should be ensured that appropriate and sufficient guarantees and conditions are introduced by the Regulation for providers or prospective providers. Such guarantees should include, among others, requesting informed consent of natural persons to participate in testing in real world conditions, with the exception of law enforcement in cases where the seeking of informed consent would prevent the AI system from being tested. Consent of subjects to participate in such testing under this Regulation is distinct from and without prejudice to consent of data subjects for the processing of their personal data under the relevant data protection law. It is also important to minimise the risks and enable oversight by competent authorities and therefore require prospective providers to have a real-world testing plan submitted to competent market surveillance authority, register the testing in dedicated sections in the EU-wide database subject to some limited exceptions, set limitations on the period for which the testing can be done and require additional safeguards for persons belonging to certain vulnerable groups as well as a written agreement defining the roles and responsibilities of prospective providers and deployers and effective oversight by competent personnel involved in the real world testing. Furthermore, it is appropriate to envisage additional safeguards to ensure that the predictions, recommendations or decisions of the AI system can be effectively reversed and disregarded and that personal data is protected and is deleted when the subjects have withdrawn their consent to participate in the testing without prejudice to their rights as data subjects under the EU data protection law. As regards transfer of data, it is also appropriate to envisage that data collected and processed for the purpose of the testing in real world conditions should only be transferred to third countries outside the Union provided appropriate and applicable safeguards under Union law are implemented, notably in accordance with bases for transfer of personal data under Union law on data protection, while for non-personal data appropriate safeguards are put in place in accordance with Union law, such as the Data Governance Act and the Data Act.

(72c)      To ensure that Artificial Intelligence leads to socially and environmentally beneficial outcomes, Member States are encouraged to support and promote research and development of AI solutions in support of socially and environmentally beneficial outcomes, such as AI-based solutions to increase accessibility for persons with disabilities, tackle socio-economic inequalities, or meet environmental targets, by allocating sufficient resources, including public and Union funding, and, where appropriate and provided that the eligibility and selection criteria are fulfilled, considering in particular projects which pursue such objectives. Such projects should be based on the principle of interdisciplinary cooperation between AI developers, experts on inequality and non- discrimination, accessibility, consumer, environmental, and digital rights, as well as academics.

(73) In order to promote and protect innovation, it is important that the interests of SMEs, including start-ups, that are providers or deployers of AI systems are taken into particular account. To this objective, Member States should develop initiatives, which are targeted at those operators, including on , awareness raising and information communication. Member States shall provide SME’s, including start-ups, having a registered office or a branch in the Union, with priority access to the AI regulatory sandboxes provided that they fulfil the eligibility conditions and selection criteria and without precluding other providers and prospective providers to access the sandboxes provided the same conditions and criteria are fulfilled. Member States shall utilise existing channels and where appropriate, establish new dedicated channels for communication with SMEs, start-ups, deployers other innovators and, as appropriate, local public authorities, to support SMEs throughout their development path by providing guidance and responding to queries about the implementation of this Regulation. Where appropriate, these channels shall work together to create synergies and ensure homogeneity in their guidance to SMEs including start-ups and deployers. Additionally, Member States should facilitate the participation of SMEs and other relevant stakeholders in the standardisation development processes. Moreover, the specific interests and needs of SMEs including start-up providers should be taken into account when Notified Bodies set conformity assessment fees. The Commission should regularly assess the certification and compliance costs for SMEs including start-ups, through transparent consultations deployers and should work with Member States to lower such costs. For example, translation costs related to mandatory documentation and communication with authorities may constitute a significant cost for providers and other operators, notably those of a smaller scale. Member States should possibly ensure that one of the languages determined and accepted by them for relevant providers’ documentation and for communication with operators is one which is broadly understood by the largest possible number of cross-border deployers. In order to address the specific needs of SMEs including start-ups, the Commission should provide standardised templates for the areas covered by this Regulation upon request of the AI Board. Additionally, the Commission should complement Member States’ efforts by providing a single information platform with easy-to-use information with regards to this Regulation for all providers and deployers, by organising appropriate communication campaigns to raise awareness about the obligations arising from this Regulation, and by evaluating and promoting the convergence of best practices in public procurement procedures in relation to AI systems. Medium-sized enterprises which recently changed from the small to medium-size category within the meaning of the Annex to Recommendation 2003/361/EC (Article 16) should have access to these support measures , as these new medium-sized enterprises may sometimes lack the legal resources and training necessary to ensure proper understanding and compliance with provisions.

(73a)      In order to promote and protect innovation, the AI-on demand platform, all relevant EU funding programmes and projects, such as Digital Europe Programme, Horizon Europe, implemented by the Commission and the Member States at national or Union level should, as appropriate, contribute to the achievement of the objectives of this Regulation.

(74) In particular, in order to minimise the risks to implementation resulting from lack of knowledge and expertise in the market as well as to facilitate compliance of providers, notably SMEs, including start-ups, and notified bodies with their obligations under this Regulation, the AI-on demand platform, the European Digital Innovation Hubs and the Testing and Experimentation Facilities established by the Commission and the Member States at national or EU level should contribute to the implementation of this Regulation. Within their respective mission and fields of competence, they may provide in particular technical and scientific support to providers and notified bodies.

(74a)      Moreover, in order to ensure proportionality considering the very small size of some operators regarding costs of innovation, it is appropriate to allow microenterprises to fulfill one of the most costly obligations, namely to establish a quality management system, in a simplified manner which would reduce the administrative burden and the costs for those enterprises without affecting the level of protection and the need for compliance with the requirements for high-risk AI systems. The Commission should develop guidelines to specify the elements of the quality management system to be fulfilled in this simplified manner by microentreprises.

(75) It is appropriate that the Commission facilitates, to the extent possible, access to Testing and Experimentation Facilities to bodies, groups or laboratories established or accredited pursuant to any relevant Union harmonisation legislation and which fulfil tasks in the context of conformity assessment of products or devices covered by that Union harmonisation legislation. This is notably the case for expert panels, expert laboratories and reference laboratories in the field of medical devices pursuant to Regulation (EU) 2017/745 and Regulation (EU) 2017/746.

(75a)      This Regulation should establish a governance framework that both allows to coordinate and support the application of this Regulation at national level, as well as build capabilities at Union level and integrate stakeholders in the field of artificial intelligence. The effective implementation and enforcement of this Regulation require a governance framework that allows to coordinate and build up central expertise at Union level. The Commission has established the AI Office by Commission decision of […], which has as its mission to develop Union expertise and capabilities in the field of artificial intelligence and to contribute to the implementation of Union legislation on artificial intelligence. Member States should facilitate the tasks of the AI Office with a view to support the development of Union expertise and capabilities at Union level and to strengthen the functioning of the digital single market. Furthermore, a European Artificial Intelligence Board composed of representatives of the Member States, a scientific panel to integrate the scientific community and an advisory forum to contribute stakeholder input to the implementation of this Regulation, both at national and Union level, should be established. The development of Union expertise and capabilities should also include making use of existing resources and expertise, notably through synergies with structures built up in the context of the Union level enforcement of other legislation and synergies with related initiatives at Union level, such as the EuroHPC Joint Undertaking and the AI Testing and Experimentation Facilities under the Digital Europe Programme.

(76) In order to facilitate a smooth, effective and harmonised implementation of this Regulation a European Artificial Intelligence Board should be established. The Board should reflect the various interests of the AI eco-system and be composed of representatives of the Member States. The Board should be responsible for a number of advisory tasks, including issuing opinions, recommendations, advice or contributing to guidance on matters related to the implementation of this Regulation, including on enforcement matters, technical specifications or existing standards regarding the requirements established in this Regulation and providing advice to the Commission and the Member States and their national competent authorities on specific questions related to artificial intelligence. In order to give some flexibility to Member States in the designation of their representatives in the AI Board, such representatives may be any persons belonging to public entities who should have the relevant competences and powers to facilitate coordination at national level and contribute to the achievement of the Board’s tasks. The Board should establish two standing sub-groups to provide a platform for cooperation and exchange among market surveillance authorities and notifying authorities on issues related respectively to market surveillance and notified bodies. The standing subgroup for market surveillance should act as the Administrative Cooperation Group (ADCO) for this Regulation in the meaning of Article 30 of Regulation (EU) 2019/1020. In line with the role and tasks of the Commission pursuant to Article 33 of Regulation (EU) 2019/1020, the Commission should support the activities of the standing subgroup for market surveillance by undertaking market evaluations or studies, notably with a view to identifying aspects of this Regulation requiring specific and urgent coordination among market surveillance authorities. The Board may establish other standing or temporary sub-groups as appropriate for the purpose of examining specific issues. The Board should also cooperate, as appropriate, with relevant EU bodies, experts groups and networks active in the context of relevant EU legislation, including in particular those active under relevant EU regulation on data, digital products and services.

(76x) With a view to ensure the involvement of stakeholders in the implementation and application of this Regulation, an advisory forum should be established to advise and provide technical expertise to the Board and the Commission. To ensure a varied and balanced stakeholder representation between commercial and non-commercial interest and, within the category of commercial interests, with regards to SMEs and other undertakings, the advisory forum should comprise inter alia industry, start-ups, SMEs, academia, civil society, including social partners, as well as the Fundamental Rights Agency, European Union Agency for Cybersecurity, the European Committee for Standardization (CEN), the European Committee for Electrotechnical Standardization (CENELEC) and the European Telecommunications Standards Institute (ETSI).

(76y) To support the implementation and enforcement of this Regulation, in particular the monitoring activities of the AI Office as regards general-purpose AI models, a scientific panel of independent experts should be established. The independent experts constituting the scientific panel should be selected on the basis of up-to-date scientific or technical expertise in the field of artificial intelligence and should perform their tasks with impartiality, objectivity and ensure the confidentiality of information and data obtained in carrying out their tasks and activities. To allow reinforcing national capacities necessary for the effective enforcement of this Regulation, Member States should be able to request support from the pool of experts constituting the scientific panel for their enforcement activities.

(76a)      In order to support adequate enforcement as regards AI systems and reinforce the capacities of the Member States, EU AI testing support structures should be established and made available to the Member States.

(77) Member States hold a key role in the application and enforcement of this Regulation. In this respect, each Member State should designate at least one notifying authority and at least one market surveillance authority as national competent authorities for the purpose of supervising the application and implementation of this Regulation. Member States may decide to appoint any kind of public entity to perform the tasks of the national competent authorities within the meaning of this Regulation, in accordance with their specific national organisational characteristics and needs. In order to increase organisation efficiency on the side of Member States and to set a single point of contact vis-à-vis the public and other counterparts at Member State and Union levels, each Member State should designate a market surveillance authority to act as single point of contact.

(77a)      The national competent authorities should exercise their powers independently, impartially and without bias, so as to safeguard the principles of objectivity of their activities and tasks and to ensure the application and implementation of this Regulation. The members of these authorities should refrain from any action incompatible with their duties and should be subject to confidentiality rules under this Regulation.

(78) In order to ensure that providers of high-risk AI systems can take into account the experience on the use of high-risk AI systems for improving their systems and the design and development process or can take any possible corrective action in a timely manner, all providers should have a post-market monitoring system in place. Where relevant, post- market monitoring should include an analysis of the interaction with other AI systems including other devices and software. Post-market monitoring should not cover sensitive operational data of deployers which are law enforcement authorities. This system is also key to ensure that the possible risks emerging from AI systems which continue to ‘learn’ after being placed on the market or put into service can be more efficiently and timely addressed. In this context, providers should also be required to have a system in place to report to the relevant authorities any serious incidents resulting from the use of their AI systems, meaning incident or malfunctioning leading to death or serious damage to health, serious and irreversible disruption of the management and operation of critical infrastructure, breaches of obligations under Union law intended to protect fundamental rights or serious damage to property or the environment.

(79) In order to ensure an appropriate and effective enforcement of the requirements and obligations set out by this Regulation, which is Union harmonisation legislation, the system of market surveillance and compliance of products established by Regulation (EU) 2019/1020 should apply in its entirety. Market surveillance authorities designated pursuant to this Regulation should have all enforcement powers under this Regulation and Regulation (EU) 2019/1020 and should exercise their powers and carry out their duties independently, impartially and without bias. Although the majority of AI systems are not subject to specific requirements and obligations under this Regulation, market surveillance authorities may take measures in relation to all AI systems when they present a risk in accordance with this Regulation. Due to the specific nature of Union institutions, agencies and bodies falling within the scope of this Regulation, it is appropriate to designate the European Data Protection Supervisor as a competent market surveillance authority for them. This should be without prejudice to the designation of national competent authorities by the Member States. Market surveillance activities should not affect the ability of the supervised entities to carry out their tasks independently, when such independence is required by Union law.

(79a)      This Regulation is without prejudice to the competences, tasks, powers and independence of relevant national public authorities or bodies which supervise the application of Union law protecting fundamental rights, including equality bodies and data protection authorities. Where necessary for their mandate, those national public authorities or bodies should also have access to any documentation created under this Regulation. A specific safeguard procedure should be set for ensuring adequate and timely enforcement against AI systems presenting a risk to health, safety and fundamental rights. The procedure for such AI systems presenting a risk should be applied to high-risk AI systems presenting a risk, prohibited systems which have been placed on the market, put into service or used in violation of the prohibited practices laid down in this Regulation and AI systems which have been made available in violation of the transparency requirements laid down in this Regulation and present a risk.

(80) Union legislation on financial services includes internal governance and risk management rules and requirements which are applicable to regulated financial institutions in the course of provision of those services, including when they make use of AI systems. In order to ensure coherent application and enforcement of the obligations under this Regulation and relevant rules and requirements of the Union financial services legislation, the competent authorities for the supervision and enforcement of the financial services legislation, notably competent authorities as defined in Directive 2009/138/EC, Directive (EU) 2016/97, Directive 2013/36/EU Regulation (EU) No 575/2013, Directive 2008/48/EC and Directive 2014/17/EU of the European Parliament and of the Council, should be designated, within their respective competences, as competent authorities for the purpose of supervising the implementation of this Regulation, including for market surveillance activities, as regards AI systems provided or used by regulated and supervised financial institutions unless Member States decide to designate another authority to fulfil these market surveillance tasks. Those competent authorities should have all powers under this Regulation and Regulation (EU) 2019/1020 on market surveillance to enforce the requirements and obligations of this Regulation, including powers to carry our ex post market surveillance activities that can be integrated, as appropriate, into their existing supervisory mechanisms and procedures under the relevant Union financial services legislation. It is appropriate to envisage that, when acting as market surveillance authorities under this Regulation, the national authorities responsible for the supervision of credit institutions regulated under Directive 2013/36/EU, which are participating in the Single Supervisory Mechanism (SSM) established by Council Regulation No 1024/2013, should report, without delay, to the European Central Bank any information identified in the course of their market surveillance activities that may be of potential interest for the European Central Bank’s prudential supervisory tasks as specified in that Regulation. To further enhance the consistency between this Regulation and the rules applicable to credit institutions regulated under Directive 2013/36/EU of the European Parliament and of the Council27Directive 2013/36/EU of the European Parliament and of the Council of 26 June 2013 on access to the activity of credit institutions and the prudential supervision of credit institutions and investment firms, amending Directive 2002/87/EC and repealing Directives 2006/48/EC and 2006/49/EC (OJ L 176, 27.6.2013, p. 338)., it is also appropriate to integrate some of the providers’ procedural obligations in relation to risk management, post marketing monitoring and documentation into the existing obligations and procedures under Directive 2013/36/EU. In order to avoid overlaps, limited derogations should also be envisaged in relation to the quality management system of providers and the monitoring obligation placed on deployers of high-risk AI systems to the extent that these apply to credit institutions regulated by Directive 2013/36/EU. The same regime should apply to insurance and re-insurance undertakings and insurance holding companies under Directive 2009/138/EU (Solvency II) and the insurance intermediaries under Directive 2016/97/EU and other types of financial institutions subject to requirements regarding internal governance, arrangements or processes established pursuant to the relevant Union financial services legislation to ensure consistency and equal treatment in the financial sector.

(80-x)    Each market surveillance authority for high-risk AI systems listed in point 1 of Annex III insofar as these systems are used for law enforcement purposes and for purposes listed in points 6, 7 and 8 of Annex III should have effective investigative and corrective powers, including at least the power to obtain access to all personal data that are being processed and to all information necessary for the performance of its tasks. The market surveillance authorities should be able to exercise their powers by acting with complete independence. Any limitations of their access to sensitive operational data under this Regulation should be without prejudice to the powers conferred to them by Directive 2016/680. No exclusion on disclosing data to national data protection authorities under this Regulation should affect the current or future powers of those authorities beyond the scope of this Regulation.

(80x)     The market surveillance authorities of the Member States and the Commission should be able to propose joint activities, including joint investigations, to be conducted by market surveillance authorities or market surveillance authorities jointly with the Commission, that have the aim of promoting compliance, identifying non-compliance, raising awareness and providing guidance in relation to this Regulation with respect to specific categories of high-risk AI systems that are found to present a serious risk across several Member States. Joint activities to promote compliance should be carried out in accordance with Article 9 of the 2019/1020. The AI Office should provide coordination support for joint investigations.

(80y)  It is necessary to clarify the responsibilities and competences on national and Union level as regards AI systems that are built on general-purpose AI models. To avoid overlapping competences, where an AI system is based on a general-purpose AI model and the model and system are provided by the same provider, the supervision should take place at Union level through the AI Office, which should have the powers of a market surveillance authority within the meaning of Regulation (EU) 2019/1020 for this purpose. In all other cases, national market surveillance authorities remain responsible for the supervision of AI systems. However, for general-purpose AI systems that can be used directly by deployers for at least one purpose that is classified as high-risk, market surveillance authorities should cooperate with the AI Office to carry out evaluations of compliance and inform the Board and other market surveillance authorities accordingly. Furthermore, market surveillance authorities should be able to request assistance from the AI Office where the market surveillance authority is unable to conclude an investigation on a high-risk AI system because of its inability to access certain information related to the general-purpose AI model on which the high-risk AI system is built. In such cases, the procedure regarding mutual assistance in cross-border cases in Chapter VI of Regulation (EU) 2019/1020 should apply by analogy.

(80z)      To make best use of the centralised Union expertise and synergies at Union level, the powers of supervision and enforcement of the obligations on providers of general-purpose AI models should be a competence of the Commission. The Commission should entrust the implementation of these tasks to the AI Office, without prejudice to the powers of organisation of the Commission and the division of competences between member States and the Union based on the Treaties. The AI Office should be able to carry out all necessary actions to monitor the effective implementation of this Regulation as regards general-purpose AI models. It should be able to investigate possible infringements of the rules on providers of general-purpose AI models both on its own initiative, following the results of its monitoring activities, or upon request from market surveillance authorities in line with the conditions set out in this Regulation. To support effective monitoring of the AI Office, it should provide for the possibility that downstream providers lodge complaints about possible infringements of the rules on providers of general-purpose AI systems. (80z+1) With a view to complement the governance systems for general-purpose AI models, the scientific panel should support the monitoring activities of the AI Office and may, in certain cases, provide qualified alerts to the AI Office which trigger follow-ups such as investigations. This should be the case where the scientific panel has reason to suspect that a general-purpose AI model poses a concrete and identifiable risk at Union level. Furthermore, this should be the case where the scientific panel has reason to suspect that a general-purpose AI model meets the criteria that would lead to a classification as general-purpose AI model with systemic risk. To equip the scientific panel with the information necessary for the performance of these tasks, there should be a mechanism whereby the scientific panel can request the Commission to require documentation or information from a provider.

(80z+2) The AI Office should be able to take the necessary actions to monitor the effective implementation of and compliance with the obligations for providers of general purpose AI models laid down in this Regulation. The AI Office should be able to investigate possible infringements in accordance with the powers provided for in this Regulation, including by requesting documentation and information, by conducting evaluations, as well as by requesting measures from providers of general purpose AI models. In the conduct of evaluations, in order to make use of independent expertise, the AI Office should be able to involve independent experts to carry out the evaluations on its behalf. Compliance with the obligations should be enforceable, inter alia, through requests to take appropriate measures, including risk mitigation measures in case of identified systemic risks as well as restricting the making available on the market, withdrawing or recalling the model. As a safeguard in case needed beyond the procedural rights provided for in this Regulation, providers of general-purpose AI models should have the procedural rights provided for in Article 18 of Regulation (EU) 2019/1020, which should apply by analogy, without prejudice to more specific procedural rights provided for by this Regulation.

(81) The development of AI systems other than high-risk AI systems in accordance with the requirements of this Regulation may lead to a larger uptake of ethical and trustworthy artificial intelligence in the Union. Providers of non-high-risk AI systems should be encouraged to create codes of conduct, including related governance mechanisms, intended to foster the voluntary application of some or all of the mandatory requirements applicable to high-risk AI systems, adapted in light of the intended purpose of the systems and the lower risk involved and taking into account the available technical solutions and industry best practices such as model and data cards. Providers and, as appropriate, deployers of all AI systems, high-risk or not, and models should also be encouraged to apply on a voluntary basis additional requirements related, for example, to the elements of the European ethic guidelines for trustworthy AI, environmental sustainability, AI literacy measures, inclusive and diverse design and development of AI systems, including attention to vulnerable persons and accessibility to persons with disability, stakeholders’ participation with the involvement as appropriate, of relevant stakeholders such as business and civil society organisations, academia and research organisations, trade unions and consumer protection organisation in the design and development of AI systems, and diversity of the development teams, including gender balance. To ensure that the voluntary codes of conduct are effective, they should be based on clear objectives and key performance indicators to measure the achievement of those objectives. They should be also developed in an inclusive way, as appropriate, with the involvement of relevant stakeholders such as business and civil society organisations, academia and research organisations, trade unions and consumer protection organisation. The Commission may develop initiatives, including of a sectorial nature, to facilitate the lowering of technical barriers hindering cross-border exchange of data for AI development, including on data access infrastructure, semantic and technical interoperability of different types of data.

(82) It is important that AI systems related to products that are not high-risk in accordance with this Regulation and thus are not required to comply with the requirements set out for high- risk AI systems are nevertheless safe when placed on the market or put into service. To contribute to this objective, Regulation (EU) 2023/988 of the European Parliament and of the Council28Regulation (EU) 2023/988 of the European Parliament and of the Council of of 10 May 2023 on general product safety, amending Regulation (EU) No 1025/2012 of the European Parliament and of the Council and Directive (EU) 2020/1828 of the European Parliament and the Council, and repealing Directive 2001/95/EC of the European Parliament and of the Council and Council Directive 87/357/EEC (Text with EEA relevance) (OJ L 135, 23.5.2023, p. 1–51). would apply as a safety net.

(83) In order to ensure trustful and constructive cooperation of competent authorities on Union and national level, all parties involved in the application of this Regulation should respect the confidentiality of information and data obtained in carrying out their tasks, in accordance with Union or national law. They should carry out their tasks and activities in such a manner as to protect, in particular, intellectual property rights, confidential business information and trade secrets, the effective implementation of this Regulation, public and national security interests, the integrity of criminal or administrative proceedings, and the integrity of classified information.

(84) Compliance with this Regulation should be enforceable by means of the imposition of penalties and other enforcement measures. Member States should take all necessary measures to ensure that the provisions of this Regulation are implemented, including by laying down effective, proportionate and dissuasive penalties for their infringement, and in respect of the ne bis in idem principle. In order to strengthen and harmonise administrative penalties for infringement of this Regulation, the upper limits for setting the administrative fines for certain specific infringements should be laid down. When assessing the amount of the fines, Member States should, in each individual case, take into account all relevant circumstances of the specific situation, with due regard in particular to the nature, gravity and duration of the infringement and of its consequences and to the provider’s size, in particular if the provider is an SME including a start-up. The European Data Protection Supervisor should have the power to impose fines on Union institutions, agencies and bodies falling within the scope of this Regulation.

(84a)      Compliance with the obligations on providers of general-purpose AI models imposed under this Regulation should be enforceable among others by means of fines. To that end, appropriate levels of fines should also be laid down for infringement of those obligations, including the failure to comply with measures requested by the Commission in accordance with this Regulation, subject to appropriate limitation periods in accordance with the principle of proportionality. All decisions taken by the Commission under this Regulation are subject to review by the Court of Justice of the European Union in accordance with the TFEU.

(84aa)    Union and national law already provides effective remedies to natural and legal persons whose rights and freedoms are adversely affected by the use of AI systems. Without prejudice to those remedies, any natural or legal person having grounds to consider that there has been an infringement of the provisions of this Regulation should be entitled to lodge a complaint to the relevant market surveillance authority.

(84b)     Affected persons should have the right to request an explanation when a decision is taken by the deployer with the output from certain high-risk systems as provided for in this Regulation as the main basis and which produces legal effects or similarly significantly affects him or her in a way that they consider to adversely impact their health, safety or fundamental rights. This explanation should be a clear and meaningful and should provide a basis for affected persons to exercise their rights. This should not apply to the use of AI systems for which exceptions or restrictions follow from Union or national law and should apply only to the extent this right is not already provided for under Union legislation.

(84c)      Persons acting as ‘whisteblowers’ on the breaches of this Regulation should be afforded the protection guaranteed by Union legislation on the protection of persons who report breaches of law. Therefore, Directive (EU) 2019/1937 should apply to the reporting of breaches of this Regulation and the protection of persons reporting such breaches.

(85) In order to ensure that the regulatory framework can be adapted where necessary, the power to adopt acts in accordance with Article 290 TFEU should be delegated to the Commission to amend the Union harmonisation legislation listed in Annex II, the high-risk AI systems listed in Annex III, the provisions regarding technical documentation listed in Annex IV, the content of the EU declaration of conformity in Annex V, the provisions regarding the conformity assessment procedures in Annex VI and VII, the provisions establishing the high-risk AI systems to which the conformity assessment procedure based on assessment of the quality management system and assessment of the technical documentation should apply, the threshold as well as to supplement benchmarks and indicators in the rules for classification of general-purpose AI models with systemic risk, the criteria for the designation of general-purpose AI models with systemic risk in Annex YY, the technical documentation for providers of general-purpose AI models in Annex VIIIb and the transparency information for providers of general-purpose AI models in Annex VIIIc. It is of particular importance that the Commission carry out appropriate consultations during its preparatory work, including at expert level, and that those consultations be conducted in accordance with the principles laid down in the Interinstitutional Agreement of 13 April 2016 on Better Law-Making1. In particular, to ensure equal participation in the preparation of delegated acts, the European Parliament and the Council receive all documents at the same time as Member States’ experts, and their experts systematically have access to meetings of Commission expert groups dealing with the preparation of delegated acts.

(85a)      Given the rapid technological developments and the required technical expertise in the effective application of this Regulation, the Commission should evaluate and review this Regulation by three years after the date of entry into application and every four years thereafter and report to the European Parliament and the Council. In addition, taking into account the implications for the scope of this Regulation, the Commission should carry out an assessment of the need to amend the list in Annex III and the list of prohibited practices once a year. Moreover, by two years after entry into application and every four years thereafter, the Commission should evaluate and report to the European Parliament and to the Council on the need to amend the high-risk areas in Annex III, the AI systems within the scope of the transparency obligations in Title IV, the effectiveness of the supervision and governance system and the progress on the development of standardisation deliverables on energy efficient development of general-purpose AI models, including the need for further measures or actions. Finally, within two years after the entry into application and every three years thereafter, the Commission should evaluate the impact and effectiveness of voluntary codes of conducts to foster the application of the requirements set out in Title III, Chapter 2, for systems other than high-risk AI systems and possibly other additional requirements for such AI systems.

(86) In order to ensure uniform conditions for the implementation of this Regulation, implementing powers should be conferred on the Commission. Those powers should be exercised in accordance with Regulation (EU) No 182/2011 of the European Parliament and of the Council1.

(87) Since the objective of this Regulation cannot be sufficiently achieved by the Member States and can rather, by reason of the scale or effects of the action, be better achieved at Union level, the Union may adopt measures in accordance with the principle of subsidiarity as set out in Article 5 TEU. In accordance with the principle of proportionality as set out in that Article, this Regulation does not go beyond what is necessary in order to achieve that objective.

(87a)      In order to ensure legal certainty, ensure an appropriate adaptation period for operators and avoid disruption to the market, including by ensuring continuity of the use of AI systems, it is appropriate that this Regulation applies to the high-risk AI systems that have been placed on the market or put into service before the general date of application thereof, only if, from that date, those systems are subject to significant changes in their design or intended purpose. It is appropriate to clarify that, in this respect, the concept of significant change should be understood as equivalent in substance to the notion of substantial modification, which is used with regard only to high-risk AI systems as defined in this Regulation. By way of exception and in light of public accountability, operators of AI systems which are components of the large-scale IT systems established by the legal acts listed in Annex IX and operators of high-risk AI systems that are intended to be used by public authorities should take the necessary steps to comply with the requirements of this Regulation by end of 2030 and by four years after the entry into application respectively.

(87b)     Providers of high-risk AI systems are encouraged to start to comply, on voluntary basis, with the relevant obligations foreseen under this Regulation already during the transitional period.

(88) This Regulation should apply from … [OP – please insert the date established in Art. 85]. However, taking into account the unacceptable risk associated with the use of AI in certain ways, the prohibitions should apply already from … [OP – please insert the date – 6 months after entry into force of this Regulation]. While the full effect of these prohibitions follows with the establishment of the governance and enforcement of this Regulation, anticipating the application of the prohibitions is important to take account of unacceptable risk and has effect on other procedures, such as in civil law. Moreover, the infrastructure related to the governance and the conformity assessment system should be operational before that date, therefore the provisions on notified bodies and governance structure should apply from … [OP – please insert the date – twelve months following the entry into force of this Regulation]. Given the rapid pace of technological advancements and adoption of general-purpose AI models, obligations for providers of general purpose AI models should apply within 12 months from the date of entry into force. Codes of Practice should be ready at the latest 3 months before the entry into application of the relevant provisions, to enable providers to demonstrate compliance in time. The AI Office should ensure that classification rules and procedures are up to date in light of technological developments. In addition, Member States should lay down and notify to the Commission the rules on penalties, including administrative fines, and ensure that they are properly and effectively implemented by the date of application of this Regulation. Therefore, the provisions on penalties should apply from [OP – please insert the date – twelve months following the entry into force of this Regulation].

(89) The European Data Protection Supervisor and the European Data Protection Board were consulted in accordance with Article 42(2) of Regulation (EU) 2018/1725 and delivered an opinion on ”18 June 2021.

TITLE I  GENERAL PROVISIONS

Article 1  Subject matter

1. The purpose of this Regulation is to improve the functioning of the internal market and promoting the uptake of human centric and trustworthy artificial intelligence, while ensuring a high level of protection of health, safety, fundamental rights enshrined in the Charter, including democracy, rule of law and environmental protection against harmful effects of artificial intelligence systems in the Union and supporting innovation.

This Regulation lays down:

(a) harmonised rules for the placing on the market, the putting into service and the use of artificial intelligence systems (‘AI systems’) in the Union;

(b) prohibitions of certain artificial intelligence practices;

(c) specific requirements for high-risk AI systems and obligations for operators of such systems;

(d) harmonised transparency rules for certain AI systems;

(da) harmonised rules for the placing on the market of general-purpose AI models;

(e) rules on market monitoring, market surveillance governance and enforcement;

(ea) measures to support innovation, with a particular focus on SMEs, including start-ups;

Article 2   Scope

1. This Regulation applies to:

(a) providers placing on the market or putting into service AI systems or placing on the market general-purpose AI models in the Union, irrespective of whether those providers are established or who are located within the Union or in a third country;

(b) deployers of AI systems that have their place of establishment or who are located within the Union;

(c) providers and deployers of AI systems that have their place of establishment or who are located in a third country, where the output produced by the system is used in the Union;

(ca)  importers and distributors of AI systems;

(cb) product manufacturers placing on the market or putting into service an AI system together with their product and under their own name or trademark;

(cc) authorised representatives of providers, which are not established in the Union.

(cd) affected persons that are located in the Union.

2. For AI systems classified as high-risk AI systems in accordance with Articles 6(1) and 6(2) related to products covered by Union harmonisation legislation listed in Annex II, section B only Article 84 of this Regulation shall apply. Article 53 shall apply only insofar as the requirements for high-risk AI systems under this Regulation have been integrated under that Union harmonisation legislation.

(d) deleted

(e) deleted

(f) deleted

(g) deleted

(h) deleted

3. This Regulation shall not apply to areas outside the scope of EU law and in any event shall not affect the competences of the Member States concerning national security, regardless of the type of entity entrusted by the Member States to carry out the tasks in relation to those competences.

This Regulation shall not apply to AI systems if and insofar placed on the market, put into service, or used with or without modification of such systems exclusively for military, defence or national security purposes, regardless of the type of entity carrying out those activities.

This Regulation shall not apply to AI systems which are not placed on the market or put into service in the Union, where the output is used in the Union exclusively for military, defence or national security purposes, regardless of the type of entity carrying out those activities.

4. This Regulation shall not apply to public authorities in a third country nor to international organisations falling within the scope of this Regulation pursuant to paragraph 1, where those authorities or organisations use AI systems in the framework of international cooperation or agreements for law enforcement and judicial cooperation with the Union or with one or more Member States, under the condition that this third country or international organisations provide adequate safeguards with respect to the protection of fundamental rights and freedoms of individuals;

5. This Regulation shall not affect the application of the provisions on the liability of intermediary service providers set out in Chapter II, Section 4 of Directive 2000/31/EC of the European Parliament and of the Council29Directive 2000/31/EC of the European Parliament and of the Council of 8 June 2000 on certain legal aspects of information society services, in particular electronic commerce, in the Internal Market (‘Directive on electronic commerce’) (OJ L 178, 17.7.2000, p. 1). [as to be replaced by the corresponding provisions of the Digital Services Act]

5a.         This Regulation shall not apply to AI systems and models, including their output, specifically developed and put into service for the sole purpose of scientific research and development.

5a.         Union law on the protection of personal data, privacy and the confidentiality of communications applies to personal data processed in connection with the rights and obligations laid down in this Regulation. This Regulation shall not affect Regulations (EU) 2016/679 and (EU) 2018/1725 and Directives 2002/58/EC and (EU) 2016/680, without prejudice to arrangements provided for in Article 10(5) and Article 54 of this Regulation;

5b.         This Regulation shall not apply to any research, testing and development activity regarding AI systems or models prior to being placed on the market or put into service; those activities shall be conducted respecting applicable Union law. The testing in real world conditions shall not be covered by this exemption.

5b.         This Regulation is without prejudice to the rules laid down by other Union legal acts related to consumer protection and product safety.

5c.         This Regulation shall not apply to obligations of deployers who are natural persons using AI systems in the course of a purely personal non-professional activity.

5e.         This Regulation shall not preclude Member States or the Union from maintaining or introducing laws, regulations or administrative provisions which are more favourable to workers in terms of protecting their rights in respect of the use of AI systems by employers, or to encourage or allow the application of collective agreements which are more favourable to workers.

5g.         The obligations laid down in this Regulation shall not apply to AI systems released under free and open source licences unless they are placed on the market or put into service as high-risk AI systems or an AI system that falls under Title II and IV.

(1) An AI system is a machine-based system designed to operate with varying levels of autonomy and that may exhibit adaptiveness after deployment and that, for explicit or implicit objectives, infers, from the input it receives, how to generate outputs such as predictions, content, recommendations, or decisions that can influence physical or virtual environments. .

(1a) ‘risk’ means the combination of the probability of an occurrence of harm and the severity of that harm;

(2) ‘provider’ means a natural or legal person, public authority, agency or other body that develops an AI system or a general purpose AI model or that has an AI system or a general purpose AI model developed and places them on the market or puts the system into service under its own name or trademark, whether for payment or free of charge;

(4) ‘deployer means any natural or legal person, public authority, agency or other body using an AI system under its authority except where the AI system is used in the course of a personal non-professional activity;

(5) ‘authorised representative’ means any natural or legal person located or established in the Union who has received and accepted a written mandate from a provider of an AI system or a general-purpose AI model to, respectively, perform and carry out on its behalf the obligations and procedures established by this Regulation;

(6) ‘importer’ means any natural or legal person located or established in the Union that places on the market an AI system that bears the name or trademark of a natural or legal person established outside the Union;

(7) ‘distributor’ means any natural or legal person in the supply chain, other than the provider or the importer, that makes an AI system available on the Union market;

(8) ‘operator’ means the provider, the product manufacturer, the deployer, the authorised representative, the importer or the distributor;

(9) ‘placing on the market’ means the first making available of an AI system or a general purpose AI model on the Union market;

(10) ‘making available on the market’ means any supply of an AI system or a general purpose AI model for distribution or use on the Union market in the course of a commercial activity, whether in return for payment or free of charge;

(11) ‘putting into service’ means the supply of an AI system for first use directly to the deployer or for own use in the Union for its intended purpose;

(12) ‘intended purpose’ means the use for which an AI system is intended by the provider, including the specific context and conditions of use, as specified in the information supplied by the provider in the instructions for use, promotional or sales materials and statements, as well as in the technical documentation;

(13) ‘reasonably foreseeable misuse’ means the use of an AI system in a way that is not in accordance with its intended purpose, but which may result from reasonably foreseeable human behaviour or interaction with other systems, including other AI systems;

(14) ‘safety component of a product or system’ means a component of a product or of a system which fulfils a safety function for that product or system, or the failure or malfunctioning of which endangers the health and safety of persons or property;

(15) ‘instructions for use’ means the information provided by the provider to inform the user of in particular an AI system’s intended purpose and proper use;

(16) ‘recall of an AI system’ means any measure aimed at achieving the return to the provider or taking it out of service or disabling the use of an AI system made available to deployers;

(17) ‘withdrawal of an AI system’ means any measure aimed at preventing an AI system in the supply chain being made available on the market;

(18) ‘performance of an AI system’ means the ability of an AI system to achieve its intended purpose;

(19) ‘notifying authority’ means the national authority responsible for setting up and carrying out the necessary procedures for the assessment, designation and notification of conformity assessment bodies and for their monitoring;

(20) ‘conformity assessment’ means the process of demonstrating whether the requirements set out in Title III, Chapter 2 of this Regulation relating to a high-risk AI system have been fulfilled;

(21) ‘conformity assessment body’ means a body that performs third-party conformity assessment activities, including testing, certification and inspection;

(22) ‘notified body’ means a conformity assessment body notified in accordance with this Regulation and other relevant Union harmonisation legislation;

(23) ‘substantial modification’ means a change to the AI system after its placing on the market or putting into service which is not foreseen or planned in the initial conformity assessment by the provider and as a result of which the compliance of the AI system with the requirements set out in Title III, Chapter 2 of this Regulation is affected or results in a modification to the intended purpose for which the AI system has been assessed;

(24) ‘CE marking of conformity’ (CE marking) means a marking by which a provider indicates that an AI system is in conformity with the requirements set out in Title III, Chapter 2 of this Regulation and other applicable Union legislation harmonising the conditions for the marketing of products (‘Union harmonisation legislation’) providing for its affixing;

(25) ‘post-market monitoring system’ means all activities carried out by providers of AI systems to collect and review experience gained from the use of AI systems they place on the market or put into service for the purpose of identifying any need to immediately apply any necessary corrective or preventive actions;

(26) ‘market surveillance authority’ means the national authority carrying out the activities and taking the measures pursuant to Regulation (EU) 2019/1020;

(27) ‘harmonised standard’ means a European standard as defined in Article 2(1)(c) of Regulation (EU) No 1025/2012;

(28) ‘common specification’ means a set of technical specifications, as defined in point 4 of Article 2 of Regulation (EU) No 1025/2012 providing means to comply with certain requirements established under this Regulation;

(29) ‘training data’ means data used for training an AI system through fitting its learnable parameters;

(30) ‘validation data’ means data used for providing an evaluation of the trained AI system and for tuning its non-learnable parameters and its learning process, among other things, in order to prevent underfitting or overfitting; whereas the validation dataset is a separate dataset or part of the training dataset, either as a fixed or variable split;

(31) ‘testing data’ means data used for providing an independent evaluation of the AI system in order to confirm the expected performance of that system before its placing on the market or putting into service;

(32) ‘input data’ means data provided to or directly acquired by an AI system on the basis of which the system produces an output;

(33) ‘biometric data’ means personal data resulting from specific technical processing relating to the physical, physiological or behavioural characteristics of a natural person, such as facial images or dactyloscopic data;

(33a) ‘biometric identification’ means the automated recognition of physical, physiological, behavioural, and psychological human features for the purpose of establishing an individual’s identity by comparing biometric data of that individual to stored biometric data of individuals in a database;

(33c) ‘biometric verification’ means the automated verification of the identity of natural persons by comparing biometric data of an individual to previously provided biometric data (one-to-one verification, including authentication);

(33d) ‘special categories of personal data’ means the categories of personal data referred to in Article 9(1) of Regulation (EU) 2016/679, Article 10 of Directive (EU) 2016/680 and Article 10(1) of Regulation (EU) 2018/1725;

(33e) ‘sensitive operational data’ means operational data related to activities of prevention, detection, investigation and prosecution of criminal offences, the disclosure of which can jeopardise the integrity of criminal proceedings.

(34) ‘emotion recognition system’ means an AI system for the purpose of identifying or inferring emotions or intentions of natural persons on the basis of their biometric data;

(35) ‘biometric categorisation system’ means an AI system for the purpose of assigning natural persons to specific categories on the basis of their biometric data unless ancillary to another commercial service and strictly necessary for objective technical reasons;

(36) ‘remote biometric identification system’ means an AI system for the purpose of identifying natural persons, without their active involvement, typically at a distance through the comparison of a person’s biometric data with the biometric data contained in a reference database;

(37) ‘‘real-time’ remote biometric identification system’ means a remote biometric identification system whereby the capturing of biometric data, the comparison and the identification all occur without a significant delay. This comprises not only instant identification, but also limited short delays in order to avoid circumvention.

(38) ‘‘post’ remote biometric identification system’ means a remote biometric identification system other than a ‘real-time’ remote biometric identification system;

(39) ‘publicly accessible space’ means any publicly or privately owned physical place accessible to an undetermined number of natural persons, regardless of whether certain conditions for access may apply, and regardless of the potential capacity restrictions;

(40) ‘law enforcement authority’ means:

(a) any public authority competent for the prevention, investigation, detection or prosecution of criminal offences or the execution of criminal penalties, including the safeguarding against and the prevention of threats to public security; or

(b) any other body or entity entrusted by Member State law to exercise public authority and public powers for the purposes of the prevention, investigation, detection or prosecution of criminal offences or the execution of criminal penalties, including the safeguarding against and the prevention of threats to public security;

(41) ‘law enforcement’ means activities carried out by law enforcement authorities or on their behalf for the prevention, investigation, detection or prosecution of criminal offences or the execution of criminal penalties, including the safeguarding against and the prevention of threats to public security;

(42) Artificial Intelligence office means the Commission’s function of contributing to the implementation, monitoring and supervision of AI systems and AI governance. References in this Regulation to the Artificial Intelligence office shall be understood as references to the Commission.

(43) ‘national competent authority’ means any of the following: the notifying authority and the market surveillance authority. As regards AI systems put into service or used by EU institutions, agencies, offices and bodies, any reference to national competent authorities or market surveillance authorities in this Regulation shall be understood as referring to the European Data Protection Supervisor;

(44) ‘serious incident’ means any incident or malfunctioning of an AI system that directly or indirectly leads to any of the following:

(a) the death of a person or serious damage to a person’s health;

(b) a serious and irreversible disruption of the management and operation of critical infrastructure.

(ba)  breach of obligations under Union law intended to protect fundamental rights;

(bb) serious damage to property or the environment.

(44a) ‘personal data’ means personal data as defined in Article 4, point (1) of Regulation (EU) 2016/679 ;

(44c) ‘non-personal data’ means data other than personal data as defined in point (1) of Article 4 of Regulation (EU) 2016/679;

(be) ‘profiling’ means any form of automated processing of personal data as defined in point (4) of Article 4 of Regulation (EU) 2016/679; or in the case of law enforcement authorities – in point 4 of Article 3 of Directive (EU) 2016/680 or, in the case of Union institutions, bodies, offices or agencies, in point 5 Article 3 of Regulation (EU) 2018/1725;

(bf) ‘real world testing plan’ means a document that describes the objectives, methodology, geographical, population and temporal scope, monitoring, organisation and conduct of testing in real world conditions;

(44 eb) ‘sandbox plan’ means a document agreed between the participating provider and the competent authority describing the objectives, conditions, timeframe, methodology and requirements for the activities carried out within the sandbox.

(bg) ‘AI regulatory sandbox’ means a concrete and controlled framework set up by a competent authority which offers providers or prospective providers of AI systems the possibility to develop, train, validate and test, where appropriate in real world conditions, an innovative AI system, pursuant to a sandbox plan for a limited time under regulatory supervision.

(bh) ‘AI literacy’ refers to skills, knowledge and understanding that allows providers, users and affected persons, taking into account their respective rights and obligations in the context of this Regulation, to make an informed deployment of AI systems, as well as to gain awareness about the opportunities and risks of AI and possible harm it can cause.

(bi)    ‘testing in real world conditions’ means the temporary testing of an AI system for its intended purpose in real world conditions outside of a laboratory or otherwise simulated environment with a view to gathering reliable and robust data and to assessing and verifying the conformity of the AI system with the requirements of this Regulation; testing in real world conditions shall not be considered as placing the AI system on the market or putting it into service within the meaning of this Regulation, provided that all conditions under Article 53 or Article 54a are fulfilled;

(bj)    ‘subject’ for the purpose of real world testing means a natural person who participates in testing in real world conditions;

(bk) ‘informed consent’ means a subject’s freely given, specific, unambiguous and voluntary expression of his or her willingness to participate in a particular testing in real world conditions, after having been informed of all aspects of the testing that are relevant to the subject’s decision to participate;

(bl)    “deep fake” means AI generated or manipulated image, audio or video content that resembles existing persons, objects, places or other entities or events and would falsely appear to a person to be authentic or truthful

(44e) ‘widespread infringement’ means any act or omission contrary to Union law that protects the interest of individuals:

(a) which has harmed or is likely to harm the collective interests of individuals residing in at least two Member States other than the Member State, in which:

(i) the act or omission originated or took place;

(ii) the provider concerned, or, where applicable, its authorised representative is established; or,

(iii) the deployer is established, when the infringement is committed by the deployer;

(b) which protects the interests of individuals, that have caused, cause or are likely to cause harm to the collective interests of individuals and that have common features, including the same unlawful practice, the same interest being infringed and that are occurring concurrently, committed by the same operator, in at least three Member States;

(44h) ‘critical infrastructure’ means an asset, a facility, equipment, a network or a system, or a part of thereof, which is necessary for the provision of an essential service within the meaning of Article 2(4) of Directive (EU) 2022/2557;

(44b) ‘general purpose AI model’ means an AI model, including when trained with a large amount of data using self-supervision at scale, that displays significant generality and is capable to competently perform a wide range of distinct tasks regardless of the way the model is placed on the market and that can be integrated into a variety of downstream systems or applications. This does not cover AI models that are used before release on the market for research, development and prototyping activities.

(44c) ‘high-impact capabilities’ in general purpose AI models means capabilities that match or exceed the capabilities recorded in the most advanced general purpose AI models.

(44d) ‘systemic risk at Union level’ means a risk that is specific to the high-impact capabilities of general-purpose AI models, having a significant impact on the internal market due to its reach, and with actual or reasonably foreseeable negative effects on public health, safety, public security, fundamental rights, or the society as a whole, that can be propagated at scale across the value chain.

(44e) ‘general-purpose AI system’ means an AI system which is based on a general- purpose AI model , that has the capability to serve a variety of purposes, both for direct use as well as for integration in other AI systems;

(44f) ’floating-point operation’ means any mathematical operation or assignment involving floating-point numbers, which are a subset of the real numbers typically represented on computers by an integer of fixed precision scaled by an integer exponent of a fixed base.

(44g) ‘downstream provider’ means a provider of an AI system, including a general- purpose AI system, which integrates an AI model, regardless of whether the model is provided by themselves and vertically integrated or provided by another entity based on contractual relations.

Article 4b   AI literacy

Providers and deployers of AI systems shall take measures to ensure, to their best extent, a sufficient level of AI literacy of their staff and other persons dealing with the operation and use of AI systems on their behalf, taking into account their technical knowledge, experience, education and training and the context the AI systems are to be used in, and considering the persons or groups of persons on which the AI systems are to be used.

TITLE II  PROHIBITED ARTIFICIAL INTELLIGENCE PRACTICES

Article 5    Prohibited Artificial Intelligence Practices

1. The following artificial intelligence practices shall be prohibited:

(a) the placing on the market, putting into service or use of an AI system that deploys subliminal techniques beyond a person’s consciousness or purposefully manipulative or deceptive techniques, with the objective to or the effect of materially distorting a person’s or a group of persons’ behaviour by appreciably impairing the person’s ability to make an informed decision, thereby causing the person to take a decision that that person would not have otherwise taken in a manner that causes or is likely to cause that person, another person or group of persons significant harm;

(b) the placing on the market, putting into service or use of an AI system that exploits any of the vulnerabilities of a person or a specific group of persons due to their age, disability or a specific social or economic situation, with the objective to or the effect of materially distorting the behaviour of that person or a person pertaining to that group in a manner that causes or is reasonably likely to cause that person or another person significant harm

(ba) the placing on the market or putting into service for this specific purpose, or use of biometric categorisation systems that categorise individually natural persons based on their biometric data to deduce or infer their race, political opinions, trade union membership, religious or philosophical beliefs, sex life or sexual orientation. This prohibition does not cover any labelling or filtering of lawfully acquired biometric datasets, such as images, based on biometric data or categorizing of biometric data in the area of law enforcement.

(c) the placing on the market, putting into service or use of AI systems for the evaluation or classification of natural persons or groups thereof over a certain period of time based on their social behaviour or known, inferred or predicted personal or personality characteristics, with the social score leading to either or both of the following:

(i) detrimental or unfavourable treatment of certain natural persons or whole groups thereof in social contexts that are unrelated to the contexts in which the data was originally generated or collected;

(ii) detrimental or unfavourable treatment of certain natural persons or groups thereof that is unjustified or disproportionate to their social behaviour or its gravity;

(d) the use of ‘real-time’ remote biometric identification systems in publicly accessible spaces for the purpose of law enforcement unless and in as far as such use is strictly necessary for one of the following objectives:

(i) the targeted search for specific victims of abduction, trafficking in human beings and sexual exploitation of human beings as well as search for missing persons

(ii) the prevention of a specific, substantial and imminent threat to the life or physical safety of natural persons or a genuine and present or genuine and foreseeable threat of a terrorist attack

(iii) the localisation or identification of a person suspected of having committed a criminal offence, for the purposes of conducting a criminal investigation, prosecution or executing a criminal penalty for offences, referred to in Annex IIa and punishable in the Member State concerned by a custodial sentence or a detention order for a maximum period of at least four years.

This paragraph is without prejudice to the provisions in Article 9 of the GDPR for the processing of biometric data for purposes other than law enforcement.

(da) the placing on the market, putting into service for this specific purpose, or use of an AI system for making risk assessments of natural persons in order to assess or predict the risk of a natural person to commit a criminal offence, based solely on the profiling of a natural person or on assessing their personality traits and characteristics;

This prohibition shall not apply to AI systems used to support the human assessment of the involvement of a person in a criminal activity, which is already based on objective and verifiable facts directly linked to a criminal activity.

(db) the placing on the market, putting into service for this specific purpose, or use of AI systems that create or expand facial recognition databases through the untargeted scraping of facial images from the internet or CCTV footage;

(dc)    the placing on the market, putting into service for this specific purpose, or use of AI systems to infer emotions of a natural person in the areas of workplace and education institutions except in cases where the use of the AI system is intended to be put in place or into the market for medical or safety reasons;

(iiid) deleted

1a.  This Article shall not affect the prohibitions that apply where an artificial intelligence practice infringes other Union law.

2. The use of ‘real-time’ remote biometric identification systems in publicly accessible spaces for the purpose of law enforcement for any of the objectives referred to in paragraph 1 point d) shall only be deployed for the purposes under paragraph 1, point d) to confirm the specifically targeted individual’s identity and it shall take into account the following elements:

(a) the nature of the situation giving rise to the possible use, in particular the seriousness, probability and scale of the harm caused in the absence of the use of the system;

(b) the consequences of the use of the system for the rights and freedoms of all persons concerned, in particular the seriousness, probability and scale of those consequences.

In addition, the use of ‘real-time’ remote biometric identification systems in publicly accessible spaces for the purpose of law enforcement for any of the objectives referred to in paragraph 1 point d) shall comply with necessary and proportionate safeguards and conditions in relation to the use in accordance with national legislations authorizing the use thereof, in particular as regards the temporal, geographic and personal limitations. The use of the ‘real-time’ remote biometric identification system in publicly accessible spaces shall only be authorised if the law enforcement authority has completed a fundamental rights impact assessment as provided for in Article 29a and has registered the system in the database according to Article 51. However, in duly justified cases of urgency, the use of the system may be commenced without the registration, provided that the registration is completed without undue delay.

3. As regards paragraphs 1, point (d) and 2, each use for the purpose of law enforcement of a ‘real-time’ remote biometric identification system in publicly accessible spaces shall be subject to a prior authorisation granted by a judicial authority or an independent administrative authority whose decision is binding of the Member State in which the use is to take place, issued upon a reasoned request and in accordance with the detailed rules of national law referred to in paragraph 4. However, in a duly justified situation of urgency, the use of the system may be commenced without an authorisation provided that, such authorisation shall be requested without undue delay, at the latest within 24 hours. If such authorisation is rejected, its use shall be stopped with immediate effect and all the data, as well as the results and outputs of this use shall be immediately discarded and deleted.

The competent judicial authority or an independent administrative authority whose decision is binding shall only grant the authorisation where it is satisfied, based on objective evidence or clear indications presented to it, that the use of the ‘real-time’ remote biometric identification system at issue is necessary for and proportionate to achieving one of the objectives specified in paragraph 1, point (d), as identified in the request and, in particular, remains limited to what is strictly necessary concerning the period of time as well as geographic and personal scope. In deciding on the request, the competent judicial authority or an independent administrative authority whose decision is binding shall take into account the elements referred to in paragraph 2. It shall be ensured that no decision that produces an adverse legal effect on a person may be taken by the judicial authority or an independent administrative authority whose decision is binding solely based on the output of the remote biometric identification system.

3a.         Without prejudice to paragraph 3, each use of a ‘real-time’ remote biometric identification system in publicly accessible spaces for law enforcement purposes shall be notified to the relevant market surveillance authority and the national data protection authority in accordance with the national rules referred to in paragraph 4. The notification shall as a minimum contain the information specified under paragraph 5 and shall not include sensitive operational data.

4. A Member State may decide to provide for the possibility to fully or partially authorise the use of ‘real-time’ remote biometric identification systems in publicly accessible spaces for the purpose of law enforcement within the limits and under the conditions listed in paragraphs 1, point (d), 2 and 3. Member States concerned shall lay down in their national law the necessary detailed rules for the request, issuance and exercise of, as well as supervision and reporting relating to, the authorisations referred to in paragraph 3. Those rules shall also specify in respect of which of the objectives listed in paragraph 1, point (d), including which of the criminal offences referred to in point (iii) thereof, the competent authorities may be authorised to use those systems for the purpose of law enforcement. Member States shall notify those rules to the Commission at the latest 30 days following the adoption thereof.

Member States may introduce, in accordance with Union law, more restrictive laws on the use of remote biometric identification systems.

5. National market surveillance authorities and the national data protection authorities of Member States that have been notified of the use of ‘real-time’ remote biometric identification systems in publicly accessible spaces for law enforcement purposes pursuant to paragraph 3a shall submit to the Commission annual reports on such use. For that purpose, the Commission shall provide Member States and national market surveillance and data protection authorities with a template, including information on the number of the decisions taken by competent judicial authorities or an independent administrative authority whose decision is binding upon requests for authorisations in accordance with paragraph 3 and their result.

6. The Commission shall publish annual reports on the use of ‘real-time’ remote biometric identification systems in publicly accessible spaces for law enforcement purposes based on aggregated data in Member States based on the annual reports referred to in paragraph 5, which shall not include sensitive operational data of the related law enforcement activities.

TITLE III  HIGH-RISK AI SYSTEM

Article 6    Classification rules for high-risk AI systems

1. Irrespective of whether an AI system is placed on the market or put into service independently from the products referred to in points (a) and (b), that AI system shall be considered high-risk where both of the following conditions are fulfilled:

(a) the AI system is intended to be used as a safety component of a product, or the AI system is itself a product, covered by the Union harmonisation legislation listed in Annex II;

(b) the product whose safety component pursuant to point (a) is the AI system, or the AI system itself as a product, is required to undergo a third-party conformity assessment, with a view to the placing on the market or putting into service of that product pursuant to the Union harmonisation legislation listed in Annex II;

2. In addition to the high-risk AI systems referred to in paragraph 1, AI systems referred to in Annex III shall also be considered high-risk.

2a.  By derogation from paragraph 2 AI systems shall not be considered as high risk if they do not pose a significant risk of harm, to the health, safety or fundamental rights of natural persons, including by not materially influencing the outcome of decision making. This shall be the case if one or more of the following criteria are fulfilled:

(a) the AI system is intended to perform a narrow procedural task;

(b) the AI system is intended to improve the result of a previously completed human activity;

(c) the AI system is intended to detect decision-making patterns or deviations from prior decision-making patterns and is not meant to replace or influence the previously completed human assessment, without proper human review; or

(d) the AI system is intended to perform a preparatory task to an assessment relevant for the purpose of the use cases listed in Annex III.

Notwithstanding first subparagraph of this paragraph, an AI system shall always be considered high-risk if the AI system performs profiling of natural persons.

2b.  A provider who considers that an AI system referred to in Annex III is not high-risk shall document its assessment before that system is placed on the market or put into service.

Such provider shall be subject to the registration obligation set out in Article 51(1a). Upon request of national competent authorities, the provider shall provide the documentation of the assessment.

2c.  The Commission shall, after consulting the AI Board, and no later than [18 months] after the entry into force of this Regulation, provide guidelines specifying the practical implementation of this article completed by a comprehensive list of practical examples of high risk and non-high risk use cases on AI systems pursuant to Article 82b.

2d.  The Commission is empowered to adopt delegated acts in accordance with Article 73 to amend the criteria laid down in points a) to d) of the first subparagraph of paragraph 2a.

The Commission may adopt delegated acts adding new criteria to those laid down in points a) to d) of the first subparagraph of paragraph 2a, or modifying them, only where there is concrete and reliable evidence of the existence of AI systems that fall under the scope of Annex III but that do not pose a significant risk of harm to the health, safety and fundamental rights.

The Commission shall adopt delegated acts deleting any of the criteria laid down in the first subparagraph of paragraph 2a where there is concrete and reliable evidence that this is necessary for the purpose of maintaining the level of protection of health, safety and fundamental rights in the Union.

Any amendment to the criteria laid down in points a) to d) set out in the first subparagraph of paragraph 2a shall not decrease the overall level of protection of health, safety and fundamental rights in the Union.

When adopting the delegated acts, the Commission shall ensure consistency with the delegated acts adopted pursuant to Article 7(1) and shall take account of market and technological developments.

Article 7    Amendments to Annex III

1. The Commission is empowered to adopt delegated acts in accordance with Article 73 to amend Annex III by adding or modifying use-cases of high-risk AI systems where both of the following conditions are fulfilled:

(a) the AI systems are intended to be used in any of the areas listed in points 1 to 8 of Annex III;

(b) the AI systems pose a risk of harm to health and safety, or an adverse impact on fundamental rights, and that risk is equivalent to or greater than the risk of harm or of adverse impact posed by the high-risk AI systems already referred to in Annex III.

2. When assessing for the purposes of paragraph 1 whether an AI system poses a risk of harm to the health and safety or a risk of adverse impact on fundamental rights that is equivalent to or greater than the risk of harm posed by the high-risk AI systems already referred to in Annex III, the Commission shall take into account the following criteria:

(a) the intended purpose of the AI system;

(b) the extent to which an AI system has been used or is likely to be used;

(ba) the nature and amount of the data processed and used by the AI system, in particular whether special categories of personal data are processed;

(bb) the extent to which the AI system acts autonomously and the possibility for a human to override a decision or recommendations that may lead to potential harm;

(c) the extent to which the use of an AI system has already caused harm to health and safety, has had an adverse impact on fundamental rights or has given rise to significant concerns in relation to the likelihood of such harm or adverse impact, as demonstrated for example by reports or documented allegations submitted to national competent authorities or by other reports, as appropriate.

(d) the potential extent of such harm or such adverse impact, in particular in terms of its intensity and its ability to affect a plurality of persons or to disproportionately affect a particular group of persons;

(e) the extent to which potentially harmed or adversely impacted persons are dependent on the outcome produced with an AI system, in particular because for practical or legal reasons it is not reasonably possible to opt-out from that outcome;

(f) the extent to which there is an imbalance of power, or the potentially harmed or adversely impacted persons are in a vulnerable position in relation to the user of an AI system, in particular due to status, authority, knowledge, economic or social circumstances, or age;

(g) the extent to which the outcome produced involving an AI system is easily corrigible or reversible, taking into account the technical solutions available to correct or reverse, whereby outcomes having and adverse impact on health, safety, fundamental rights, shall not be considered as easily corrigible or reversible.

(gb) the magnitude and likelihood of benefit of the deployment of the AI system for individuals, groups, or society at large, including possible improvements in product safety;

(h) the extent to which existing Union legislation provides for:

(i) effective measures of redress in relation to the risks posed by an AI system, with the exclusion of claims for damages;

(ii)     effective measures to prevent or substantially minimise those risks.

2a.         The Commission is empowered to adopt delegated acts in accordance with Article 73 to amend the list in Annex III by removing high-risk AI systems where both of the following conditions are fulfilled:

(a) the high-risk AI system(s) concerned no longer pose any significant risks to fundamental rights, health or safety, taking into account the criteria listed in paragraph 2;

(b) the deletion does not decrease the overall level of protection of health, safety and fundamental rights under Union law.

Chapter 2 Requirements for high-risk AI systems

Article 8    Compliance with the requirements

1. High-risk AI systems shall comply with the requirements established in this Chapter, taking into account its intended purpose as well as the generally acknowledged state of the art on AI and AI related technologies. The risk management system referred to in Article 9 shall be taken into account when ensuring compliance with those requirements.

​2.

2a.  Where a product contains an artificial intelligence system, to which the requirements of this Regulation as well as requirements of the Union harmonisation legislation listed in Annex II, Section A apply, providers shall be responsible for ensuring that their product is fully compliant with all applicable requirements required under the Union harmonisation legislation.

In ensuring the compliance of high-risk AI systems referred in paragraph 1 with the requirements set out in Chapter 2 of this Title, and in order to ensure consistency, avoid duplications and minimise additional burdens, providers shall have a choice to integrate, as appropriate, the necessary testing and reporting processes, information and documentation they provide with regard to their product into already existing documentation and procedures required under the Union harmonisation legislation listed in Annex II, Section A.

Article 9    Risk management system

1. A risk management system shall be established, implemented, documented and maintained in relation to high-risk AI systems.

2. The risk management system shall be understood as a continuous iterative process planned and run throughout the entire lifecycle of a high-risk AI system, requiring regular systematic review and updating. It shall comprise the following steps:

(a) identification and analysis of the known and the reasonably foreseeable risks that the high-risk AI system can pose to the health, safety or fundamental rights when the high-risk AI system is used in accordance with its intended purpose ;

(b) estimation and evaluation of the risks that may emerge when the high-risk AI system is used in accordance with its intended purpose and under conditions of reasonably foreseeable misuse;

(c) evaluation of other possibly arising risks based on the analysis of data gathered from the post-market monitoring system referred to in Article 61;

(d) adoption of appropriate and targeted risk management measures designed to address the risks identified pursuant to point a of this paragraph in accordance with the provisions of the following paragraphs.

2a.  The risks referred to in this paragraph shall concern only those which may be reasonably mitigated or eliminated through the development or design of the high-risk AI system, or the provision of adequate technical information.

3. The risk management measures referred to in paragraph 2, point (d) shall give due consideration to the effects and possible interaction resulting from the combined application of the requirements set out in this Chapter 2, with a view to minimising risks more effectively while achieving an appropriate balance in implementing the measures to fulfil those requirements.

4. The risk management measures referred to in paragraph 2, point (d) shall be such that relevant residual risk associated with each hazard as well as the overall residual risk of the high-risk AI systems is judged to be acceptable.

In identifying the most appropriate risk management measures, the following shall be ensured:

(a) elimination or reduction of identified risks and evaluated pursuant to paragraph 2 as far as technically feasible through adequate design and development of the high-risk AI system,

(b) where appropriate, implementation of adequate mitigation and control measures addressing risks that cannot be eliminated;

(c) provision of the required information pursuant to Article 13, referred to in paragraph 2, point (b) of this Article, and, where appropriate, training to deployers.

With a view to eliminating or reducing risks related to the use of the high-risk AI system, due consideration shall be given to the technical knowledge, experience, education, training to be expected by the deployer and the presumable context in which the system is intended to be used.

5. High-risk AI systems shall be tested for the purposes of identifying the most appropriate and targeted risk management measures. Testing shall ensure that high-risk AI systems perform consistently for their intended purpose and they are in compliance with the requirements set out in this Chapter.

6. Testing procedures may include testing in real world conditions in accordance with Article 54a.

7. The testing of the high-risk AI systems shall be performed, as appropriate, at any point in time throughout the development process, and, in any event, prior to the placing on the market or the putting into service. Testing shall be made against prior defined metrics and probabilistic thresholds that are appropriate to the intended purpose of the high-risk AI system.

8. When implementing the risk management system described in paragraphs 1 to 6, providers shall give consideration to whether in view of its intended purpose the high-risk AI system is likely to adversely impact persons under the age of 18 and, as appropriate, other vulnerable groups of people.

9. For providers of high-risk AI systems that are subject to requirements regarding internal risk management processes under relevant sectorial Union law, the aspects described in paragraphs 1 to 8 may be part of or combined with the risk management procedures established pursuant to that law.

Article 10    Data and data governance

1. High-risk AI systems which make use of techniques involving the training of models with data shall be developed on the basis of training, validation and testing data sets that meet the quality criteria referred to in paragraphs 2 to 5 whenever such datasets are used.

2. Training, validation and testing data sets shall be subject to appropriate data governance and management practices appropriate for the intended purpose of the AI system. Those practices shall concern in particular,

(a) the relevant design choices;

(aa) data collection processes and origin of data, and in the case of personal data, the original purpose of data collection;

(b) [deleted]

(c) relevant data preparation processing operations, such as annotation, labelling, cleaning, updating, enrichment and aggregation;

(d) the formulation of assumptions, notably with respect to the information that the data are supposed to measure and represent;

(e) an assessment of the availability, quantity and suitability of the data sets that are needed;

(f) examination in view of possible biases that are likely to affect the health and safety of persons, negatively impact fundamental rights or lead to discrimination prohibited under Union law, especially where data outputs influence inputs for future operations;

(fa)    appropriate measures to detect, prevent and mitigate possible biases identified according to point f;

(g) the identification of relevant data gaps or shortcomings that prevent compliance with this Regulation, and how those gaps and shortcomings can be addressed.

3. Training, validation and testing datasets shall be relevant, sufficiently representative, and to the best extent possible, free of errors and complete in view of the intended purpose. They shall have the appropriate statistical properties, including, where applicable, as regards the persons or groups of persons in relation to whom the high-risk AI system is intended to be used. These characteristics of the data sets may be met at the level of individual data sets or a combination thereof.

4. Datasets shall take into account, to the extent required by the intended purpose, the characteristics or elements that are particular to the specific geographical, contextual, behavioural or functional setting within which the high-risk AI system is intended to be used.

5. To the extent that it is strictly necessary for the purposes of ensuring bias detection and correction in relation to the high-risk AI systems in accordance with the second paragraph, point f and fa, the providers of such systems may exceptionally process special categories of personal data referred to in Article 9(1) of Regulation (EU) 2016/679, Article 10 of Directive (EU) 2016/680 and Article 10(1) of Regulation (EU) 2018/1725, subject to appropriate safeguards for the fundamental rights and freedoms of natural persons. In addition to provisions set out in the Regulation (EU) 2016/679, Directive (EU) 2016/680 and Regulation (EU) 2018/1725, all the following conditions shall apply in order for such processing to occur:

(a) the bias detection and correction cannot be effectively fulfilled by processing other data, including synthetic or anonymised data;

(b) the special categories of personal data processed for the purpose of this paragraph are subject to technical limitations on the re-use of the personal data and state of the art security and privacy-preserving measures, including pseudonymisation;

(c) the special categories of personal data processed for the purpose of this paragraph are subject to measures to ensure that the personal data processed are secured, protected, subject to suitable safeguards, including strict controls and documentation of the access, to avoid misuse and ensure only authorised persons have access to those personal data with appropriate confidentiality obligations;

(d) the special categories of personal data processed for the purpose of this paragraph are not to be transmitted, transferred or otherwise accessed by other parties

(e) the special categories of personal data processed for the purpose of this paragraph are deleted once the bias has been corrected or the personal data has reached the end of its retention period, whatever comes first;

(f) the records of processing activities pursuant to Regulation (EU) 2016/679, Directive (EU) 2016/680 and Regulation (EU) 2018/1725 includes justification why the processing of special categories of personal data was strictly necessary to detect and correct biases and this objective could not be achieved by processing other data.

6. For the development of high-risk AI systems not using techniques involving the training of models, paragraphs 2 to 5 shall apply only to the testing data sets.

Article 11    Technical documentation

1. The technical documentation of a high-risk AI system shall be drawn up before that system is placed on the market or put into service and shall be kept up-to date.

The technical documentation shall be drawn up in such a way to demonstrate that the high- risk AI system complies with the requirements set out in this Chapter and provide national competent authorities and notified bodies with the necessary information in a clear and comprehensive form to assess the compliance of the AI system with those requirements. It shall contain, at a minimum, the elements set out in Annex IV. SMEs, including start-ups, may provide the elements of the technical documentation specified in Annex IV in a simplified manner. For this purpose, the Commission shall establish a simplified technical documentation form targeted at the needs of small and micro enterprises. Where an SME, including start-ups, opts to provide the information required in Annex IV in a simplified manner, it shall use the form referred to in this paragraph. Notified bodies shall accept the form for the purpose of conformity assessment.

2. Where a high-risk AI system related to a product, to which the legal acts listed in Annex II, section A apply, is placed on the market or put into service one single technical documentation shall be drawn up containing all the information set out in paragraph 1 as well as the information required under those legal acts.

3. The Commission is empowered to adopt delegated acts in accordance with Article 73 to amend Annex IV where necessary to ensure that, in the light of technical progress, the technical documentation provides all the necessary information to assess the compliance of the system with the requirements set out in this Chapter.

Article 12   Record-keeping

1. High-risk AI systems shall technically allow for the automatic recording of events (‘logs’) over the duration of the lifetime of the system.

2. In order to ensure a level of traceability of the AI system’s functioning that is appropriate to the intended purpose of the system, logging capabilities shall enable the recording of events relevant for:

2a.   (i) identification of situations that may result in the AI system presenting a risk within the meaning of Article 65(1) or in a substantial modification; (ii) facilitation of the post-market monitoring referred to in Article 61; and (iii) monitoring of the operation of high-risk AI systems referred to in Article 29(4).

3. deleted

4. For high-risk AI systems referred to in paragraph 1, point (a) of Annex III, the logging capabilities shall provide, at a minimum:

(a) recording of the period of each use of the system (start date and time and end date and time of each use);

(b) the reference database against which input data has been checked by the system;

(c) the input data for which the search has led to a match;

(d) the identification of the natural persons involved in the verification of the results, as referred to in Article 14 (5).

Article 13   Transparency and provision of information to deployers

1. High-risk AI systems shall be designed and developed in such a way to ensure that their operation is sufficiently transparent to enable deployers to interpret the system’s output and use it appropriately. An appropriate type and degree of transparency shall be ensured with a view to achieving compliance with the relevant obligations of the provider and deployer set out in Chapter 3 of this Title.

2. High-risk AI systems shall be accompanied by instructions for use in an appropriate digital format or otherwise that include concise, complete, correct and clear information that is relevant, accessible and comprehensible to users.

3. The instructions for use shall contain at least the following information:

(a) the identity and the contact details of the provider and, where applicable, of its authorised representative;

(b) the characteristics, capabilities and limitations of performance of the high-risk AI system, including:

(i) its intended purpose;

(ii) the level of accuracy, including its metrics, robustness and cybersecurity referred to in Article 15 against which the high-risk AI system has been tested and validated and which can be expected, and any known and foreseeable circumstances that may have an impact on that expected level of accuracy, robustness and cybersecurity;

(iii) any known or foreseeable circumstance, related to the use of the high-risk AI system in accordance with its intended purpose or under conditions of reasonably foreseeable misuse, which may lead to risks to the health and safety or fundamental rights referred to in Article 9(2);

(iiia) where applicable, the technical capabilities and characteristics of the AI system to provide information that is relevant to explain its output.

(iv) when appropriate, its performance regarding specific persons or groups of persons on which the system is intended to be used;

(v) when appropriate, specifications for the input data, or any other relevant information in terms of the training, validation and testing data sets used, taking into account the intended purpose of the AI system.

(va) where applicable, information to enable deployers to interpret the system’s output and use it appropriately.

(c) the changes to the high-risk AI system and its performance which have been pre- determined by the provider at the moment of the initial conformity assessment, if any;

(d) the human oversight measures referred to in Article 14, including the technical measures put in place to facilitate the interpretation of the outputs of AI systems by the deployers;

(e) the computational and hardware resources needed, the expected lifetime of the high- risk AI system and any necessary maintenance and care measures, including their frequency, to ensure the proper functioning of that AI system, including as regards software updates;

(ea) where relevant, a description of the mechanisms included within the AI system that allows users to properly collect, store and interpret the logs in accordance with Article 12.

Article 14    Human oversight

1. High-risk AI systems shall be designed and developed in such a way, including with appropriate human-machine interface tools, that they can be effectively overseen by natural persons during the period in which the AI system is in use.

2. Human oversight shall aim at preventing or minimising the risks to health, safety or fundamental rights that may emerge when a high-risk AI system is used in accordance with its intended purpose or under conditions of reasonably foreseeable misuse, in particular when such risks persist notwithstanding the application of other requirements set out in this Chapter.

3. The oversight measures shall be commensurate to the risks, level of autonomy and context of use of the AI system and shall be ensured through either one or all of the following types of measures:

(a) measures identified and built, when technically feasible, into the high-risk AI system by the provider before it is placed on the market or put into service;

(b) measures identified by the provider before placing the high-risk AI system on the market or putting it into service and that are appropriate to be implemented by the user.

(4) For the purpose of implementing paragraphs 1 to 3, the high-risk AI system shall be provided to the user in such a way that natural persons to whom human oversight is assigned are enabled, as appropriate and proportionate to the circumstances:

(a) to properly understand the relevant capacities and limitations of the high-risk AI system and be able to duly monitor its operation, also in view of detecting and addressing anomalies, dysfunctions and unexpected performance;

(b) to remain aware of the possible tendency of automatically relying or over-relying on the output produced by a high-risk AI system (‘automation bias’), in particular for high-risk AI systems used to provide information or recommendations for decisions to be taken by natural persons;

(c) to correctly interpret the high-risk AI system’s output, taking into account for example the interpretation tools and methods available;

(d) to decide, in any particular situation, not to use the high-risk AI system or otherwise disregard, override or reverse the output of the high-risk AI system;

(e) to intervene on the operation of the high-risk AI system or interrupt, the system through a “stop” button or a similar procedure that allows the system to come to a halt in a safe state.

5. For high-risk AI systems referred to in point 1(a) of Annex III, the measures referred to in paragraph 3 shall be such as to ensure that, in addition, no action or decision is taken by the deployer on the basis of the identification resulting from the system unless this has been separately verified and confirmed by at least two natural persons with the necessary competence, training and authority.

The requirement for a separate verification by at least two natural persons shall not apply to high risk AI systems used for the purpose of law enforcement, migration, border control or asylum, in cases where Union or national law considers the application of this requirement to be disproportionate.

Article 15   Accuracy, robustness and cybersecurity

1. High-risk AI systems shall be designed and developed in such a way that they achieve an appropriate level of accuracy, robustness, and cybersecurity, and perform consistently in those respects throughout their lifecycle.

1a.  To address the technical aspects of how to measure the appropriate levels of accuracy and robustness set out in paragraph 1 of this Article and any other relevant performance metrics, the Commission shall, in cooperation with relevant stakeholder and organisations such as metrology and benchmarking authorities, encourage as appropriate, the development of benchmarks and measurement methodologies.

2. The levels of accuracy and the relevant accuracy metrics of high-risk AI systems shall be declared in the accompanying instructions of use.

3. High-risk AI systems shall be as resilient as possible regarding errors, faults or inconsistencies that may occur within the system or the environment in which the system operates, in particular due to their interaction with natural persons or other systems. Technical and organisational measures shall be taken towards this regard.

The robustness of high-risk AI systems may be achieved through technical redundancy solutions, which may include backup or fail-safe plans.

High-risk AI systems that continue to learn after being placed on the market or put into service shall be developed in such a way to eliminate or reduce as far as possible the risk of possibly biased outputs influencing input for future operations (‘feedback loops’) are duly addressed with appropriate mitigation measures.

4. High-risk AI systems shall be resilient as regards to attempts by unauthorised third parties to alter their use, outputs or performance by exploiting the system vulnerabilities.

The technical solutions aimed at ensuring the cybersecurity of high-risk AI systems shall be appropriate to the relevant circumstances and the risks.

The technical solutions to address AI specific vulnerabilities shall include, where appropriate, measures to prevent, detect, respond to, resolve and control for attacks trying to manipulate the training dataset (‘data poisoning’), or pre-trained components used in training (‘model poisoning’) , inputs designed to cause the model to make a mistake (‘adversarial examples’ or ‘model evasion’), confidentiality attacks or model flaws.

Chapter 3 Obligations of Providers and Deployers of High-Risk AI systems and Other Parties   

Article 16   Obligations of providers of high-risk AI systems

Providers of high-risk AI systems shall:

(a) ensure that their high-risk AI systems are compliant with the requirements set out in Chapter 2 of this Title;

(aa) indicate their name, registered trade name or registered trade mark, the address at which they can be contacted on the high-risk AI system or, where that is not possible, on its packaging or its accompanying documentation, as applicable;

(b) have a quality management system in place which complies with Article 17;

(c) keep the documentation referred to in Article 18;

(d) when under their control, keep the logs automatically generated by their high-risk AI systems as referred to in Article 20;

(e) ensure that the high-risk AI system undergoes the relevant conformity assessment procedure as referred to in Article 43, prior to its placing on the market or putting into service;

(ea)  draw up an EU declaration of conformity in accordance with Article 48;

(eb) affix the CE marking to the high-risk AI system to indicate conformity with this Regulation, in accordance with Article 49;

(f) comply with the registration obligations referred to in Article 51(1);

(g) take the necessary corrective actions and provide information as required in Article 21;

(i) Moved above in line 313b

(j) upon a reasoned request of a national competent authority, demonstrate the conformity of the high-risk AI system with the requirements set out in Chapter 2 of this Title.

(ja)    ensure that the high-risk AI system complies with accessibility requirements, in accordance with Directive 2019/882 on accessibility requirements for products and services and Directive 2016/2102 on the accessibility of the websites and mobile applications of public sector bodies.

Article 17    Quality management system

1. Providers of high-risk AI systems shall put a quality management system in place that ensures compliance with this Regulation. That system shall be documented in a systematic and orderly manner in the form of written policies, procedures and instructions, and shall include at least the following aspects:

(a) a strategy for regulatory compliance, including compliance with conformity assessment procedures and procedures for the management of modifications to the high-risk AI system;

(b) techniques, procedures and systematic actions to be used for the design, design control and design verification of the high-risk AI system;

(c) techniques, procedures and systematic actions to be used for the development, quality control and quality assurance of the high-risk AI system;

(d) examination, test and validation procedures to be carried out before, during and after the development of the high-risk AI system, and the frequency with which they have to be carried out

(e) technical specifications, including standards, to be applied and, where the relevant harmonised standards are not applied in full, or do not cover all of the relevant requirements set out in Chapter II of this Title, the means to be used to ensure that the high-risk AI system complies with those requirements;

(f) systems and procedures for data management, including data acquisition, data collection, data analysis, data labelling, data storage, data filtration, data mining, data aggregation, data retention and any other operation regarding the data that is performed before and for the purposes of the placing on the market or putting into service of high-risk AI systems;

(g) the risk management system referred to in Article 9;

(h) the setting-up, implementation and maintenance of a post-market monitoring system, in accordance with Article 61;

(i) procedures related to the reporting of a serious incident in accordance with Article 62;

(j) the handling of communication with national competent authorities, other relevant authorities, including those providing or supporting the access to data, notified bodies, other operators, customers or other interested parties;

(k) systems and procedures for record keeping of all relevant documentation and information;

(l) resource management, including security of supply related measures;

(m) an accountability framework setting out the responsibilities of the management and other staff with regard to all aspects listed in this paragraph.

2. The implementation of aspects referred to in paragraph 1 shall be proportionate to the size of the provider’s organisation. Providers shall in any event respect the degree of rigour and the level of protection required to ensure compliance of their AI systems with this Regulation.

2a.   For providers of high-risk AI systems that are subject to obligations regarding quality management systems or their equivalent function under relevant sectorial Union law, the aspects described in paragraph 1 may be part of the quality management systems pursuant to that law.

3. For providers that are financial institutions subject to requirements regarding their internal governance, arrangements or processes under Union financial services legislation, the obligation to put in place a quality management system with the exception of paragraph 1, points (g), (h) and (i) shall be deemed to be fulfilled by complying with the rules on internal governance arrangements or processes pursuant to the relevant Union financial services legislation. In that context, any harmonised standards referred to in Article 40 of this Regulation shall be taken into account.

Article 18   Documentation keeping

1. The provider shall, for a period ending 10 years after the AI system has been placed on the market or put into service, keep at the disposal of the national competent authorities:

(a) the technical documentation referred to in Article 11;

(b) the documentation concerning the quality management system referred to in Article 17;

(c) the documentation concerning the changes approved by notified bodies where applicable;

(d) the decisions and other documents issued by the notified bodies where applicable;

(e) the EU declaration of conformity referred to in Article 48.

1a.     Each Member State shall determine conditions under which the documentation referred to in paragraph 1 remains at the disposal of the national competent authorities for the period indicated in that paragraph for the cases when a provider or its authorised representative established on its territory goes bankrupt or ceases its activity prior to the end of that period.

2. Providers that are financial institutions subject to requirements regarding their internal governance, arrangements or processes under Union financial services legislation shall maintain the technical documentation as part of the documentation kept under the relevant Union financial services legislation.

Article 19  deleted

1. deleted

2. deleted

Article 20  Automatically generated logs

1. Providers of high-risk AI systems shall keep the logs, referred to in Article 12(1), automatically generated by their high-risk AI systems, to the extent such logs are under their control. Without prejudice to applicable Union or national law, the logs shall be kept for a period appropriate to the intended purpose of the high-risk AI system, of at least 6 months, unless provided otherwise in applicable Union or national law, in particular in Union law on the protection of personal data.

2. Providers that are financial institutions subject to requirements regarding their internal governance, arrangements or processes under Union financial services legislation shall maintain the logs automatically generated by their high-risk AI systems as part of the documentation kept under the relevant financial service legislation.

Article 21  Corrective actions and duty of information

Providers of high-risk AI systems which consider or have reason to consider that a high- risk AI system which they have placed on the market or put into service is not in conformity with this Regulation shall immediately take the necessary corrective actions to bring that system into conformity, to withdraw it, to disable it, or to recall it, as appropriate. They shall inform the distributors of the high-risk AI system in question and, where applicable, the deployers, the authorised representative and importers accordingly.

Where the high-risk AI system presents a risk within the meaning of Article 65(1) and the provider becomes aware of that risk, they shall immediately investigate the causes, in collaboration with the reporting deployer, where applicable, and inform the market surveillance authorities of the Member States in which they made the high-risk AI system available and, where applicable, the notified body that issued a certificate for the high-risk AI system in accordance with Article 44, in particular, of the nature of the non-compliance and of any relevant corrective action taken.

Article 22  deleted

Article 23  Cooperation with competent authorities

1. Providers of high-risk AI systems shall, upon a reasoned request by a competent authority, provide that authority all the information and documentation necessary to demonstrate the conformity of the high-risk AI system with the requirements set out in Chapter 2 of this Title, in a language which can be easily understood by the authority in an official Union language determined by the Member State concerned.

1a   Upon a reasoned request by a national competent authority providers shall also give the requesting national competent authority, as applicable, access to the logs referred to in Article 12(1) automatically generated by the high-risk AI system to the extent such logs are under their control.

(1b)  Any information obtained by a national competent authority pursuant to the provisions of this Article shall be treated in compliance with the confidentiality obligations set out in Article 70.

Article 25  Authorised representatives

1. Prior to making their systems available on the Union market providers established outside the Union shall, by written mandate, appoint an authorised representative which is established in the Union.

1b.   The provider shall enable its authorised representative to perform its tasks under this Regulation.

2. The authorised representative shall perform the tasks specified in the mandate received from the provider. It shall provide a copy of the mandate to the market surveillance authorities upon request, in one of the official languages of the institution of the Union determined by the national competent authority. For the purpose of this Regulation, the mandate shall empower the authorised representative to carry out the following tasks:

(-a)    verify that the EU declaration of conformity and the technical documentation have been drawn up and that an appropriate conformity        assessment procedure has been carried out by the provider;

(a) keep at the disposal of the national competent authorities and national authorities referred to in Article 63(7), for a period ending 10 years after the high-risk AI system has been placed on the market or put into service, the contact details of the provider by which the authorised representative has been appointed, a copy of the EU declaration of conformity, the technical documentation and, if applicable, the certificate issued by the notified body;

(b) provide a national competent authority, upon a reasoned request, with all the information and documentation, including that kept according to point (a), necessary to demonstrate the conformity of a high-risk AI system with the requirements set out in Chapter 2 of this Title, including access to the logs, as referred to in Article 12(1), automatically generated by the high-risk AI system to the extent such logs are under the control of the provider;

(c) cooperate with competent authorities, upon a reasoned request, on any action the latter takes in relation to the high-risk AI system, in particular to reduce and mitigate the risks posed by the high-risk AI system;

(ca) where applicable, comply with the registration obligations referred in Article 51(1), or, if the registration is carried out by the provider itself, ensure that the information referred to in [point 3] of Annex VIII is correct.

The mandate shall empower the authorised representative to be addressed, in addition to or instead of the provider, by the competent authorities, on all issues related to ensuring compliance with this Regulation.

(2b) The authorised representative shall terminate the mandate if it considers or has reason to consider that the provider acts contrary to its obligations under this Regulation. In such a case, it shall also immediately inform the market surveillance authority of the Member State in which it is established, as well as, where applicable, the relevant notified body, about the termination of the mandate and the reasons thereof.

Article 26   Obligations of importers

1. Before placing a high-risk AI system on the market, importers of such system shall ensure that such a system is in conformity with this Regulation by verifying that:

(a) the relevant conformity assessment procedure referred to in Article 43 has been carried out by the provider of that AI system;

(b) the provider has drawn up the technical documentation in accordance with Article 11 and Annex IV;

(c) the system bears the required CE conformity marking and is accompanied by the EU declaration of conformity and instructions of use;

(ca) the provider has appointed an authorised representative in accordance with Article 25(1).

2. Where an importer has sufficient reason to consider that a high-risk AI system is not in conformity with this Regulation, or is falsified, or accompanied by falsified documentation, it shall not place that system on the market until that AI system has been brought into conformity. Where the high-risk AI system presents a risk within the meaning of Article 65(1), the importer shall inform the provider of the AI system , the authorised representatives and the market surveillance authorities to that effect.

3. Importers shall indicate their name, registered trade name or registered trade mark, and the address at which they can be contacted on the high-risk AI system and on its packaging or its accompanying documentation, where applicable.

4. Importers shall ensure that, while a high-risk AI system is under their responsibility, where applicable, storage or transport conditions do not jeopardise its compliance with the requirements set out in Chapter 2 of this Title.

4a.   Importers shall keep, for a period ending 10 years after the AI system has been placed on the market or put into service, a copy of the certificate issued by the notified body, where applicable, of the instructions for use and of the EU declaration of conformity.

5. Importers shall provide national competent authorities, upon a reasoned request, with all the necessary information and documentation including that kept in accordance with paragraph 4a to demonstrate the conformity of a high-risk AI system with the requirements set out in Chapter 2 of this Title in a language which can be easily understood by them. To this purpose they shall also ensure that the technical documentation can be made available to those authorities.

5a.   Importers shall cooperate with national competent authorities on any action those authorities take, in particular to reduce and mitigate the risks posed by the high-risk AI system.

Article 27   Obligations of distributors

1. Before making a high-risk AI system available on the market, distributors shall verify that the high-risk AI system bears the required CE conformity marking, that it is accompanied by a copy of EU declaration of conformity and instruction of use, and that the provider and the importer of the system, as applicable, have complied with their obligations set out in Article 16, point (aa) and (b) and 26(3) respectively.

2. Where a distributor considers or has reason to consider, on the basis of the information in its possession, that a high-risk AI system is not in conformity with the requirements set out in Chapter 2 of this Title, it shall not make the high-risk AI system available on the market until that system has been brought into conformity with those requirements. Furthermore, where the system presents a risk within the meaning of Article 65(1), the distributor shall inform the provider or the importer of the system, as applicable, to that effect.

3. Distributors shall ensure that, while a high-risk AI system is under their responsibility, where applicable, storage or transport conditions do not jeopardise the compliance of the system with the requirements set out in Chapter 2 of this Title.

4. A distributor that considers or has reason to consider, on the basis of the information in its possession, that a high-risk AI system which it has made available on the market is not in conformity with the requirements set out in Chapter 2 of this Title shall take the corrective actions necessary to bring that system into conformity with those requirements, to withdraw it or recall it or shall ensure that the provider, the importer or any relevant operator, as appropriate, takes those corrective actions. Where the high-risk AI system presents a risk within the meaning of Article 65(1), the distributor shall immediately inform the provider or importer of the system and the national competent authorities of the Member States in which it has made the product available to that effect, giving details, in particular, of the non-compliance and of any corrective actions taken.

5. Upon a reasoned request from a national competent authority, distributors of the high- risk AI system shall provide that authority with all the information and documentation regarding its activities as described in paragraph 1 to 4 necessary to demonstrate the conformity of a high-risk system with the requirements set out in Chapter 2 of this Title.

5a.   Distributors shall cooperate with national competent authorities on any action those authorities take in relation to an AI system, of which they are the distributor, in particular to reduce or mitigate the risk posed by the high-risk AI system.

Article 28   Responsibilities along the AI value chain

1. Any distributor, importer, deployer or other third-party shall be considered a provider of a high-risk AI system for the purposes of this Regulation and shall be subject to the obligations of the provider under Article 16, in any of the following circumstances:

(a) they put their name or trademark on a high-risk AI system already placed on the market or put into service, without prejudice to contractual arrangements stipulating that the obligations are allocated otherwise.

(b) they make a substantial modification to a high-risk AI system that has already been placed on the market or has already been put into service and in a way that it remains a high-risk AI system in accordance with Article 6;

(ba) they modify the intended purpose of an AI system, including a general purpose AI system, which has not been classified as high-risk and has already been placed on the market or put into service in such manner that the AI system becomes a high risk AI system in accordance with Article 6

(c) deleted

2. Where the circumstances referred to in paragraph 1, point (a) to (ba) occur, the provider that initially placed the AI system on the market or put it into service shall no longer be considered a provider of that specific AI system for the purposes of this Regulation. This former provider shall closely cooperate and shall make available the necessary information and provide the reasonably expected technical access and other assistance that are required for the fulfilment of the obligations set out in this Regulation, in particular regarding the compliance with the conformity assessment of high-risk AI systems.

This paragraph shall not apply in the cases where the former provider has expressly excluded the change of its system into a high-risk system and therefore the obligation to hand over the documentation.

2a.    For high-risk AI systems that are safety components of products to which the legal acts listed in Annex II, section A apply, the manufacturer of those products shall be considered the provider of the high-risk AI system and shall be subject to the obligations under Article 16 under either of the following scenarios:

(i) the high-risk AI system is placed on the market together with the product under the name or trademark of the product manufacturer; (ii) the high-risk AI system is put into service under the the name or trademark of the product manufacturer after the product has been placed on the market.

2b. The provider of a high risk AI system and the third party that supplies an AI system, tools, services, components, or processes that are used or integrated in a high-risk AI system shall, by written agreement, specify the necessary information, capabilities, technical access and other assistance based on the generally acknowledged state of the art, in order to enable the provider of the high risk AI system to fully comply with the obligations set out in this Regulation. This obligation shall not apply to third parties making accessible to the public tools, services, processes, or AI components other than general-purpose AI models under a free and open licence.

The AI Office may develop and recommend voluntary model contractual terms between providers of high-risk AI systems and third parties that supply tools, services, components or processes that are used or integrated in high-risk AI systems.

When developing voluntary model contractual terms, the AI Office shall take into account possible contractual requirements applicable in specific sectors or business cases. The model contractual terms shall be published and be available free of charge in an easily usable electronic format.

2b.    Paragraphs 2 and 2a are without prejudice to the need to respect and protect intellectual property rights and confidential business information or trade secrets in accordance with Union and national law.

Article 29   Obligations of deployers of high-risk AI systems

1. Deployers of high-risk AI systems shall take appropriate technical and organisational measures to ensure they use such systems in accordance with the instructions of use accompanying the systems, pursuant to paragraphs 2 and 5 of this Article.

1a.    Deployers shall assign human oversight to natural persons who have the necessary competence, training and authority, as well as the necessary support.

1a.    To the extent deployers exercise control over the high-risk AI system, they shall ensure that the natural persons assigned to ensure human oversight of the high-risk AI systems have the necessary competence, training and authority as well as the necessary support

2. The obligations in paragraph 1 and 1a, are without prejudice to other deployer obligations under Union or national law and to the deployer’s discretion in organising its own resources and activities for the purpose of implementing the human oversight measures indicated by the provider.

3. Without prejudice to paragraph 1 and 1a, to the extent the deployer exercises control over the input data, that deployer shall ensure that input data is relevant and sufficiently representative in view of the intended purpose of the high-risk AI system.

4. Deployers shall monitor the operation of the high-risk AI system on the basis of the instructions of use and when relevant, inform providers in accordance with Article 61. When they have reasons to consider that the use in accordance with the instructions of use may result in the AI system presenting a risk within the meaning of Article 65(1) they shall, without undue delay, inform the provider or distributor and relevant market surveillance authority and suspend the use of the system. They shall also immediately inform first the provider, and then the importer or distributor and relevant market surveillance authorities when they have identified any serious incident If the deployer is not able to reach the provider, Article 62 shall apply mutatis mutandis. This obligation shall not cover sensitive operational data of users of AI systems which are law enforcement authorities.

For deployers that are financial institutions subject to requirements regarding their internal governance, arrangements or processes under Union financial services legislation, the monitoring obligation set out in the first subparagraph shall be deemed to be fulfilled by complying with the rules on internal governance arrangements, processes and mechanisms pursuant to the relevant financial service legislation.

5. Deployers of high-risk AI systems shall keep the logs automatically generated by that high-risk AI system to the extent such logs are under their control for a period appropriate to the intended purpose of the high-risk AI system, of at least six months, unless provided otherwise in applicable Union or national law, in particular in Union law on the protection of personal data.

Deployers that are financial institutions subject to requirements regarding their internal governance, arrangements or processes under Union financial services legislation shall maintain the logs as part of the documentation kept pursuant to the relevant Union financial service legislation.

(a) Prior to putting into service or use a high-risk AI system at the workplace, deployers who are employers shall inform workers representatives and the affected workers that they will be subject to the system. This information shall be provided, where applicable, in accordance with the rules and procedures laid down in Union and national law and practice on information of workers and their representatives.

(b) Deployers of high-risk AI systems that are public authorities or Union institutions, bodies, offices and agencies shall comply with the registration obligations referred to in Article 51. When they find that the system that they envisage to use has not been registered in the EU database referred to in Article 60 they shall not use that system and shall inform the provider or the distributor.

(c) Deployers of high-risk AI systems that are public authorities, including Union institutions, bodies, offices and agencies referred to in Article 51(1a)(b) shall comply with the registration obligations referred to in Article 51.

6. Where applicable, deployers of high-risk AI systems shall use the information provided under Article 13 to comply with their obligation to carry out a data protection impact assessment under Article 35 of Regulation (EU) 2016/679 or Article 27 of Directive (EU) 2016/680,

6a.    Without prejudice to Directive (EU) 2016/680, in the framework of an investigation for the targeted search of a person convicted or suspected of having committed a criminal offence, the deployer of an AI system for post-remote biometric identification shall request an authorisation, prior, or without undue delay and no later than 48hours, by a judicial authority or an administrative authority whose decision is binding and subject to judicial review, for the use of the system, except when the system is used for the initial identification of a potential suspect based on objective and verifiable facts directly linked to the offence. Each use shall be limited to what is strictly necessary for the investigation of a specific criminal offence.

If the requested authorisation provided for in the first subparagraph of this paragraph is rejected, the use of the post remote biometric identification system linked to that authorisation shall be stopped with immediate effect and the personal data linked to the use of the system for which the authorisation was requested shall be deleted.

In any case, such AI system for post remote biometric identification shall not be used for law enforcement purposes in an untargeted way, without any link to a criminal offence, a criminal proceeding, a genuine and present or genuine and foreseeable threat of a criminal offence or the search for a specific missing person.

It shall be ensured that no decision that produces an adverse legal effect on a person may be taken by the law enforcement authorities solely based on the output of these post remote biometric identification systems.

This paragraph is without prejudice to the provisions of Article 10 of the Directive (EU) 2016/680 and Article 9 of the GDPR for the processing of biometric data.

Regardless of the purpose or deployer, each use of these systems shall be documented in the relevant police file and shall be made available to the relevant market surveillance authority and the national data protection authority upon request, excluding the disclosure of sensitive operational data related to law enforcement. This subparagraph shall be without prejudice to the powers conferred by the Directive 2016/680 to supervisory authorities.

Deployers shall, in addition, submit annual reports to the relevant market surveillance and national data protection authorities on the uses of post-remote biometric identification systems, excluding the disclosure of sensitive operational data related to law enforcement. The reports can be aggregated to cover several deployments in one operation.

Member States may introduce, in accordance with Union law, more restrictive laws on the use of post remote biometric identification systems.

6b.         Without prejudice to Article 52, deployers of high-risk AI systems referred to in Annex III that make decisions or assist in making decisions related to natural persons shall inform the natural persons that they are subject to the use of the high-risk AI system. For high risk AI systems used for law enforcement purposes Article 13 of Directive 2016/680 shall apply.

6c.         Deployers shall cooperate with the relevant national competent authorities on any action those authorities take in relation with the high-risk system in order to implement this Regulation.

Article 29a  Fundamental rights impact assessment for high-risk AI systems

1. Prior to deploying a high-risk AI system as defined in Article 6(2) into use, with the exception of AI systems intended to be used in the area listed in point 2 of Annex III, deployers that are bodies governed by public law or private operators providing public services and operators deploying high-risk systems referred to in Annex III, point 5, b) and d) shall perform an assessment of the impact on fundamental rights that the use of the system may produce. For that purpose, deployers shall perform an assessment consisting of:

(a) a description of the deployer’s processes in which the high-risk AI system will be used in line with its intended purpose

(b) a description of the period of time and frequency in which each high-risk AI system is intended to be used

(c) the categories of natural persons and groups likely to be affected by its use in the specific context

(d) the specific risks of harm likely to impact the categories of persons or group of persons identified pursuant point (c), taking into account the information given by the provider pursuant to article 13;

(e) a description of the implementation of human oversight measures, according to the instructions of use;

(f) the measures to be taken in case of the materialization of these risks, including their arrangements for internal governance and complaint mechanisms.

2. The obligation laid down in paragraph 1 applies to the first use of the high-risk AI system. The deployer may, in similar cases, rely on previously conducted fundamental rights impact assessments or existing impact assessments carried out by provider. If, during the use of the high-risk AI system, the deployer considers that any of the factors listed in paragraph 1change are or no longer up to date, the deployer will take the necessary steps to update the information.

3. Once the impact assessment has been performed, the deployer shall notify the market surveillance authority of the results of the assessment, submitting the filled template referred to in paragraph 5 as a part of the notification. In the case referred to in Article 47(1), deployers may be exempted from these obligations.

4. If any of the obligations laid down in this article are already met through the data protection impact assessment conducted pursuant to Article 35 of Regulation (EU) 2016/679 or Article 27 of Directive (EU) 2016/680, the fundamental rights impact assessment referred to in paragraph 1 shall be conducted in conjunction with that data protection impact assessment.

5. The AI Office shall develop a template for a questionnaire, including through an automated tool, to facilitate users to implement the obligations of this Article in a simplified manner.

Chapter 4  Notifying Authorities and Notified Bodies 

Article 30  Notifying authorities

1. Each Member State shall designate or establish at least one notifying authority responsible for setting up and carrying out the necessary procedures for the assessment, designation and notification of conformity assessment bodies and for their monitoring. These procedures shall be developed in cooperation between the notifying authorities of all Member States.

2. Member States may decide that the assessment and monitoring referred to in paragraph 1 shall be carried out by a national accreditation body within the meaning of and in accordance with Regulation (EC) No 765/2008.

3. Notifying authorities shall be established, organised and operated in such a way that no conflict of interest arises with conformity assessment bodies and the objectivity and impartiality of their activities are safeguarded.

4. Notifying authorities shall be organised in such a way that decisions relating to the notification of conformity assessment bodies are taken by competent persons different from those who carried out the assessment of those bodies.

5. Notifying authorities shall not offer or provide any activities that conformity assessment bodies perform or any consultancy services on a commercial or competitive basis.

6. Notifying authorities shall safeguard the confidentiality of the information they obtain in accordance with Article 70.

7. Notifying authorities shall have an adequate number of competent personnel at their disposal for the proper performance of their tasks. Competent personnel shall have the necessary expertise, where applicable, for their function, in fields such as information technologies, artificial intelligence and law, including the supervision of fundamental rights.

Article 31   Application of a conformity assessment body for notification

1. Conformity assessment bodies shall submit an application for notification to the notifying authority of the Member State in which they are established.

2. The application for notification shall be accompanied by a description of the conformity assessment activities, the conformity assessment module or modules and the types of AI systems for which the conformity assessment body claims to be competent, as well as by an accreditation certificate, where one exists, issued by a national accreditation body attesting that the conformity assessment body fulfils the requirements laid down in Article 33. Any valid document related to existing designations of the applicant notified body under any other Union harmonisation legislation shall be added.

3. Where the conformity assessment body concerned cannot provide an accreditation certificate, it shall provide the notifying authority with all the documentary evidence necessary for the verification, recognition and regular monitoring of its compliance with the requirements laid down in Article 33. For notified bodies which are designated under any other Union harmonisation legislation, all documents and certificates linked to those designations may be used to support their designation procedure under this Regulation, as appropriate. The notified body shall update the documentation referred to in paragraph 2 and paragraph 3 whenever relevant changes occur, in order to enable the authority responsible for notified bodies to monitor and verify continuous compliance with all the requirements laid down in Article 33.

Article 32  Notification procedure

1. Notifying authorities may only notify conformity assessment bodies which have satisfied the requirements laid down in Article 33.

2. Notifying authorities shall notify the Commission and the other Member States using the electronic notification tool developed and managed by the Commission of each conformity assessment body referred to in paragraph 1.

3. The notification referred to in paragraph 2 shall include full details of the conformity assessment activities, the conformity assessment module or modules and the types of AI systems concerned and the relevant attestation of competence. Where a notification is not based on an accreditation certificate as referred to in Article 31 (2), the notifying authority shall provide the Commission and the other Member States with documentary evidence which attests to the conformity assessment body’s competence and the arrangements in place to ensure that that body will be monitored regularly and will continue to satisfy the requirements laid down in Article 33.

4. The conformity assessment body concerned may perform the activities of a notified body only where no objections are raised by the Commission or the other Member States within two weeks of a notification by a notifying authority where it includes an accreditation certificate referred to in Article 31(2), or within two months of a notification by the notifying authority where it includes documentary evidence referred to in Article 31(3).

4a.     Where objections are raised, the Commission shall without delay enter into consultation with the relevant Member States and the conformity assessment body. In view thereof, the Commission shall decide whether the authorisation is justified or not. The Commission shall address its decision to the Member State concerned and the relevant conformity assessment body.

4b.     Deleted [covered by par.2]

Article 33   Requirements relating to notified bodies

1. A notified body shall be established under national law of a Member State and have legal personality.

2. Notified bodies shall satisfy the organisational, quality management, resources and process requirements that are necessary to fulfil their tasks, as well as suitable cybersecurity requirements.

3. The organisational structure, allocation of responsibilities, reporting lines and operation of notified bodies shall be such as to ensure that there is confidence in the performance by and in the results of the conformity assessment activities that the notified bodies conduct.

4. Notified bodies shall be independent of the provider of a high-risk AI system in relation to which it performs conformity assessment activities. Notified bodies shall also be independent of any other operator having an economic interest in the high-risk AI system that is assessed, as well as of any competitors of the provider. This shall not preclude the use of assessed AI systems that are necessary for the operations of the conformity assessment body or the use of such systems for personal purposes.

4a.     A conformity assessment body, its top-level management and the personnel responsible for carrying out the conformity assessment tasks shall not be directly involved in the design, development, marketing or use of high-risk AI systems, or represent the parties engaged in those activities. They shall not engage in any activity that may conflict with their independence of judgement or integrity in relation to conformity assessment activities for which they are notified. This shall in particular apply to consultancy services.

5. Notified bodies shall be organised and operated so as to safeguard the independence, objectivity and impartiality of their activities. Notified bodies shall document and implement a structure and procedures to safeguard impartiality and to promote and apply the principles of impartiality throughout their organisation, personnel and assessment activities.

6. Notified bodies shall have documented procedures in place ensuring that their personnel, committees, subsidiaries, subcontractors and any associated body or personnel of external bodies respect the confidentiality of the information in accordance with Article 70 which comes into their possession during the performance of conformity assessment activities, except when disclosure is required by law. The staff of notified bodies shall be bound to observe professional secrecy with regard to all information obtained in carrying out their tasks under this Regulation, except in relation to the notifying authorities of the Member State in which their activities are carried out.

7. Notified bodies shall have procedures for the performance of activities which take due account of the size of an undertaking, the sector in which it operates, its structure, the degree of complexity of the AI system in question.

8. Notified bodies shall take out appropriate liability insurance for their conformity assessment activities, unless liability is assumed by the Member State in which they are established in accordance with national law or that Member State is itself directly responsible for the conformity assessment.

9. Notified bodies shall be capable of carrying out all the tasks falling to them under this Regulation with the highest degree of professional integrity and the requisite competence in the specific field, whether those tasks are carried out by notified bodies themselves or on their behalf and under their responsibility.

10. Notified bodies shall have sufficient internal competences to be able to effectively evaluate the tasks conducted by external parties on their behalf. The notified body shall have permanent availability of sufficient administrative, technical, legal and scientific personnel who possess experience and knowledge relating to the relevant types of artificial intelligence systems, data and data computing and to the requirements set out in Chapter 2 of this Title.

11. Notified bodies shall participate in coordination activities as referred to in Article 38. They shall also take part directly or be represented in European standardisation organisations, or ensure that they are aware and up to date in respect of relevant standards.

Article 33a  Presumption of conformity with requirements relating to notified bodies

Where a conformity assessment body demonstrates its conformity with the criteria laid down in the relevant harmonised standards or parts thereof the references of which have been published in the Official Journal of the European Union it shall be presumed to comply with the requirements set out in Article 33 in so far as the applicable harmonised standards cover those requirements.

Article 34   Subsidiaries of and subcontracting by notified bodies

1. Where a notified body subcontracts specific tasks connected with the conformity assessment or has recourse to a subsidiary, it shall ensure that the subcontractor or the subsidiary meets the requirements laid down in Article 33 and shall inform the notifying authority accordingly.

2. Notified bodies shall take full responsibility for the tasks performed by subcontractors or subsidiaries wherever these are established.

3. Activities may be subcontracted or carried out by a subsidiary only with the agreement of the provider. Notified bodies shall make a list of their subsidiaries publicly available.

4. The relevant documents concerning the assessment of the qualifications of the subcontractor or the subsidiary and the work carried out by them under this Regulation shall be kept at the disposal of the notifying authority for a period of 5 years from the termination date of the subcontracting activity.

Article 34a   Operational obligations of notified bodies

1. Notified bodies shall verify the conformity of high-risk AI system in accordance with the conformity assessment procedures referred to in Article 43.

2. Notified bodies shall perform their activities while avoiding unnecessary burdens for providers, and taking due account of the size of an undertaking, the sector in which it operates, its structure and the degree of complexity of the high risk AI system in question. In so doing, the notified body shall nevertheless respect the degree of rigour and the level of protection required for the compliance of the high risk AI system with the requirements of this Regulation. Particular attention shall be paid to minimising administrative burdens and compliance costs for micro and small enterprises as defined in Commission Recommendation 2003/361/EC.

3. Notified bodies shall make available and submit upon request all relevant documentation, including the providers’ documentation, to the notifying authority referred to in Article 30 to allow that authority to conduct its assessment, designation, notification, monitoring activities and to facilitate the assessment outlined in this Chapter.

Article 35  Identification numbers and lists of notified bodies designated under this Regulation

1. The Commission shall assign an identification number to notified bodies. It shall assign a single number, even where a body is notified under several Union acts.

2. The Commission shall make publicly available the list of the bodies notified under this Regulation, including the identification numbers that have been assigned to them and the activities for which they have been notified. The Commission shall ensure that the list is kept up to date.

Article 36   Changes to notifications

-1.  The notifying authority shall notify the Commission and the other Member States of any relevant changes to the notification of a notified body via the electronic notification tool referred to in Article 32(2).

-1a.   The procedures described in Article 31 and 32 shall apply to extensions of the scope of the notification. For changes to the notification other than extensions of its scope, the procedures laid down in the following paragraphs shall apply.

Where a notified body decides to cease its conformity assessment activities it shall inform the notifying authority and the providers concerned as soon as possible and in the case of a planned cessation one year before ceasing its activities. The certificates may remain valid for a temporary period of nine months after cessation of the notified body’s activities on condition that another notified body has confirmed in writing that it will assume responsibilities for the AI systems covered by those certificates. The new notified body shall complete a full assessment of the AI systems affected by the end of that period before issuing new certificates for those systems. Where the notified body has ceased its activity, the notifying authority shall withdraw the designation.

2. Where a notifying authority has sufficient reasons to consider that a notified body no longer meets the requirements laid down in Article 33, or that it is failing to fulfil its obligations, the notifying authority shall without delay investigate the matter with the utmost diligence. In that context, it shall inform the notified body concerned about the objections raised and give it the possibility to make its views known. If the notifying authority comes to the conclusion that the notified body no longer meets the requirements laid down in Article 33 or that it is failing to fulfil its obligations, it shall restrict, suspend or withdraw notification as appropriate, depending on the seriousness of the failure to meet those requirements or fulfil those obligations. It shall immediately inform the Commission and the other Member States accordingly.

2a.         Where its designation has been suspended, restricted, or fully or partially withdrawn, the notified body shall inform the manufacturers concerned at the latest within 10 days.

2b.         In the event of restriction, suspension or withdrawal of a notification, the notifying authority shall take appropriate steps to ensure that the files of the notified body concerned are kept and make them available to notifying authorities in other Member States and to market surveillance authorities at their request.

2c.         In the event of restriction, suspension or withdrawal of a designation, the notifying authority shall:

(a) assess the impact on the certificates issued by the notified body;

(b) submit a report on its findings to the Commission and the other Member States within three months of having notified the changes to the notification;

(c) require the notified body to suspend or withdraw, within a reasonable period of time determined by the authority, any certificates which were unduly issued in order to ensure the conformity of AI systems on the market;

(d) inform the Commission and the Member States about certificates of which it has required their suspension or withdrawal;

(e) provide the national competent authorities of the Member State in which the provider has its registered place of business with all relevant information about the certificates for which it has required suspension or withdrawal. That competent authority shall take the appropriate measures, where necessary, to avoid a potential risk to health, safety or fundamental rights.

2d.         With the exception of certificates unduly issued, and where a notification has been suspended or restricted, the certificates shall remain valid in the following circumstances:

(a) the notifying authority has confirmed, within one month of the suspension or restriction, that there is no risk to health, safety or fundamental rights in relation to certificates affected by the suspension or restriction, and the notifying authority has outlined a timeline and actions anticipated to remedy the suspension or restriction; or

(b) the notifying authority has confirmed that no certificates relevant to the suspension will be issued, amended or re-issued during the course of the suspension or restriction, and states whether the notified body has the capability of continuing to monitor and remain responsible for existing certificates issued for the period of the suspension or restriction. In the event that the authority responsible for notified bodies determines that the notified body does not have the capability to support existing certificates issued, the provider shall provide to the national competent authorities of the Member State in which the provider of the system covered by the certificate has its registered place of business, within three months of the suspension or restriction, a written confirmation that another qualified notified body is temporarily assuming the functions of the notified body to monitor and remain responsible for the certificates during the period of suspension or restriction.

2e.         With the exception of certificates unduly issued, and where a designation has been withdrawn, the certificates shall remain valid for a period of nine months in the following circumstances:

(a) where the national competent authority of the Member State in which the provider of the AI system covered by the certificate has its registered place of business has confirmed that there is no risk to health, safety and fundamental rights associated with the systems in question; and

(b) another notified body has confirmed in writing that it will assume immediate responsibilities for those systems and will have completed assessment of them within twelve months of the withdrawal of the designation.

In the circumstances referred to in the first subparagraph, the national competent authority of the Member State in which the provider of the system covered by the certificate has its place of business may extend the provisional validity of the certificates for further periods of three months, which altogether shall not exceed twelve months.

2f.          The national competent authority or the notified body assuming the functions of the notified body affected by the change of notification shall immediately inform the Commission, the other Member States and the other notified bodies thereof.

Article 37   Challenge to the competence of notified bodies

1. The Commission shall, where necessary, investigate all cases where there are reasons to doubt the competence of a notified body or the continued fulfilment by a notified body of the requirements laid down in Article 33 and their applicable responsibilities.

2. The Notifying authority shall provide the Commission, on request, with all relevant information relating to the notification or the maintenance of the competence of the notified body concerned.

3. The Commission shall ensure that all sensitive information obtained in the course of its investigations pursuant to this Article is treated confidentially in accordance with Article 70.

4. Where the Commission ascertains that a notified body does not meet or no longer meets the requirements for its notification, it shall inform -the notifying Member State accordingly and request it to take the necessary corrective measures, including suspension or withdrawal of the notification if necessary. Where the Member State fails to take the necessary corrective measures, the Commission may, by means of implementing acts, suspend, restrict or withdraw the designation. That implementing act shall be adopted in accordance with the examination procedure referred to in Article 74(2).

Article 38   Coordination of notified bodies

1. The Commission shall ensure that, with regard to high-risk AI systems, appropriate coordination and cooperation between notified bodies active in the conformity assessment procedures pursuant to this Regulation are put in place and properly operated in the form of a sectoral group of notified bodies.

2. The notifying authority shall ensure that the bodies notified by them participate in the work of that group, directly or by means of designated representatives.

2a.   The Commission shall provide for the exchange of knowledge and best practices between the Member States’ notifying authorities.

Article 39   Conformity assessment bodies of third countries

Conformity assessment bodies established under the law of a third country with which the Union has concluded an agreement may be authorised to carry out the activities of notified Bodies under this Regulation, provided that they meet the requirements in Article 33 or they ensure an equivalent level of compliance.

Chapter 5  STANDARDS, CONFORMITY ASSESSMENT, CERTIFICATES, REGISTRATION

Article 40   Harmonised standards and standardisation deliverables

High-risk AI systems which are in conformity with harmonised standards or parts thereof the references of which have been published in the Official Journal of the European Union in accordance with Regulation (EU) 1025/2012 shall be presumed to be in conformity with the requirements set out in Chapter 2 of this Title or, as applicable, with the requirements set out in [Chapter on GPAI], to the extent those standards cover those requirements.

2.   The Commission shall issue standardisation requests covering all requirements of Title II Chapter III and as applicable [GPAI Chapter] of this Regulation, in accordance with Article 10 of Regulation EU (No)1025/2012 without undue delay. The standardisation request shall also ask for deliverables on reporting and documentation processes to improve AI systems resource performance, such as reduction of energy and other resources consumption of the high-risk AI system during its lifecycle, and on energy efficient development of general-purpose AI models. When preparing standardisation request, the Commission shall consult the Board and relevant stakeholders, including the Advisory Forum.

When issuing a standardisation request to European standardisation organisations, the Commission shall specify that standards have to be consistent, including with the existing and future standards developed in the various sectors for products covered by the existing Union safety legislation listed in Annex II, clear and aimed at ensuring that AI systems or models placed on the market or put into service in the Union meet the relevant requirements laid down in this Regulation.

The Commission shall request the European standardisation organisations to provide evidence of their best efforts to fulfil the above objectives in accordance with Article 24 of Regulation EU 1025/2012.

1c    The actors involved in the standardisation process shall seek to promote investment and innovation in AI, including through increasing legal certainty, as well as competitiveness and growth of the Union market, and contribute to strengthening global cooperation on standardisation and taking into account existing international standards in the field of AI that are consistent with Union values, fundamental rights and interests, and enhance multi- stakeholder governance ensuring a balanced representation of interests and effective participation of all relevant stakeholders in accordance with Articles 5, 6, and 7 of Regulation (EU) No 1025/2012

Article 41   Common specifications

1. The Commission is empowered to adopt, after consulting the Advisory Forum referred to in Article 58, implementing acts in accordance with the examination procedure referred to in Article 74(2) establishing common specifications for the requirements set out in Chapter 2 of this Title or, as applicable, with requirements set out in Article [GPAI Chapter], for AI systems within the scope of this Regulation, where the following conditions have been fulfilled:

(a) the Commission has requested, pursuant to Article 10(1) of Regulation 1025/2012, one or more European standardisation organisations to draft a harmonised standard for the requirements set out in Chapter 2 of this Title; and (i) the request has not been accepted by any of the European standardisation organisations; or (ii) the harmonised standards addressing that request are not delivered within the deadline set in accordance with article 10(1) of Regulation 1025/2012; or (iii) the relevant harmonised standards insufficiently address fundamental rights concerns; or (iv) the harmonised standards do not comply with the request; and

(b) no reference to harmonised standards covering the requirements referred to in Chapter II of this Title has been published in the Official Journal of the European Union, in accordance with Regulation (EU) No 1025/2012, and no such reference is expected to be published within a reasonable period.

1a. Before preparing a draft implementing act, the Commission shall inform the committee referred to in Article 22 of Regulation EU (No) 1025/2012 that it considers that the conditions in paragraph 1 are fulfilled.

3. High-risk AI systems which are in conformity with the common specifications referred to in paragraph 1, or parts thereof, shall be presumed to be in conformity with the requirements set out in Chapter 2 of this Title, to the extent those common specifications cover those requirements.

3a.    Where a harmonised standard is adopted by a European standardisation organisation and proposed to the Commission for the publication of its reference in the Official Journal of the European Union, the Commission shall assess the harmonised standard in accordance with Regulation (EU) No 1025/2012. When reference of a harmonised standard is published in the Official Journal of the European Union, the Commission shall repeal acts referred to in paragraph 1 and 1b, or parts thereof which cover the same requirements set out in Chapter 2 of this Title.

4. Where providers of high-risk AI systems do not comply with the common specifications referred to in paragraph 1, they shall duly justify that they have adopted technical solutions that meet the requirements referred to in Chapter II to a level at least equivalent thereto.

4b.    When a Member State considers that a common specification does not entirely satisfy the requirements set out in Chapter 2 of this Title, it shall inform the Commission thereof with a detailed explanation and the Commission shall assess that information and, if appropriate, amend the implementing act establishing the common specification in question.

Article 42   Presumption of conformity with certain requirements

1. High-risk AI systems that have been trained and tested on data reflecting the specific geographical, behavioural, contextual or functional setting within which they are intended to be used shall be presumed to be in compliance with the respective requirements set out in Article 10(4).

2. High-risk AI systems that have been certified or for which a statement of conformity has been issued under a cybersecurity scheme pursuant to Regulation (EU) 2019/881 of the European Parliament and of the Council1 and the references of which have been published in the Official Journal of the European Union shall be presumed to be in compliance with the cybersecurity requirements set out in Article 15 of this Regulation in so far as the cybersecurity certificate or statement of conformity or parts thereof cover those requirements.

Article 43   Conformity assessment

1. For high-risk AI systems listed in point 1 of Annex III, where, in demonstrating the compliance of a high-risk AI system with the requirements set out in Chapter 2 of this Title, the provider has applied harmonised standards referred to in Article 40, or, where applicable, common specifications referred to in Article 41, the provider shall opt for one of the following procedures:

(a) the conformity assessment procedure based on internal control referred to in Annex VI; or

(b) the conformity assessment procedure based on assessment of the quality management system and assessment of the technical documentation, with the involvement of a notified body, referred to in Annex VII.

In demonstrating the compliance of a high-risk AI system with the requirements set out in Chapter 2 of this Title, the provider shall follow the conformity assessment procedure set out in Annex VII in the following cases: (a) where harmonised standards referred to in Article 40, do not exist and common specifications referred to in Article 41 are not available; (aa) the provider has not applied or has applied only in part the harmonised standard; (b) where the common specifications referred to in point (a) exist but the provider has not applied them; (c) where one or more of the harmonised standards referred to in point (a) has been published with a restriction and only on the part of the standard that was restricted;

For the purpose of the conformity assessment procedure referred to in Annex VII, the provider may choose any of the notified bodies. However, when the system is intended to be put into service by law enforcement, immigration or asylum authorities as well as EU institutions, bodies or agencies, the market surveillance authority referred to in Article 63(5) or (6), as applicable, shall act as a notified body.

2. For high-risk AI systems referred to in points 2 to 8 of Annex III providers shall follow the conformity assessment procedure based on internal control as referred to in Annex VI, which does not provide for the involvement of a notified body.

3. For high-risk AI systems, to which legal acts listed in Annex II, section A, apply, the provider shall follow the relevant conformity assessment as required under those legal acts. The requirements set out in Chapter 2 of this Title shall apply to those high-risk AI systems and shall be part of that assessment. Points 4.3., 4.4., 4.5. and the fifth paragraph of point 4.6 of Annex VII shall also apply.

For the purpose of that assessment, notified bodies which have been notified under those legal acts shall be entitled to control the conformity of the high-risk AI systems with the requirements set out in Chapter 2 of this Title, provided that the compliance of those notified bodies with requirements laid down in Article 33(4), (9) and (10) has been assessed in the context of the notification procedure under those legal acts.

Where the legal acts listed in Annex II, section A, enable the manufacturer of the product to opt out from a third-party conformity assessment, provided that that manufacturer has applied all harmonised standards covering all the relevant requirements, that manufacturer may make use of that option only if he has also applied harmonised standards or, where applicable, common specifications referred to in Article 41, covering the requirements set out in Chapter 2 of this Title.

4. High-risk AI systems that have already been subject to a conformity assessment procedure shall undergo a new conformity assessment procedure whenever they are substantially modified, regardless of whether the modified system is intended to be further distributed or continues to be used by the current deployer.

For high-risk AI systems that continue to learn after being placed on the market or put into service, changes to the high-risk AI system and its performance that have been pre- determined by the provider at the moment of the initial conformity assessment and are part of the information contained in the technical documentation referred to in point 2(f) of Annex IV, shall not constitute a substantial modification.

5. The Commission is empowered to adopt delegated acts in accordance with Article 73 for the purpose of updating Annexes VI and Annex VII in light of technical progress.

6. The Commission is empowered to adopt delegated acts to amend paragraphs 1 and 2 in order to subject high-risk AI systems referred to in points 2 to 8 of Annex III to the conformity assessment procedure referred to in Annex VII or parts thereof. The Commission shall adopt such delegated acts taking into account the effectiveness of the conformity assessment procedure based on internal control referred to in Annex VI in preventing or minimizing the risks to health and safety and protection of fundamental rights posed by such systems as well as the availability of adequate capacities and resources among notified bodies.

Article 44   Certificates

1. Certificates issued by notified bodies in accordance with Annex VII shall be drawn-up in a language which can be easily understood by the relevant authorities in the Member State in which the notified body is established.

2. Certificates shall be valid for the period they indicate, which shall not exceed five years for AI systems covered by Annex II and four years for AI systems covered by Annex III. On application by the provider, the validity of a certificate may be extended for further periods, each not exceeding five years for AI systems covered by Annex II and four years for AI systems covered by Annex III, based on a re-assessment in accordance with the applicable conformity assessment procedures. Any supplement to a certificate shall remain valid as long as the certificate which it supplements is valid.

3. Where a notified body finds that an AI system no longer meets the requirements set out in Chapter 2 of this Title, it shall, taking account of the principle of proportionality, suspend or withdraw the certificate issued or impose any restrictions on it, unless compliance with those requirements is ensured by appropriate corrective action taken by the provider of the system within an appropriate deadline set by the notified body. The notified body shall give reasons for its decision.

An appeal procedure against decisions of the notified bodies, including on issued conformity certificates, shall be available.

Article 46    Information obligations of notified bodies

1. Notified bodies shall inform the notifying authority of the following

(a) any Union technical documentation assessment certificates, any supplements to those certificates, quality management system approvals issued in accordance with the requirements of Annex VII;

(b) any refusal, restriction, suspension or withdrawal of a Union technical documentation assessment certificate or a quality management system approval issued in accordance with the requirements of Annex VII;

(c) any circumstances affecting the scope of or conditions for notification;

(d) any request for information which they have received from market surveillance authorities regarding conformity assessment activities;

(e) on request, conformity assessment activities performed within the scope of their notification and any other activity performed, including cross-border activities and subcontracting.

2. Each notified body shall inform the other notified bodies of:

(a) quality management system approvals which it has refused, suspended or withdrawn, and, upon request, of quality system approvals which it has issued;

(b) EU technical documentation assessment certificates or any supplements thereto which it has refused, withdrawn, suspended or otherwise restricted, and, upon request, of the certificates and/or supplements thereto which it has issued.

3. Each notified body shall provide the other notified bodies carrying out similar conformity assessment activities covering the same types ofAI systems with relevant information on issues relating to negative and, on request, positive conformity assessment results.

3a.   The obligations referred to in paragraphs 1 to 3 shall be complied with in accordance with Article 70.

Article 47   Derogation from conformity assessment procedure

1. By way of derogation from Article 43 and upon a duly justified request, any market surveillance authority may authorise the placing on the market or putting into service of specific high-risk AI systems within the territory of the Member State concerned, for exceptional reasons of public security or the protection of life and health of persons, environmental protection and the protection of key industrial and infrastructural assets. That authorisation shall be for a limited period of time while the necessary conformity assessment procedures are being carried out, taking into account the exceptional reasons justifying the derogation. The completion of those procedures shall be undertaken without undue delay.

1a.   In a duly justified situation of urgency for exceptional reasons of public security or in case of specific, substantial and imminent threat to the life or physical safety of natural persons, law enforcement authorities or civil protection authorities may put a specific high-risk AI system into service without the authorisation referred to in paragraph 1 provided that such authorisation is requested during or after the use without undue delay, and if such authorisation is rejected, its use shall be stopped with immediate effect and all the results and outputs of this use shall be immediately discarded.

2. The authorisation referred to in paragraph 1 shall be issued only if the market surveillance authority concludes that the high-risk AI system complies with the requirements of Chapter 2 of this Title. The market surveillance authority shall inform the Commission and the other Member States of any authorisation issued pursuant to paragraph 1. This obligation shall not cover sensitive operational data in relation to the activities of law enforcement authorities.

3. Where, within 15 calendar days of receipt of the information referred to in paragraph 2, no objection has been raised by either a Member State or the Commission in respect of an authorisation issued by a market surveillance authority of a Member State in accordance with paragraph 1, that authorisation shall be deemed justified.

4. Where, within 15 calendar days of receipt of the notification referred to in paragraph 2, objections are raised by a Member State against an authorisation issued by a market surveillance authority of another Member State, or where the Commission considers the authorisation to be contrary to Union law or the conclusion of the Member States regarding the compliance of the system as referred to in paragraph 2 to be unfounded, the Commission shall without delay enter into consultation with the relevant Member State; the operator(s) concerned shall be consulted and have the possibility to present their views. In view thereof, the Commission shall decide whether the authorisation is justified or not. The Commission shall address its decision to the Member State concerned and the relevant operator or operators.

5. If the authorisation is considered unjustified, this shall be withdrawn by the market surveillance authority of the Member State concerned.

6. For high-risk AI systems related to products covered by Union harmonisation legislation referred to in Annex II Section A, only the conformity assessment derogation procedures established in that legislation shall apply.

Article 48   EU declaration of conformity

1. The provider shall draw up a written machine readable, physical or electronically signed EU declaration of conformity for each high-risk AI system and keep it at the disposal of the national competent authorities for 10 years after the AI high-risk system has been placed on the market or put into service. The EU declaration of conformity shall identify the high-risk AI system for which it has been drawn up.A copy of the EU declaration of conformity shall be submitted to the relevant national competent authorities upon request.

2. The EU declaration of conformity shall state that the high-risk AI system in question meets the requirements set out in Chapter 2 of this Title. The EU declaration of conformity shall contain the information set out in Annex V and shall be translated into a language that can be easily understood by the national competent authorities of the Member State(s) in which the high-risk AI system is placed on the market or made available.

3. Where high-risk AI systems are subject to other Union harmonisation legislation which also requires an EU declaration of conformity, a single EU declaration of conformity shall be drawn up in respect of all Union legislations applicable to the high-risk AI system. The declaration shall contain all the information required for identification of the Union harmonisation legislation to which the declaration relates.

4. By drawing up the EU declaration of conformity, the provider shall assume responsibility for compliance with the requirements set out in Chapter 2 of this Title. The provider shall keep the EU declaration of conformity up-to-date as appropriate.

5. The Commission shall be empowered to adopt delegated acts in accordance with Article 73 for the purpose of updating the content of the EU declaration of conformity set out in Annex V in order to introduce elements that become necessary in light of technical progress.

Article 49   CE marking of conformity

1. The CE marking of conformity shall be subject to the general principles set out in Article 30 of Regulation (EC) No 765/2008.

1a.    For high-risk AI systems provided digitally, a digital CE marking shall be used, only if it can be easily accessed via the interface from which the AI system is accessed or via an easily accessible machine-readable code or other electronic means.

2. The CE marking shall be affixed visibly, legibly and indelibly for high-risk AI systems. Where that is not possible or not warranted on account of the nature of the high-risk AI system, it shall be affixed to the packaging or to the accompanying documentation, as appropriate.

3. Where applicable, the CE marking shall be followed by the identification number of the notified body responsible for the conformity assessment procedures set out in Article 43. The identification number of the notified body shall be affixed by the body itself or, under its instructions, by the provider or by its authorised representative. The identification number shall also be indicated in any promotional material which mentions that the high- risk AI system fulfils the requirements for CE marking.

3a.         Where high-risk AI systems are subject to other Union law which also provides for the affixing of the CE marking, the CE marking shall indicate that the high-risk AI system also fulfil the requirements of that other law.

Article 50    Moved to Article 18

Article 51   Registration

Before placing on the market or putting into service a high-risk AI system listed in Annex III, with the exception of high risk AI systems referred to in Annex III point 2, the provider or, where applicable, the authorised representative shall register themselves and their system in the EU database referred to in Article 60.

1a. Before placing on the market or putting into service an AI system for which the provider has concluded that it is not high-risk in application of the procedure under Article 6(2a), the provider or, where applicable, the authorised representative shall register themselves and that system in the EU database referred to in Article 60.

1b. Before putting into service or using a high-risk AI system listed in Annex III, with the exception of high-risk AI systems listed in Annex III, point 2, deployers who are public authorities, agencies or bodies or persons acting on their behalf shall register themselves, select the system and register its use in the EU database referred to in Article 60.

1c. For high-risk AI systems referred to Annex III, points 1, 6 and 7 in the areas of law enforcement, migration, asylum and border control management, the registration referred to in paragraphs 1 to 1b shall be done in a secure non-public section of the EU database referred to in Article 60 and include only the following information, as applicable:

  • points 1 to 9 of Annex VIII, section A with the exception of points 5a, 7 and 8
  • points 1 to 3 of Annex VIII, section B
  • points 1 to 9 of Annex VIII, section X with the exception of points 6 and 7 points 1 to 5 of Annex VIIIa with the exception of point 4.

Only the Commission and national authorities referred to in Art. 63 (5) shall have access to these restricted sections of the EU database.

1d. High risk AI systems referred to in Annex III, point 2 shall be registered at national level.

TITLE IV  TRANSPARENCY OBLIGATIONS FOR PROVIDERS AND DEPLOYERS OF CERTAIN AI SYSTEMS AND GPAI MODELS

Article 52   Transparency obligations for providers and users of certain AI systems and GPAI models

1. Providers shall ensure that AI systems intended to directly interact with natural persons are designed and developed in such a way that the concerned natural persons are informed that they are interacting with an AI system, unless this is obvious from the point of view of a natural person who is reasonably well-informed, observant and circumspect, taking into account the circumstances and the context of use. This obligation shall not apply to AI systems authorised by law to detect, prevent, investigate and prosecute criminal offences, subject to appropriate safeguards for the rights and freedoms of third parties unless those systems are available for the public to report a criminal offence.1a. Providers of AI systems, including GPAI systems, generating synthetic audio, image, video or text content, shall ensure the outputs of the AI system are marked in a machine- readable format and detectable as artificially generated or manipulated. Providers shall ensure their technical solutions are effective, interoperable, robust and reliable as far as this is technically feasible, taking into account specificities and limitations of different types of content, costs of implementation and the generally acknowledged state-of-the-art, as may be reflected in relevant technical standards.

This obligation shall not apply to the extent the AI systems perform an assistive function for standard editing or do not substantially alter the input data provided by the deployer or the semantics thereof, or where authorised by law to detect, prevent, investigate and prosecute criminal offences.

2. Deployers of an emotion recognition system or a biometric categorisation system shall inform of the operation of the system the natural persons exposed thereto and process the personal data in accordance with Regulation (EU) 2016/679, Regulation (EU) 2016/1725 and Directive (EU) 2016/280, as applicable. This obligation shall not apply to AI systems used for biometric categorization and emotion recognition, which are permitted by law to detect, prevent and investigate criminal offences, subject to appropriate safeguards for the rights and freedoms of third parties, and in compliance with Union law.

3. Deployers of an AI system that generates or manipulates image, audio or video content constituting a deep fake, shall disclose that the content has been artificially generated or manipulated. This obligation shall not apply where the use is authorised by law to detect, prevent, investigate and prosecute criminal offence. Where the content forms part of an evidently artistic, creative, satirical, fictional analogous work or programme, the transparency obligations set out in this paragraph are limited to disclosure of the existence of such generated or manipulated content in an appropriate manner that does not hamper the display or enjoyment of the work.

Deployers of an AI system that generates or manipulates text which is published with the purpose of informing the public on matters of public interest shall disclose that the text has been artificially generated or manipulated. This obligation shall not apply where the use is authorised by law to detect, prevent, investigate and prosecute criminal offences or where the AI-generated content has undergone a process of human review or editorial control and where a natural or legal person holds editorial responsibility for the publication of the content.

3a.  The information referred to in paragraphs 1 to 3 shall be provided to the concerned natural persons in a clear and distinguishable manner at the latest at the time of the first interaction or exposure. The information shall respect the applicable accessibility requirements.

4. Paragraphs 1, 2 and 3 shall not affect the requirements and obligations set out in Title III of this Regulation and shall be without prejudice to other transparency obligations for users of AI systems laid down in Union or national law.

4a. The AI Office shall encourage and facilitate the drawing up of codes of practice at Union level to facilitate the effective implementation of the obligations regarding the detection and labelling of artificially generated or manipulated content. The Commission is empowered to adopt implementing acts to approve these codes of practice in accordance with the procedure laid down in Article 52e paragraphs 6-8. If it deems the code is not adequate, the Commission is empowered to adopt an implementing act specifying the common rules for the implementation of those obligations in accordance with the examination procedure laid down in Article 73 paragraph 2.

Article 52a Classification of general-purpose AI models as general purpose AI models with systemic risk

1. A general-purpose AI model shall be classified as general-purpose AI model with systemic risk if it meets any of the following criteria:

(a) it has high impact capabilities evaluated on the basis of appropriate technical tools and methodologies, including indicators and benchmarks;

(b) based on a decision of the Commission, ex officio or following a qualified alert by the scientific panel that a general purpose AI model has capabilities or impact equivalent to those of point a).

2. A general-purpose AI model shall be presumed to have high impact capabilities pursuant to point a) of paragraph 1 when the cumulative amount of compute used for its training measured in floating point operations (FLOPs) is greater than 10^25.

3. The Commission shall adopt delegated acts in accordance with Article 73(2) to amend the thresholds listed in the paragraphs above, as well as to supplement benchmarks and indicators in light of evolving technological developments, such as algorithmic improvements or increased hardware efficiency, when necessary, for these thresholds to reflect the state of the art.

Article 52b   Procedure

1. Where a general-purpose AI model meets the requirements referred to in points (a) of Article A(1), the relevant provider shall notify the Commission without delay and in any event within 2 weeks after those requirements are met or it becomes known that these requirements will be met. That notification shall include the information necessary to demonstrate that the relevant requirements have been met. If the Commission becomes aware of a general purpose AI model presenting systemic risks of which it has not been notified, it may decide to designate it as a model with systemic risk.

2. The provider of a general-purpose AI model that meets the requirements referred to in points (a) of Article A(1) may present, with its notification, sufficiently substantiated arguments to demonstrate that, exceptionally, although it meets the said requirements, the general-purpose AI model does not present, due to its specific characteristics, systemic risks and therefore should not be classified as general-purpose AI model with systemic risk.

3. Where the Commission concludes that the arguments submitted pursuant to paragraph 2 are not sufficiently substantiated and the relevant provider was not able to demonstrate that the general purpose AI model does not present, due to its specific characteristics, systemic risks, it shall reject those arguments and the general-purpose AI model shall be considered as general purpose AI model with systemic risk.

4. The Commission may designate a general purpose AI model as presenting systemic risks, ex officio or following a qualified alert of the scientific panel pursuant to point (a) of Article [Alerts of systemic risks by the scientific panel] (1) on the basis of criteria set out in Annex YY. The Commission shall be empowered to specify and update the criteria in Annex YY by means of delegated acts in accordance with Article 74 (2).

4a. Upon a reasoned request of a provider whose model has been designated as a general- purpose AI model with systemic risk pursuant to paragraph 4, the Commission shall take the request into account and may decide to reassess whether the general-purpose AI model can still be considered to present systemic risks on the basis of the criteria set out in Annex YY. Such request shall contain objective, concrete and new reasons that have arisen since the designation decision. Providers may request reassessment at the earliest six months after the designation decision. Where the Commission, following its reassessment, decides to maintain the designation as general-purpose AI model with systemic risk, providers may request reassessment at the earliest six months after this decision.

5. The Commission shall ensure that a list of general-purpose AI models with systemic risk is published and shall keep that list up to date, without prejudice to the need to respect and protect intellectual property rights and confidential business information or trade secrets in accordance with Union and national law.

Chapter II   Obligations for providers of general purpose AI models

Article 52c   Obligations for providers of general purpose AI models

1. Providers of general purpose AI models shall:

(a) draw up and keep up-to-date the technical documentation of the model, including its training and testing process and the results of its evaluation, which shall contain, at a minimum, the elements set out in Annex XX for the purpose of providing it, upon request, to the AI Office and the national competent authorities;

(b) draw up, keep up-to-date and make available information and documentation to providers of AI systems who intend to integrate the general-purpose AI model in their AI system. Without prejudice to the need to respect and protect intellectual property rights and confidential business information or trade secrets in accordance with Union and national law, the information and documentation shall:

(i) enable providers of AI systems to have a good understanding of the capabilities and limitations of the general purpose AI model and to comply with their obligations pursuant to this Regulation; and

(ii) contain, at a minimum, the elements set out in Annex XY;

(c) put in place a policy to respect Union copyright law in particular to identify and respect, including through state of the art technologies, the reservations of rights expressed pursuant to Article 4(3) of Directive (EU) 2019/790;

(d) draw up and make publicly available a sufficiently detailed summary about the content used for training of the general-purpose AI model, according to a template provided by the AI Office;

-2. The obligations set out in paragraph 1, with the exception of letters (c) and (d), shall not apply to providers of AI models that are made accessible to the public under a free and open licence that allows for the access, usage, modification, and distribution of the model, and whose parameters, including the weights, the information on the model architecture, and the information on model usage, are made publicly available. This exception shall not apply to general purpose AI models with systemic risks.

2. Providers of general purpose AI models shall cooperate as necessary with the Commission and the national competent authorities in the exercise of their competences and powers pursuant to this Regulation.

3. Providers of general purpose AI models may rely on codes of practice within the meaning of Article E demonstrate compliance with the obligations in paragraph 1, until a harmonised standard is published. Compliance with a European harmonised standard grants providers the presumption of conformity. Providers of general-purpose AI models with systemic risks who do not adhere to an approved code of practice shall demonstrate alternative adequate means of compliance for approval of the Commission.

4. For the purpose of facilitating compliance with Annex XX, notably point 2, (d) and (e), the Commission shall be empowered to adopt delegated acts in accordance with Article 73 to detail measurement and calculation methodologies with a view to allow comparable and verifiable documentation.

4a. The Commission is empowered to adopt delegated acts in accordance with Article 73(2) to amend Annexes XX and XY in the light of the evolving technological developments.

4b. Any information and documentation obtained pursuant to the provisions of this Article, including trade secrets, shall be treated in compliance with the confidentiality obligations set out in Article 70.

New article 52ca Authorised representative1. Prior to placing a general purpose AI model on the Union market providers established outside the Union shall, by written mandate, appoint an authorised representative which is established in the Union and shall enable it to perform its tasks under this Regulation. 2. The authorised representative shall perform the tasks specified in the mandate received from the provider. It shall provide a copy of the mandate to the AI Office upon request, in one of the official languages of the institutions of the Union. For the purpose of this Regulation, the mandate shall empower the authorised representative to carry out the following tasks: a) verify that the technical documentation specified in Annex IXa has been drawn up and all obligations referred to in Articles 52c and, where applicable, Article 52d have been fulfilled by the provider; b) keep a copy of the technical documentation at the disposal of the AI Office and national competent authorities, for a period ending 10 years after the model has been placed on the market and the contact details of the provider by which the authorised representative has been appointed; c) provide the AI Office, upon a reasoned request, with all the information and documentation, including that kept according to point (a), necessary to demonstrate the compliance with the obligations in this Title; d)  cooperate with the AI Office and national competent authorities, upon a reasoned request, on any action the latter takes in relation to the general-purpose AI model with systemic risks, including when the model is integrated into AI systems placed on the market or put into service in the Union; 3. The mandate shall empower the authorised representative to be addressed, in addition to or instead of the provider, by the AI Office or the national competent authorities, on all issues related to ensuring compliance with this Regulation. 4. The authorised representative shall terminate the mandate if it considers or has reason to consider that the provider acts contrary to its obligations under this Regulation. In such a case, it shall also immediately inform the AI Office about the termination of the mandate and the reasons thereof. 5. The obligation set out in this article shall not apply to providers of general purpose AI models that are made accessible to the public under a free and open source licence that allows for the access, usage, modification, and distribution of the model, and whose parameters, including the weights, the information on the model architecture, and the information on model usage, are made publicly available, unless the general purpose AI models present systemic risks.

Chapter III   Obligations for providers of general purpose AI models with systemic risk

Article 52d   Obligations for providers of general-purpose AI models with systemic risk

1. In addition to the obligations listed in Article C, providers of general-purpose AI models with systemic risk shall:

(a) perform model evaluation in accordance with standardised protocols and tools reflecting the state of the art, including conducting and documenting adversarial testing of the model with a view to identify and mitigate systemic risk;assess and mitigate possible systemic risks at Union level, including their sources, that may stem from the development, placing on the market, or use of general purpose AI models with systemic risk;keep track of, document and report without undue delay to the AI Office and, as appropriate, to national competent authorities, relevant information about serious incidents and possible corrective measures to address them;

(b) ensure an adequate level of cybersecurity protection for the general purpose AI model with systemic risk and the physical infrastructure of the model.

(c) Providers of general purpose AI models with systemic risk may rely on codes of practice within the meaning of Article E to demonstrate compliance with the obligations in paragraph 1, until a harmonised standard is published. Compliance with a European harmonised standard grants providers the presumption of conformity. Providers of general- purpose AI models with systemic risks who do not adhere to an approved code of practice shall demonstrate alternative adequate means of compliance for approval of the Commission.

(d) Any information and documentation obtained pursuant to the provisions of this Article, including trade secrets, shall be treated in compliance with the confidentiality obligations set out in Article 70.

Article 52e  Codes of practice

1. The AI Office shall encourage and facilitate the drawing up of codes of practice at Union level as an element to contribute to the proper application of this Regulation, taking into account international approaches.

2. The AI Office and the AI Board shall aim to ensure that the codes of practice cover, but not necessarily be limited to, the obligations provided for in Articles C and D, including the following issues:

(a) means to ensure that the information referred to in Article C (a) and (b) is kept up to date in the light of market and technological developments, and the adequate level of detail for the summary about the content used for training;

(b) the identification of the type and nature of the systemic risks at Union level, including their sources when appropriate;

(c) the measures, procedures and modalities for the assessment and management of the systemic risks at Union level, including the documentation thereof. The assessment and management of the systemic risks at Union level shall be proportionate to the risks, take into consideration their severity and probability and take into account the specific challenges of tackling those risks in the light of the possible ways in which such risks may emerge and materialize along the AI value chain.

3. The AI Office may invite the providers of general-purpose AI models, as well as relevant national competent authorities, to participate in the drawing up of codes of practice. Civil society organisations, industry, academia and other relevant stakeholders, such as downstream providers and independent experts, may support the process.

4. The AI Office and the Board shall aim to ensure that the codes of practice clearly set out their specific objectives and contain commitments or measures, including key performance indicators as appropriate, to ensure the achievement of those objectives and take due account of the needs and interests of all interested parties, including affected persons, at Union level.

5. The AI Office may invite all providers of general-purpose AI models to participate in the codes of practice. For providers of general-purpose AI models not presenting systemic risks this participation should be limited to obligations foreseen in paragraph 2 point a) of this Article, unless they declare explicitly their interest to join the full code.

6. The AI Office shall aim to ensure that participants to the codes of practice report regularly to the AI Office on the implementation of the commitments and the measures taken and their outcomes, including as measured against the key performance indicators as appropriate. Key performance indicators and reporting commitments shall take into account differences in size and capacity between different participants.

7. The AI Office and the AI Board shall regularly monitor and evaluate the achievement of the objectives of the codes of practice by the participants and their contribution to the proper application of this Regulation. The AI Office and the Board shall assess whether the codes of practice cover the obligations provided for in Articles C and D, including the issues listed in paragraph 2 of this Article, and shall regularly monitor and evaluate the achievement of their objectives. They shall publish their assessment of the adequacy of the codes of practice. The Commission may, by way of implementing acts, decide to approve the code of practice and give it a general validity within the Union. Those implementing acts shall be adopted in accordance with the examination procedure set out in Article 74(2).

8. As appropriate, the AI Office shall also encourage and facilitate review and adaptation of the codes of practice, in particular in light of emerging standards. The AI Office shall assist in the assessment of available standards.

9. If, by the time the Regulation becomes applicable, a Code of Practice cannot be finalised, or if the AI Office deems it is not adequate following under paragraph 6, the Commission may provide, by means of implementing acts, common rules for the implementation of the obligations provided for in Articles C [Article 52c] and D [Article 52d], including the issues set out in paragraph 2.

TITLE V   MEASURES IN SUPPORT OF INNOVATION

Article 53   AI regulatory sandboxes

1. Member States shall ensure that their competent authorities establish at least one AI regulatory sandbox at national level, which shall be operational 24 months after entry into force. This sandbox may also be established jointly with one or several other Member States’ competent authorities. The Commission may provide technical support, advice and tools for the establishment and operation of AI regulatory sandboxes. The obligation established in previous paragraph can also be fulfilled by participation in an existing sandbox insofar as this participation provides equivalent level of national coverage for the participating Member States.

1a.   Additional AI regulatory sandboxes at regional or local levels or jointly with other Member States’ competent authorities may also be established;

1b.   The European Data Protection Supervisor may also establish an AI regulatory sandbox for the EU institutions, bodies and agencies and exercise the roles and the tasks of national competent authorities in accordance with this chapter.

1c.   Member States shall ensure that competent authorities referred to in paragraphs 1 and 1a allocate sufficient resources to comply with this Article effectively and in a timely manner. Where appropriate, national competent authorities shall cooperate with other relevant authorities and may allow for the involvement of other actors within the AI ecosystem.

This Article shall not affect other regulatory sandboxes established under national or Union law. Member States shall ensure an appropriate level of cooperation between the authorities supervising those other sandboxes and the national competent authorities.

1d.   AI regulatory sandboxes established under Article 53(1) of this Regulation shall, in accordance with Articles 53 and 53a, provide for a controlled environment that fosters innovation and facilitates the development, training, testing and validation of innovative AI systems for a limited time before their placement on the market or putting into service pursuant to a specific sandbox plan agreed between the prospective providers and the competent authority. Such regulatory sandboxes may include testing in real world conditions supervised in the sandbox.

1e.    Competent authorities shall provide, as appropriate, guidance, supervision and support within the sandbox with a view to identifying risks, in particular to fundamental rights, health and safety, testing, mitigation measures, and their effectiveness in relation to the obligations and requirements of this Regulation and, where relevant, other Union and Member States legislation supervised within the sandbox.

1f.    Competent authorities shall provide providers and prospective providers with guidance on regulatory expectations and how to fulfil the requirements and obligations set out in this Regulation.

Upon request of the provider or prospective provider of the AI system, the competent authority shall provide a written proof of the activities successfully carried out in the sandbox. The competent authority shall also provide an exit report detailing the activities carried out in the sandbox and the related results and learning outcomes. Providers may use such documentation to demonstrate the compliance with this Regulation through the conformity assessment process or relevant market surveillance activities. In this regard, the exit reports and the written proof provided by the national competent authority shall be taken positively into account by market surveillance authorities and notified bodies, with a view to accelerate conformity assessment procedures to a reasonable extent.

1fa. Subject to the confidentiality provisions in Article 70 and with the agreement of the sandbox provider/prospective provider, the European Commission and the Board shall be authorised to access the exit reports and shall take them into account, as appropriate, when exercising their tasks under this Regulation. If both provider and prospective provider and the national competent authority explicitly agree to this, the exit report can be made publicly available through the single information platform referred to in this article.

1g.     The establishment of AI regulatory sandboxes shall aim to contribute to the following objectives:

  1. improve legal certainty to achieve regulatory compliance with this Regulation or, where relevant, other applicable Union and Member States legislation;
  2. support the sharing of best practices through cooperation with the authorities involved in the AI regulatory sandbox;
  3. foster innovation and competitiveness and facilitate the development of an AI ecosystem;
  4. contribute to evidence-based regulatory learning;
  5. facilitate and accelerate access to the Union market for AI systems, in particular when provided by small and medium-sized enterprises (SMEs), including start-ups.

2. National competent authorities shall ensure that, to the extent the innovative AI systems involve the processing of personal data or otherwise fall under the supervisory remit of other national authorities or competent authorities providing or supporting access to data, the national data protection authorities, and those other national authorities are associated to the operation of the AI regulatory sandbox and involved in the supervision of those aspects to the extent of their respective tasks and powers, as applicable.

3. The AI regulatory sandboxes shall not affect the supervisory and corrective powers of the competent authorities supervising the sandboxes, including at regional or local level. Any significant risks to health and safety and fundamental rights identified during the development and testing of such AI systems shall result in an adequate mitigation. National competent authorities shall have the power to temporarily or permanently suspend the testing process, or participation in the sandbox if no effective mitigation is possible and inform the AI Office of such decision. National competent authorities shall exercise their supervisory powers within the limits of the relevant legislation, using their discretionary powers when implementing legal provisions to a specific AI sandbox project, with the objective of supporting innovation in AI in the Union.

4. Providers and prospective providers in the AI regulatory sandbox shall remain liable under applicable Union and Member States liability legislation for any damage inflicted on third parties as a result of the experimentation taking place in the sandbox. However, provided that the prospective provider(s) respect the specific plan and the terms and conditions for their participation and follow in good faith the guidance given by the national competent authority, no administrative fines shall be imposed by the authorities for infringements of this Regulation. To the extent that other competent authorities responsible for other Union and Member States’ legislation have been actively involved in the supervision of the AI system in the sandbox and have provided guidance for compliance, no administrative fines shall be imposed regarding that legislation.

4b. The AI regulatory sandboxes shall be designed and implemented in such a way that, where relevant, they facilitate cross-border cooperation between national competent authorities.

5. National competent authorities shall coordinate their activities and cooperate within the framework of the Board.

5a.         National competent authorities shall inform the AI Office and the Board of the establishment of a sandbox and may ask for support and guidance. A list of planned and existing AI sandboxes shall be made publicly available by the AI Office and kept up to date in order to encourage more interaction in the regulatory sandboxes and cross-border cooperation.

5b.         National competent authorities shall submit to the AI Office and to the Board, annual reports, starting one year after the establishment of the AI regulatory sandbox and then every year until its termination and a final report. Those reports shall provide information on the progress and results of the implementation of those sandboxes, including best practices, incidents, lessons learnt and recommendations on their setup and, where relevant, on the application and possible revision of this Regulation, including its delegated and implementing acts, and other Union law supervised within the sandbox. Those annual reports or abstracts thereof shall be made available to the public, online. The Commission shall, where appropriate, take the annual reports into account when exercising their tasks under this Regulation.

6. The Commission shall develop a single and dedicated interface containing all relevant information related to sandboxes to allow stakeholders to interact with regulatory sandboxes and to raise enquiries with competent authorities, and to seek non-binding guidance on the conformity of innovative products, services, business models embedding AI technologies, in accordance with Article 55(1)(c). The Commission shall proactively coordinate with national competent authorities, where relevant.

Article 53a Modalities and functioning of AI regulatory sandboxes

In order to avoid fragmentation across the Union, the Commission shall adopt a an implementing act detailing the modalities for the establishment, development, implementation, operation and supervision of the AI regulatory sandboxes. The implementing act shall include common principles on the following issues:

1. eligibility and selection for participation in the AI regulatory sandbox;

2. procedure for the application, participation, monitoring, exiting from and termination of the AI regulatory sandbox, including the sandbox plan and the exit report;

3. the terms and conditions applicable to the participants. The implementing acts shall ensure that:

a) regulatory sandboxes are open to any applying prospective provider of an AI system who fulfils eligibility and selection criteria. The criteria for accessing to the regulatory sandbox are transparent and fair and establishing authorities inform applicants of their decision within 3 months of the application;

b) regulatory sandboxes allow broad and equal access and keep up with demand for participation; prospective providers may also submit applications in partnerships with users and other relevant third parties;

c) the modalities and conditions concerning regulatory sandboxes shall to the best extent possible support flexibility for national competent authorities to establish and operate their AI regulatory sandboxes;

d) access to the AI regulatory sandboxes is free of charge for SMEs and start-ups without prejudice to exceptional costs that national competent authorities may recover in a fair and proportionate manner;

e) they facilitate prospective providers, by means of the learning outcomes of the sandboxes, to conduct the conformity assessment obligations of this Regulation or the voluntary application of the codes of conduct referred to in Article 69;

f) regulatory sandboxes facilitate the involvement of other relevant actors within the AI ecosystem, such as notified bodies and standardisation organisations (SMEs, start-ups, enterprises, innovators, testing and experimentation facilities, research and experimentation labs and digital innovation hubs, centers of excellence, individual researchers), in order to allow and facilitate cooperation with the public and private sector;

g) procedures, processes and administrative requirements for application, selection, participation and exiting the sandbox are simple, easily intelligible, clearly communicated in order to facilitate the participation of SMEs and start-ups with limited legal and administrative capacities and are streamlined across the Union, in order to avoid fragmentation and that participation in a regulatory sandbox established by a Member State, or by the EDPS is mutually and uniformly recognised and carries the same legal effects across the Union;

h) participation in the AI regulatory sandbox is limited to a period that is appropriate to the complexity and scale of the project. This period may be extended by the national competent authority;

i) the sandboxes shall facilitate the development of tools and infrastructure for testing, benchmarking, assessing and explaining dimensions of AI systems relevant for regulatory learning , such as accuracy, robustness and cybersecurity as well as measures to mitigate risks to fundamental rights,[environment] and the society at large.

3.    Prospective providers in the sandboxes, in particular SMEs and start-ups, shall be directed, where relevant, to pre-deployment services such as guidance on the implementation of this Regulation, to other value-adding services such as help with standardisation documents and certification, Testing & Experimentation Facilities, Digital Hubs, Centres of Excellence, and [EU benchmarking capabilities].

4.    When national competent authorities consider authorising testing in real world conditions supervised within the framework of an AI regulatory sandbox established under this Article, they shall specifically agree with the participants on the terms and conditions of such testing and in particular on the appropriate safeguards with the view to protect fundamental rights, health and safety. Where appropriate, they shall cooperate with other national competent authorities with a view to ensure consistent practices across the Union.

Article 54   Further processing of personal data for developing certain AI systems in the public interest in the AI regulatory sandbox

1. In the AI regulatory sandbox personal data lawfully collected for other purposes may be processed solely for the purposes of developing, training and testing certain AI systems in the sandbox when all of the following conditions are met:

(a) AI systems shall be developed for safeguarding substantial public interest by a public authority or another natural or legal person governed by public law or by private law and in one or more of the following areas:

(ii) public safety and public health, including disease dete.ction, diagnosis prevention, control and treatment and improvement of health care systems;

(iii) a high level of protection and improvement of the quality of the environment, protection of biodiversity, pollution as well as green transition, climate change mitigation and adaptation;

(iiia) energy sustainability

(iiib) safety and resilience of transport systems and mobility, critical infrastructure and networks;

(iiic) efficiency and quality of public administration and public services;

(b) the data processed are necessary for complying with one or more of the requirements referred to in Title III, Chapter 2 where those requirements cannot be effectively fulfilled by processing anonymised, synthetic or other non-personal data;

(c) there are effective monitoring mechanisms to identify if any high risks to the rights and freedoms of the data subjects, as referred to in Article 35 of Regulation (EU) 2016/679 and in Article 39 of Regulation (EU) 2018/1725, may arise during the sandbox experimentation as well as response mechanism to promptly mitigate those risks and, where necessary, stop the processing;

(d) any personal data to be processed in the context of the sandbox are in a functionally separate, isolated and protected data processing environment under the control of the prospective provider and only authorised persons have access to that those data;

(e) Providers can only further share the originaly collected data in compliance with EU data protection law. Any personal data crated in the sandbox cannot be shared outside the sandbox

(f) any processing of personal data in the context of the sandbox do not lead to measures or decisions affecting the data subjects nor affect the application of their rights laid down in Union law on the protection of personal data;

(g) any personal data processed in the context of the sandbox are protected by means of appropriate technical and organisational measures and deleted once the participation in the sandbox has terminated or the personal data has reached the end of its retention period;

(h) the logs of the processing of personal data in the context of the sandbox are kept for the duration of the participation in the sandbox, unless provided otherwise by Union or national law;

(i) complete and detailed description of the process and rationale behind the training, testing and validation of the AI system is kept together with the testing results as part of the technical documentation in Annex IV;

(i) a short summary of the AI project developed in the sandbox, its objectives and expected results published on the website of the competent authorities. This obligation shall not cover sensitive operational data in relation to the activities of law enforcement, border control, immigration or asylum authorities.

1a.     For the purpose of prevention, investigation, detection or prosecution of criminal offences or the execution of criminal penalties, including the safeguarding against and the prevention of threats to public security, under the control and responsibility of law enforcement authorities, the processing of personal data in AI regulatory sandboxes shall be based on a specific Member State or Union law and subject to the same cumulative conditions as referred to in paragraph 1.

2. Paragraph 1 is without prejudice to Union or Member States legislation excluding processing for other purposes than those explicitly mentioned in that legislation, as well as to Union or Member States laws laying down the basis for the processing of personal data which is necessary for the purpose of developing, testing and training of innovative AI systems or any other legal basis, in compliance with Union law on the protection of personal data.

Article 54a   Testing of high-risk AI systems in real world conditions outside AI regulatory sandboxes

1. Testing of AI systems in real world conditions outside AI regulatory sandboxes may be conducted by providers or prospective providers of high-risk AI systems listed in Annex III, in accordance with the provisions of this Article and the real-world testing plan referred to in this Article, without prejudice to the prohibitions under Article 5.

The detailed elements of the real-world testing plan shall be specified in implementing acts adopted by the Commission in accordance with the examination procedure referred to in Article 74(2).

This provision shall be without prejudice to Union or national law for the testing in real world conditions of high-risk AI systems related to products covered by legislation listed in Annex II.

2. Providers or prospective providers may conduct testing of high-risk AI systems referred to in Annex III in real world conditions at any time before the placing on the market or putting into service of the AI system on their own or in partnership with one or more prospective deployers.

3. The testing of high-risk AI systems in real world conditions under this Article shall be without prejudice to ethical review that may be required by national or Union law.

4. Providers or prospective providers may conduct the testing in real world conditions only where all of the following conditions are met:

(a) the provider or prospective provider has drawn up a real-world testing plan and submitted it to the market surveillance authority in the Member State(s) where the testing in real world conditions is to be conducted

(b) the market surveillance authority in the Member State(s) where the testing in real world conditions is to be conducted has approved the testing in real world conditions and the real-world testing plan. Where the market surveillance authority in that Member State has not provided with an answer in 30 days, the testing in real world conditions and the real-world testing plan shall be understood as approved. In cases where national law does not foresee a tacit approval, the testing in real world conditions shall be subject to an authorisation;

(c) the provider or prospective provider with the exception of high-risk AI systems referred to in Annex III, points 1, 6 and 7 in the areas of law enforcement, migration, asylum and border control management, and high risk AI systems referred to in Annex III point 2, has registered the testing in real world conditions in the non public part of the EU database referred to in Article 60(3) with a Union-wide unique single identification number and the information specified in Annex VIIIa.

(d) the provider or prospective provider conducting the testing in real world conditions is established in the Union or it has appointed a legal representative who is established in the Union;

(e) Data collected and processed for the purpose of the testing in real world conditions shall only be transferred to third countries outside the Union provided appropriate and applicable safeguards under Union law are implemented;

(f)the testing in real world conditions does not last longer than necessary to achieve its objectives and in any case not longer than 6 months, which may be extended for an additional amount of 6 months, subject to prior notification by the provider to the market surveillance authority, accompanied by an explanation on the need for such time extension;

(g) persons belonging to vulnerable groups due to their age, physical or mental disability are appropriately protected;

(h) where a provider or prospective provider organises the testing in real world conditions in cooperation with one or more prospective deployers, the latter have been informed of all aspects of the testing that are relevant to their decision to participate, and given the relevant instructions on how to use the AI system referred to in Article 13; the provider or prospective provider and the deployer(s) shall conclude an agreement specifying their roles and responsibilities with a view to ensuring compliance with the provisions for testing in real world conditions under this Regulation and other applicable Union and Member States legislation;

(i) the subjects of the testing in real world conditions have given informed consent in accordance with Article 54b, or in the case of law enforcement, where the seeking of informed consent would prevent the AI system from being tested, the testing itself and the outcome of the testing in the real world conditions shall not have any negative effect on the subject and his or her personal data shall be deleted after the test is performed.

(j) the testing in real world conditions is effectively overseen by the provider or prospective provider and deployer(s) with persons who are suitably qualified in the relevant field and have the necessary capacity, training and authority to perform their tasks;

(k) the predictions, recommendations or decisions of the AI system can be effectively reversed and disregarded.

5.    Any subject of the testing in real world conditions, or his or her legally designated representative, as appropriate, may, without any resulting detriment and without having to provide any justification, withdraw from the testing at any time by revoking his or her informed consent and request the immediate and permanent deletion of their personal data. The withdrawal of the informed consent shall not affect the activities already carried out. 5a. In accordance with Article 63a, Member States shall confer their market surveillance authorities the powers of requiring providers and prospective providers information, of carrying out unannounced remote or on-site inspections and on performing checks on the development of the testing in real world conditions and the related products. Market surveillance authorities shall use these powers to ensure a safe development of these tests.

6. Any serious incident identified in the course of the testing in real world conditions shall be reported to the national market surveillance authority in accordance with Article 62 of this Regulation. The provider or prospective provider shall adopt immediate mitigation measures or, failing that, suspend the testing in real world conditions until such mitigation takes place or otherwise terminate it. The provider or prospective provider shall establish a procedure for the prompt recall of the AI system upon such termination of the testing in real world conditions.

7. Providers or prospective providers shall notify the national market surveillance authority in the Member State(s) where the testing in real world conditions is to be conducted of the suspension or termination of the testing in real world conditions and the final outcomes.

8. The provider and prospective provider shall be liable under applicable Union and Member States liability legislation for any damage caused in the course of their participation in the testing in real world conditions.

Article 54b Informed consent to participate in testing in real world conditions outside AI regulatory sandboxes

1. For the purpose of testing in real world conditions under Article 54a, informed consent shall be freely given by the subject of testing prior to his or her participation in such testing and after having been duly informed with concise, clear, relevant, and understandable information regarding:

(i) the nature and objectives of the testing in real world conditions and the possible inconvenience that may be linked to his or her participation; (ii) the conditions under which the testing in real world conditions is to be conducted, including the expected duration of the subject’s participation; (iii) the subject’s rights and guarantees regarding participation, in particular his or her right to refuse to participate in and the right to withdraw from testing in real world conditions at any time without any resulting detriment and without having to provide any justification; (iv) the modalities for requesting the reversal or the disregard of the predictions, recommendations or decisions of the AI system; (v)     the Union-wide unique single identification number of the testing in real world conditions in accordance with Article 54a(4c) and the contact details of the provider or its legal representative from whom further information can be obtained.

2. The informed consent shall be dated and documented and a copy shall be given to the subject or his or her legal representative.

Article 55   Measures for providers and deployers, in particular SMEs, including start-ups

1. Member States shall undertake the following actions:

(a) provide SMEs, including start-ups, having a registered office or a branch in the Union, with priority access to the AI regulatory sandboxes, to the extent that they fulfil the eligibility conditions and selection criteria. The priority access shall not preclude other SMEs including start-ups other than those referred to in the first subparagraph to access to the AI regulatory sandbox, provided that they fulfil the eligibility conditions and selection criteria;

(b) organise specific awareness raising and training activities on the application of this Regulation tailored to the needs of SMEs including start-ups, users and, as appropriate, local public authorities;

(c) utilise existing dedicated channels and where appropriate, establish new ones for communication with SMEs including start-ups, users, other innovators and, as appropriate, local public authorities to provide advice and respond to queries about the implementation of this Regulation, including as regards participation in AI regulatory sandboxes.;

(ca) facilitate the participation of SMEs and other relevant stakeholders in the standardisation development process.

2. The specific interests and needs of the SME providers, including start-ups, shall be taken into account when setting the fees for conformity assessment under Article 43, reducing those fees proportionately to their size, market size and other relevant indicators.

2a.     The AI Office shall undertake the following actions:

(a) upon request of the AI Board, provide standardised templates for the areas covered by this Regulation;

(b) develop and maintain a single information platform providing easy to use information in relation to this Regulation for all operators across the Union;

(c) organise appropriate communication campaigns to raise awareness about the obligations arising from this Regulation;

(d) evaluate and promote the convergence of best practices in public procurement procedures in relation to AI systems.

Article 55a          Derogations for specific operators

2b.         Microenterprises as defined in Article 2(3) of the Annex to the Commission Recommendation 2003/361/EC concerning the definition of micro, small and medium- sized enterprises, provided those enterprises do not have partner enterprises or linked enterprises as defined in Article 3 of the same Annex may fulfil certain elements of the quality management system required by Article 17 of this Regulation in a simplified manner. For this purpose, the Commission shall develop guidelines on the elements of the quality management system which may be fulfilled in a simplified manner considering the needs of micro enterprises without affecting the level of protection and the need for compliance with the requirements for high-risk AI systems.

2c.         2. Paragraph 1 shall not be interpreted as exempting those operators from fulfilling any other requirements and obligations laid down in this Regulation, including those established in Articles 9, 10, 11, 12, 13, 14, 15, 61 and 62.

TITLE VI GOVERNANCE

Article 55b  Governance at Union level 

1. The Commission shall develop Union expertise and capabilities in the field of artificial intelligence. For this purpose, the Commission has established the European AI Office by Decision […]”

2.   Member States shall facilitate the tasks entrusted to the AI Office, as reflected in this Regulation

Chapter 1  European Artificial Intelligence Board

Article 56  Establishment and structure of the European Artificial Intelligence Board

2. A ‘European Artificial Intelligence Board’ (the ‘Board’) is established.

2. The Board shall be composed of one representative per Member State. The European Data Protection Supervisor, shall participate as observer. The AI Office shall also attend the Board’s meetings without taking part in the votes. Other national and Union authorities, bodies or experts may be invited to the meetings by the Board on a case by case basis, where the issues discussed are of relevance for them.

2a.   Each representative shall be designated by their Member State for a period of 3 years, renewable once.

2b.   Member States shall ensure that their representatives in the Board:

(a) have the relevant competences and powers in their Member State so as to contribute actively to the achievement of the Board’s tasks referred to in Article 58; 

(b) are designated as a single contact point vis-à-vis the Board and, where appropriate, taking into account Member States’ needs, as a single contact point for stakeholders; 

(c) are empowered to facilitate consistency and coordination between national competent authorities in their Member State as regards the implementation of this Regulation, including through the collection of relevant data and information for the purpose of fulfilling their tasks on the Board.

3. The designated representatives of the Member States shall adopt the Board’s rules of procedure by a two-thirds majority. The rules of procedure shall, in particular, lay down procedures for the selection process, duration of mandate and specifications of the tasks of the Chair, the voting modalities, and the organisation of the Board’s activities and its sub- groups.

3a.       The Board shall establish two standing sub-groups to provide a platform for cooperation     and exchange among market surveillance authorities and notifying authorities on issues    related to market surveillance and notified bodies respectively.

The standing sub-group for market surveillance should act as the Administrative Cooperation Group (ADCO) for this Regulation in the meaning of Article 30 of Regulation (EU) 2019/1020.

The Board may establish other standing or temporary sub-groups as appropriate for the purpose of examining specific issues. Where appropriate, representatives of the advisory forum as referred to in Article [XX] may be invited to such sub-groups or to specific meetings of those subgroups in the capacity of observers.

3b.     The Board shall be organised and operated so as to safeguard the objectivity and impartiality of its activities.

4.      The Board shall be chaired by one of the representatives of the Member States. The European AI Office shall provide the Secretariat for the Board. convene the meetings upon request of the Chair and prepare the agenda in accordance with the tasks of the Board pursuant to this Regulation and its rules of procedure.

Article 58  Tasks of the Board

The Board shall advise and assist the Commission and the Member States in order to facilitate the consistent and effective application of this Regulation. For this purpose the Board may in particular:

(a) contribute to the coordination among national competent authorities responsible for the application of this Regulation and, in cooperation and subject to agreement of the concerned market surveillance authorities, support joint activities of market surveillance authorities referred to in Article 63(7a);

(b) collect and share technical and regulatory expertise and best practices among Member States;

(c) provide advice in the implementation of this Regulation, in particular as regards the enforcement of rules on general purpose AI models;

(d) contribute to the harmonisation of administrative practices in the Member States, including in relation to the derogation from the conformity assessment procedures referred to in Article 47, the functioning of regulatory sandboxes and testing in real world conditions referred to in Article 53, 54 and 54a;

(e) upon the request of the Commission or on its own initiative, issue recommendations and written opinions on any relevant matters related to the implementation of this Regulation and to its consistent and effective application, including:

(i) on the development and application of codes of conduct and code of practice pursuant to this Regulation as well as the Commission’s guidelines;

(ii) the evaluation and review of this Regulation pursuant to Article 84, including as regards the serious incident reports referred to in Article 62 and the functioning of the database referred to in Article 60, the preparation of the delegated or implementing acts, and possible alignments of this Regulation with the legal acts listed in Annex II;

(iii) on technical specifications or existing standards regarding the requirements set out in Title III, Chapter 2,

(iv) on the use of harmonised standards or common specifications referred to in Articles 40 and 41,

(v) trends, such as European global competitiveness in artificial intelligence, the uptake of artificial intelligence in the Union and the development of digital skills; (via) trends on the evolving typology of AI value chains, in particular on the resulting implications in terms of accountability;

(vi) on the potential need for amendment of Annex III in accordance with Article 7 and on the potential need for possible revision of Article 5 pursuant to Article 84, taking into account relevant available evidence and the latest developments in technology;

(f) support the Commission in promoting AI literacy, public awareness and understanding of the benefits, risks, safeguards and rights and obligations in relation to the use of AI systems;

(g) facilitate the development of common criteria and a shared understanding among market operators and competent authorities of the relevant concepts provided for in this Regulation, including by contributing to the development of benchmarks;

(h) cooperate, as appropriate, with other Union institutions, bodies, offices and agencies, as well as relevant Union expert groups and networks in particular in the fields of product safety, cybersecurity, competition, digital and media services, financial services, , consumer protection, data and fundamental rights protection;

(i) contribute to the effective cooperation with the competent authorities of third countries and with international organisations;

(j) assist national competent authorities and the Commission, in developing the organisational and technical expertise required for the implementation of this Regulation, including by contributing to the assessment of training needs for staff of Member States involved in implementing this Regulation;

(j1) assist the AI Office in supporting national competent authorities in the establishment and development of regulatory sandboxes and facilitate cooperation and information-sharing among regulatory sandboxes;

(k) contribute and provide relevant advice in the development of guidance documents;

(l) advise the Commission in relation to international matters on artificial intelligence

(m) provide opinions to the Commission on the qualified alerts regarding general purpose AI models

(n) receive opinions by the Member states on the qualified alerts regarding general purpose AI models and on national experiences and practices on the monitoring and enforcement of the AI systems, in particular systems integrating the general purpose AI models.

Article 58a  Advisory forum 

1. An advisory forum shall be established to advise and provide technical expertise to the Board and the Commission to contribute to their tasks under this Regulation.

2. The membership of the advisory forum shall represent a balanced selection of stakeholders, including industry, start-ups, SMEs, civil society and academia. The membership of the advisory forum shall be balanced with regard to commercial and non- commercial interests and, within the category of commercial interests, with regards to SMEs and other undertakings.

3. The Commission shall appoint the members of the advisory forum, in accordance with the criteria set out in the previous paragraph, among stakeholders with recognised expertise in the field of AI.

4. The term of office of the members of the advisory forum shall be two years, which may be extended by up to no more than four years.

5. The Fundamental Rights Agency, European Union Agency for Cybersecurity, the European Committee for Standardization (CEN), the European Committee for Electrotechnical Standardization (CENELEC), and the European Telecommunications Standards Institute (ETSI) shall be permanent members of the advisory forum. 

6. The advisory forum shall draw up its rules of procedure. It shall elect two co-chairs from among its members, in accordance with criteria set out in paragraph 2. The term of office of the co- chairs shall be two years, renewable once. 

7. The advisory forum shall hold meetings at least two times a year. The advisory forum may invite experts and other stakeholders to its meetings. 

8. In fulfilling its role as set out in paragraph 1, the advisory forum may prepare opinions, recommendations and written contributions upon request of the Board or the Commission

9. The advisory forum may establish standing or temporary subgroups as appropriate for the purpose of examining specific questions related to the objectives of this Regulation. 

10. The advisory forum shall prepare an annual report of its activities. That report shall be made publicly available.

Chapter 1a Scientific Panel of independent experts

Article 58b Scientific panel of independent expert

1. The Commission shall, by means of an implementing act, make provisions on the establishment of a scientific panel of independent experts (the ‘scientific panel’) intended to support the enforcement activities under this Regulation. Those implementing acts shall be adopted in accordance with the examination procedure referred to in Article 74(2). 

2. The scientific panel shall consist of experts selected by the Commission on the basis of up-to-date scientific or technical expertise in the field of artificial intelligence necessary for the tasks set out in paragraph 3, and shall be able to demonstrate meeting all of the following conditions: (a) particular expertise and competence and scientific or technical expertise in the field of artificial intelligence; (b)  independence from any provider of AI systems or general purpose AI models or systems; (c)ability to carry out activities diligently, accurately and objectively. The Commission, in consultation with the AI Board, shall determine the number of experts in the panel in accordance with the required needs and shall ensure fair gender and geographical representation. 

3. The scientific panel shall advise and support the European AI Office, in particular with regard to the following tasks: 

(a) support the implementation and enforcement of this Regulation as regards general purpose AI models and systems, in particular by (i) alerting the AI Office of possible systemic risks at Union level of general purpose AI models, in accordance with Article [Alerts of systemic risks by the scientific panel]; (ii) contributing to the development of tools and methodologies for evaluating capabilities of general purpose AI models and systems, including through benchmarks; (iii) providing advice on the classification of general purpose AI models with systemic risk; (iiii) providing advice on the classification of different general purpose AI models and systems; (iv) contributing to the development of tools and templates. 

(b) support the work of market surveillance authorities, at their request; 

(c) support cross-border market surveillance activities as referred to in Article 63(7a), without prejudice of the powers of market surveillance authorities; 

(d) support the AI Office when carrying out its duties in the context of the safeguard clause pursuant to Article 66; 

4. The experts shall perform their tasks with impartiality, objectivity and ensure the confidentiality of information and data obtained in carrying out their tasks and activities. They shall neither seek nor take instructions from anyone when exercising their tasks under paragraph 3. Each expert shall draw up a declaration of interests, which shall be made publicly available. The AI Office shall establish systems and procedures to actively manage and prevent potential conflicts of interest.

5. The implementing act referred to in paragraph 1 shall include provisions on the conditions, procedure and modalities for the scientific panel and its members to issue alerts and request the assistance of the AI Office to the performance of its tasks.

Article 58c   Access to the pool of experts by the Member States 

1. Member States may call upon experts of the scientific panel to support their enforcement activities under this Regulation. 

2. The Member States may be required to pay fees for the advice and support by the experts. The structure and the level of fees as well as the scale and structure of recoverable costs shall be set out in the implementing act referred to in Article 58b(1), taking into account the objectives of the adequate implementation of this Regulation, cost-effectiveness and the necessity to ensure an effective access to experts by all Member States.

3. The Commission shall facilitate timely access to the experts by the Member States, as needed, and ensure that the combination of support activities carried out by EU AI testing support pursuant to Article 68a and experts pursuant to this Article is efficiently organised and provides the best possible added value.

Chapter 2    National Competent Authorities

Article 59  Designation of national competent authorities and single point of contact

1. deleted

2. Each Member State shall establish or designate at least one notifying authority and at least one market surveillance authority for the purpose of this Regulation as national competent authorities. These national competent authorities shall exercise their powers independently, impartially and without bias so as to safeguard the principles of objectivity of their activities and tasks and to ensure the application and implementation of this Regulation. The members of these authorities shall refrain from any action incompatible with their duties. Provided that those principles are respected, such activities and tasks may be performed by one or several designated authorities, in accordance with the organisational needs of the Member State.

3. Member States shall communicate to the Commission the identity of the notifying authorities and the market surveillance authorities and the tasks of those authorities and as well as any subsequent changes thereto. Member States shall make publicly available information on how competent authorities and single point of contact can be contacted, through electronic communication means by… [12 months after the date of entry into force of this Regulation]. Member States shall designate a market surveillance authority to act as single point of contact for this Regulation and notify the Commission of the identity of the single point of contact. The Commission shall make a list of the single points of contact publicly available.

4. Member States shall ensure that the national competent authority is provided with adequate technical, financial and human resources, and infrastructure to fulfil their tasks effectively under this Regulation. In particular, the national competent authority shall have a sufficient number of personnel permanently available whose competences and expertise shall include an in-depth understanding of artificial intelligence technologies, data and data computing, personal data protection, cybersecurity, fundamental rights, health and safety risks and knowledge of existing standards and legal requirements. Member States shall assess and, if deemed necessary, update competence and resource requirements referred to in this paragraph on an annual basis.

4a.     National competent authorities shall satisfy an adequate level of cybersecurity measures.

4c.         When performing their tasks, the national competent authorities shall act in compliance with the confidentiality obligations set out in Article 70.

5. By one year after entry into force of this Regulation and once every two years thereafter Member States shall report to the Commission on the status of the financial and human resources of the national competent authorities with an assessment of their adequacy. The Commission shall transmit that information to the Board for discussion and possible recommendations.

6. The Commission shall facilitate the exchange of experience between national competent authorities.

7. National competent authorities may provide guidance and advice on the implementation of this Regulation, in particular to SMEs including start-ups, taking into account the Board’s and the Commission’s guidance and advice, as appropriate. Whenever national competent authorities intend to provide guidance and advice with regard to an AI system in areas covered by other Union legislation, the competent national authorities under that Union legislation shall be consulted, as appropriate. 

8. When Union institutions, agencies and bodies fall within the scope of this Regulation, the European Data Protection Supervisor shall act as the competent authority for their supervision.

TITLE VII  EU DATABASE FOR HIGH-RISK AI SYSTEMS LISTED IN ANNEX III

Article 60 EU database for high-risk AI systems listed in Annex III

1. The Commission shall, in collaboration with the Member States, set up and maintain a EU database containing information referred to in paragraphs 2 and 2a concerning high-risk AI systems referred to in Article 6(2) which are registered in accordance with Articles 51 and 54a. When setting the functional specifications of such database, the Commission shall consult the relevant experts, and when updating the functional specifications of such database, the Commission shall consult the AI Board.

2. The data listed in Annex VIII, Section A, shall be entered into the EU database by the provider or where applicable the authorised representative.

2a.         The data listed in Annex VIII, Section B, shall be entered into the EU database by the deployer who is or who acts on behalf of public authorities, agencies or bodies, according to articles 51(1a) and (1b).

3. With the exception of the section referred to in Article 51(1c) and Article 54a(5), the information contained in the EU database registered in accordance with Article 51 shall be accessible and publicly available in a user friendly manner. The information should be easily navigable and machine-readable. The information registered in accordance with Article 54a shall be accessible only to market surveillance authorities and the Commission, unless the prospective provider or provider has given consent for making this information also accessible the public.

4. The EU database shall contain personal data only insofar as necessary for collecting and processing information in accordance with this Regulation. That information shall include the names and contact details of natural persons who are responsible for registering the system and have the legal authority to represent the provider or the deployer, as applicable.

5. The Commission shall be the controller of the EU database. It shall make available to providers, prospective providers and deployers adequate technical and administrative support. The database shall comply with the applicable accessibility requirements.

TITLE VIII POST-MARKET MONITORING, INFORMATION SHARING, MARKET SURVEILLANCE

Chapter 1   Post-market monitoring

Article 61   Post-market monitoring by providers and post-market monitoring plan for high-risk AI systems

1. Providers shall establish and document a post-market monitoring system in a manner that is proportionate to the nature of the artificial intelligence technologies and the risks of the high-risk AI system.

2. The post-market monitoring system shall actively and systematically collect, document and analyse relevant data which may be provided by deployers or which may be collected through other sources on the performance of high-risk AI systems throughout their lifetime, and allow the provider to evaluate the continuous compliance of AI systems with the requirements set out in Title III, Chapter 2. Where relevant, post-market monitoring shall include an analysis of the interaction with other AI systems. This obligation shall not cover sensitive operational data of deployers which are law enforcement authorities.

3. The post-market monitoring system shall be based on a post-market monitoring plan. The post-market monitoring plan shall be part of the technical documentation referred to in Annex IV. The Commission shall adopt an implementing act laying down detailed provisions establishing a template for the post-market monitoring plan and the list of elements to be included in the plan by six months before the entry into application of this Regulation.

4. For high-risk AI systems covered by the legal acts referred to in Annex II, Section A, where a post-market monitoring system and plan is already established under that legislation, in order to ensure consistency, avoid duplications and minimise additional burdens, providers shall have a choice to integrate, as appropriate, the necessary elements described in paragraphs 1, 2 and 3 using the template referred in paragraph 3 into already existing system and plan under the Union harmonisation legislation listed in Annex II, Section A, provided it achieves an equivalent level of protection.

The first subparagraph shall also apply high-risk AI systems referred to in point 5 of Annex III placed on the market or put into service by financial institutions that are subject to requirements regarding their internal governance, arrangements or processes under Union financial services legislation.

Chapter 2   Sharing of Information on Serious Incidents

Article 62   Reporting of serious incidents

1. Providers of high-risk AI systems placed on the Union market shall report any serious incident to the market surveillance authorities of the Member States where that incident occurred.

(1a) As a general rule, the period for the reporting referred to in paragraph 1 shall take account of the severity of the serious incident.

(1b) The notification referred to in paragraph 1 shall be made immediately after the provider has established a causal link between the AI system and the serious incident or the reasonable likelihood of such a link, and, in any event, not later than 15 days after the provider or, where applicable, the deployer, becomes aware of the serious incident.

(1c) Notwithstanding paragraph 1b, in the event of a widespread infringement or a serious incident as defined in Article 3(44) point (b) the report referred to in paragraph 1 shall be provided immediately, and not later than 2 days after the provider or, where applicable, the deployer becomes aware of that incident.

(1d) Notwithstanding paragraph 1b, in the event of death of a person the report shall be provided immediately after the provider or the deployer has established or as soon as it suspects a causal relationship between the high-risk AI system and the serious incident but not later than 10 days after the date on which the provider or, where applicable, the deployer becomes aware of the serious incident.

(1e) Where necessary to ensure timely reporting, the provider or, where applicable, the deployer, may submit an initial report that is incomplete followed up by a complete report.

1a.    Following the reporting of a serious incident pursuant to the first subparagraph, the provider shall, without delay, perform the necessary investigations in relation to the serious incident and the AI system concerned. This shall include a risk assessment of the incident and corrective action. The provider shall co-operate with the competent authorities and where relevant with the notified body concerned during the investigations referred to in the first subparagraph and shall not perform any investigation which involves altering the AI system concerned in a way which may affect any subsequent evaluation of the causes of the incident, prior to informing the competent authorities of such action.

2. Upon receiving a notification related to a serious incident referred to in Article 3(44)(c), the relevant market surveillance authority shall inform the national public authorities or bodies referred to in Article 64(3). The Commission shall develop dedicated guidance to facilitate compliance with the obligations set out in paragraph 1. That guidance shall be issued 12 months after the entry into force of this Regulation, at the latest, and shall be assessed regularly.

2a.      “2a. The market surveillance authority shall take appropriate measures, as provided in Article 19 of the Regulation 2019/1020, within 7 days from the date it received the notification referred to in paragraph 1 and follow the notification procedures as provided in the Regulation 2019/1020.

3. For high-risk AI systems referred to in Annex III that are placed on the market or put into service by providers that are subject to Union legislative instruments laying down reporting obligations equivalent to those set out in this Regulation, the notification of serious incidents shall be limited to those referred to in Article 3(44) (c ).

3a.   For high-risk AI systems which are safety components of devices, or are themselves devices, covered by Regulation (EU) 2017/745 and Regulation (EU) 2017/746 the notification of serious incidents shall be limited to those referred to in Article 3(44)(c) and be made to the national competent authority chosen for this purpose by the Member States where that incident occurred.

3a.   National competent authorities shall immediately notify the Commission of any serious incident, whether or not it has taken action on it, in accordance with Article 20 of Regulation 2019/1020.

Chapter 3 Enforcement

Article 63   Market surveillance and control of AI systems in the Union market

1. Regulation (EU) 2019/1020 shall apply to AI systems covered by this Regulation. However, for the purpose of the effective enforcement of this Regulation:

(a) any reference to an economic operator under Regulation (EU) 2019/1020 shall be understood as including all operators identified in Article 2(1) of this Regulation;

(b) any reference to a product under Regulation (EU) 2019/1020 shall be understood as including all AI systems falling within the scope of this Regulation.

2. As part of their reporting obligations under Article 34(4) of Regulation (EU) 2019/1020, the market surveillance authorities shall report annually, to the Commission and relevant national competition authorities any information identified in the course of market surveillance activities that may be of potential interest for the application of Union law on competition rules. They shall also annually report to the Commission about the use of prohibited practices that occurred during that year and about the measures taken.

3. For high-risk AI systems, related to products to which legal acts listed in Annex II, section A apply, the market surveillance authority for the purposes of this Regulation shall be the authority responsible for market surveillance activities designated under those legal acts. By derogation from the previous paragraph in justified circumstances, Member States may designate another relevant authority to act as a market surveillance authority provided that coordination is ensured with the relevant sectoral market surveillance authorities responsible for the enforcement of the legal acts listed in Annex II.

3a.     The procedures referred to in Articles 65, 66, 67 and 68 of this Regulation shall not apply to AI systems related to products, to which legal acts listed in Annex II, section A apply, when such legal acts already provide for procedures ensuring an equivalent level of protection and having the same objective. In such a case, these sectoral procedures shall apply instead

3b.     Without prejudice to the powers of market surveillance authorities under Article 14 of Regulation 2019/1020, for the purpose of ensuring the effective enforcement of this Regulation, market surveillance authorities may exercise the powers referred to in Article 14(4)(d) and (j) of Regulation 2019/1020 remotely as appropriate.

4. For high-risk AI systems placed on the market, put into service or used by financial institutions regulated by Union legislation on financial services, the market surveillance authority for the purposes of this Regulation shall be the relevant national authority responsible for the financial supervision of those institutions under that legislation in so far as the placement on the market, putting into service or the use of the AI system is in direct connection with the provision of those financial services.

4a.   By way of a derogation from the previous subparagraph, in justified circumstances and provided that coordination is ensured, another relevant authority may be identified by the Member State as market surveillance authority for the purposes of this Regulation.

National market surveillance authorities supervising regulated credit institutions regulated under Directive 2013/36/EU, which are participating in the Single Supervisory Mechanism (SSM) established by Council Regulation No 1204/2013, should report, without delay, to the European Central Bank any information identified in the course of their market surveillance activities that may be of potential interest for the European Central Bank’s prudential supervisory tasks as specified in that Regulation.

5. For high-risk AI systems listed in point 1 in so far as the systems are used for law enforcement purposes and for purposes listed in points 6, 7 and 8 of Annex III, Member States shall designate as market surveillance authorities for the purposes of this Regulation either the competent data protection supervisory authorities under Regulation 2016/679, or Directive (EU) 2016/680 or any other authority designated pursuant to the same condictions laid down in Articles 1 to 44 of Directive or Directive (EU) 2016/680. Market surveillance activities shall in no way affect the independence of judicial authorities or otherwise interfere with their activities when acting in their judicial capacity

6. Where Union institutions, agencies and bodies fall within the scope of this Regulation, the European Data Protection Supervisor shall act as their market surveillance authority except in relation to the Court of Justice acting in its judicial capacity.

7. Member States shall facilitate the coordination between market surveillance authorities designated under this Regulation and other relevant national authorities or bodies which supervise the application of Union harmonisation legislation listed in Annex II or other Union legislation that might be relevant for the high-risk AI systems referred to in Annex III.

7a.    Market surveillance authorities and the Commission shall be able to propose joint activities, including joint investigations, to be conducted by either market surveillance authorities or market surveillance authorities jointly with the Commission, that have the aim of promoting compliance, identifying non-compliance, raising awareness and providing guidance in relation to this Regulation with respect to specific categories of high-risk AI systems that are found to present a serious risk across several Member States in accordance with Article 9 of the 2019/1020. The AI Office shall provide coordination support for joint investigations.

7a.   Without prejudice to powers provided under Regulation (EU) 2019/1020, and where relevant and limited to what is necessary to fulfil their tasks, the market surveillance authorities shall be granted full access by the provider to the documentation as well as the training, validation and testing datasets used for the development of the high-risk AI system, including, where appropriate and subject to security safeguards, through application programming interfaces (‘API’) or other relevant technical means and tools enabling remote access.

7b.    Market surveillance authorities shall be granted access to the source code of the high-risk AI system upon a reasoned request and only when the following cumulative conditions are fulfilled:

  1. access to source code is necessary to assess the conformity of a high-risk AI system with the requirements set out in Title III, Chapter 2, and 
  2. testing/auditing procedures and verifications based on the data and documentation provided by the provider have been exhausted or proved insufficient.

7c.    Any information and documentation obtained by market surveillance authorities shall be treated in compliance with the confidentiality obligations set out in Article 70.

Article 63a   Mutual Assistance, market surveillance and control of general purpose AI systems

1. Where an AI system is based on a general purpose AI model and the model and the system are developed by the same provider, the AI office shall have powers to monitor and supervise compliance of this AI system with the obligations of this Regulation. To carry monitoring and supervision tasks the AI Office shall have all the powers of a market surveillance authority within the meaning of the Regulation 2019/1020. 

2. Where the relevant market surveillance authorities have sufficient reasons to consider that general purpose AI systems that can be used directly by deployers for at least one purpose that is classified as high-risk pursuant to this Regulation, is non-compliant with the requirements laid down in this Regulation, it shall cooperate with the AI Office to carry out evaluation of compliance and inform the Board and other market surveillance authorities accordingly. 

3. When a national market surveillance authority is unable to conclude its investigation on the high-risk AI system because of its inability to access certain information related to the AI model despite having made all appropriate efforts to obtain that information, it may submit a reasoned request to the AI Office where access to this information can be enforced. In this case the AI Office shall supply to the applicant authority without delay, and in any event within 30 days, any information that the AI Office considers to be relevant in order to establish whether a high-risk AI system is non-compliant. National market authorities shall safeguard the confidentiality of the information they obtain in accordance with the Article 70. The procedure provided in Chapter VI of the Regulation (EU) 1020/2019 shall apply by analogy.

Article 63b   Supervision of testing in real world conditions by market surveillance authorities

1. Market surveillance authorities shall have the competence and powers to ensure that testing in real world conditions is in accordance with this Regulation. 

2. Where testing in real world conditions is conducted for AI systems that are supervised within an AI regulatory sandbox under Article 54, the market surveillance authorities shall verify the compliance with the provisions of Article 54a as part of their supervisory role for the AI regulatory sandbox. Those authorities may, as appropriate, allow the testing in real world conditions to be conducted by the provider or prospective provider in derogation to the conditions set out in Article 54a(4) (f) and (g).

3. Where a market surveillance authority has been informed by the prospective provider, the provider or any third party of a serious incident or has other grounds for considering that the conditions set out in Articles 54a and 54b are not met, it may take any of the following decisions on its territory, as appropriate:

(a) suspend or terminate the testing in real world conditions;

(b) require the provider or prospective provider and user(s) to modify any aspect of the testing in real world conditions.

4. Where a market surveillance authority has taken a decision referred to in paragraph 3 of this Article or has issued an objection within the meaning of Article 54a(4)(b), the decision or the objection shall indicate the grounds thereof and the modalities and conditions for the provider or prospective provider to challenge the decision or objection.

5. Where applicable, where a market surveillance authority has taken a decision referred to in paragraph 3 of this Article, it shall communicate the grounds therefor to the market surveillance authorities of the other Member States in which the AI system has been tested in accordance with the testing plan.

Article 64   Powers of authorities protecting fundamental rights

3. National public authorities or bodies which supervise or enforce the respect of obligations under Union law protecting fundamental rights, including the right to non-discrimination, in relation to the use of high-risk AI systems referred to in Annex III shall have the power to request and access any documentation created or maintained under this Regulation in accesible language and format when access to that documentation is necessary for effectively fulfilling their mandate within the limits of their jurisdiction. The relevant public authority or body shall inform the market surveillance authority of the Member State concerned of any such request.

4. By three months after the entering into force of this Regulation, each Member State shall identify the public authorities or bodies referred to in paragraph 3 and make a list publicly available. Member States shall notify the list to the Commission and all other Member States and keep the list up to date.

5. Where the documentation referred to in paragraph 3 is insufficient to ascertain whether a breach of obligations under Union law intended to protect fundamental rights has occurred, the public authority or body referred to in paragraph 3 may make a reasoned request to the market surveillance authority, to organise testing of the high-risk AI system through technical means. The market surveillance authority shall organise the testing with the close involvement of the requesting public authority or body within reasonable time following the request.

6. Any information and documentation obtained by the national public authorities or bodies referred to in paragraph 3 pursuant to the provisions of this Article shall be treated in compliance with the confidentiality obligations set out in Article 70.

Article 65   Procedure for dealing with AI systems presenting a risk at national level

1. AI systems presenting a risk shall be understood as a product presenting a risk defined in Article 3, point 19 of Regulation (EU) 2019/1020 insofar as risks to the health or safety or to fundamental rights of persons are concerned.

2. Where the market surveillance authority of a Member State has sufficient reasons to consider that an AI system presents a risk as referred to in paragraph 1, it shall carry out an evaluation of the AI system concerned in respect of its compliance with all the requirements and obligations laid down in this Regulation. Particular attention shall be given to AI systems presenting a risk to vulnerable groups (referred to in Article 5). When risks to fundamental rights are identified, the market surveillance authority shall also inform and fully cooperate with the relevant national public authorities or bodies referred to in Article 64(3). The relevant operators shall cooperate as necessary with the market surveillance authority and the other national public authorities or bodies referred to in Article 64(3);

Where, in the course of that evaluation, the market surveillance authority and where applicable in cooperation with the national public authority referred to in Article 64(3) finds that the AI system does not comply with the requirements and obligations laid down in this Regulation, it shall without undue delay require the relevant operator to take all appropriate corrective actions to bring the AI system into compliance, to withdraw the AI system from the market, or to recall it within a period it may prescribe and in any event no later than fifteen working days or as provided for in the relevant Union harmonisation law as applicable

The market surveillance authority shall inform the relevant notified body accordingly. Article 18 of Regulation (EU) 2019/1020 shall apply to the measures referred to in the second subparagraph.

3. Where the market surveillance authority considers that non-compliance is not restricted to its national territory, it shall inform the Commission, and the other Member States without undue delay of the results of the evaluation and of the actions which it has required the operator to take.

5. Where the operator of an AI system does not take adequate corrective action within the period referred to in paragraph 2, the market surveillance authority shall take all appropriate provisional measures to prohibit or restrict the AI system’s being made available on its national market or put into service, to withdraw the product or the standalone AI system from that market or to recall it. That authority shall without undue delay notify the Commission and the other Member States of those measures.

6. The notification referred to in paragraph 5 shall include all available details, in particular the information necessary for the identification of the non-compliant AI system, the origin of the AI system and the supply chain, the nature of the non-compliance alleged and the risk involved, the nature and duration of the national measures taken and the arguments put forward by the relevant operator. In particular, (the market surveillance authorities) shall indicate whether the non-compliance is due to one or more of the following:

(-a)    non-compliance with the prohibition of the artificial intelligence practices referred to in Article 5;

(a) failure of a high-risk AI system to meet requirements set out in Title III, Chapter 2;

(ba)  non-compliance with provisions set out in Article 52;

7. The market surveillance authorities of the Member States other than the market surveillance authority of the Member State initiating the procedure shall without undue delay inform the Commission and the other Member States of any measures adopted and of any additional information at their disposal relating to the non-compliance of the AI system concerned, and, in the event of disagreement with the notified national measure, of their objections.

8. Where, within three months of receipt of the notification referred to in paragraph 5, no objection has been raised by either a market surveillance authority of a Member State or the Commission in respect of a provisional measure taken by a market surveillance authority of another Member State, that measure shall be deemed justified. This is without prejudice to the procedural rights of the concerned operator in accordance with Article 18 of Regulation (EU) 2019/1020. The period referred to in the first sentence of this paragraph shall be reduced to thirty days in the event of non-compliance with the prohibition of the artificial intelligence practices referred to in Article 5.

9. The market surveillance authorities of all Member States shall ensure that appropriate restrictive measures are taken in respect of the product or the AI system concerned, such as withdrawal of the product or the AI system from their market, without undue delay.

Article 65a   Procedure for dealing with AI systems classified by the provider as a not high-risk in application of Annex III

1. Where a market surveillance authority has sufficient reasons to consider that an AI system classified by the provider as non high-risk in application of Annex III is high-risk, they market surveillance authority shall carry out an evaluation of the AI system concerned in respect of its classification as a high-risk AI system based on the conditions set out in Annex III and the Commission guidelines.

2. Where, in the course of that evaluation, the market surveillance authority finds that the AI system concerned is high-risk, it shall without undue delay require the relevant provider to take all necessary actions to bring the AI system into compliance with the requirements and obligations laid down in this Regulation as well as take appropriate corrective action within a period it may prescribe.

3. Where the market surveillance authority considers that the use of the AI system concerned is not restricted to its national territory, it shall inform the Commission and the other Member States without undue delay of the results of the evaluation and of the actions which it has required the provider to take.

4. The provider shall ensure that all necessary action is taken to bring the AI system into compliance with the requirements and obligations laid down in this Regulation. Where the provider of an AI system concerned does not bring the AI system into compliance with the requirements and obligations of this Regulation within the period referred to in paragraph 2, the provider shall be subject to fines in accordance with Article 71.

5. The provider shall ensure that all appropriate corrective action is taken in respect of all the AI systems concerned that it has made available on the market throughout the Union.

6. Where the provider of the AI system concerned does not take adequate corrective action within the period referred to in paragraph 2, then the provisions of Article 65 paragraphs 5 to 9 apply.

7. Where, in the course of that evaluation pursuant to paragraph 1, the market surveillance authority establishes that the AI system was misclassified by the provider as not high-risk to circumvent the application of requirements in Title III, Chapter 2, the provider shall be subject to fines in accordance with Article 71.

8. In exercising their power to monitor the application of this article and in accordance with Article 11 of Regulation (EU) 2019/1020, market surveillance authorities may perform appropriate checks, taking into account in particular information stored in the EU database referred to in Article 60.

1. Where, within three months of receipt of the notification referred to in Article 65(5), or 30 days in the case of non-compliance with the prohibition of the artificial intelligence practices referred to in Article 5, objections are raised by the market surveillance authority of a Member State against a measure taken by another market surveillance authority, or where the Commission considers the measure to be contrary to Union law, the Commission shall without undue delay enter into consultation with the market surveillance authority of the relevant Member State and operator or operators and shall evaluate the national measure. On the basis of the results of that evaluation, the Commission shall decide whether the national measure is justified or not within six months, or 60 days in the case of non-compliance with the prohibition of the artificial intelligence practices referred to in Article 5, starting from the notification referred to in Article 65(5) and notify such decision to the market surveillance authority of the Member State concerned. The Commission shall also inform all other market surveillance authorities of such decision.

2. If the measure taken by the relevant Member States is considered justified by the Commission, all Member States shall ensure that appropriate restrictive measures are taken in respect of the AI system concerned, such as withdrawal of the AI system from their market without undue delay, and shall inform the Commission accordingly. If the national measure is considered unjustified by the Commission, the Member State concerned shall withdraw the measure and inform the Commission accordingly.

3. Where the national measure is considered justified and the non-compliance of the AI system is attributed to shortcomings in the harmonised standards or common specifications referred to in Articles 40 and 41 of this Regulation, the Commission shall apply the procedure provided for in Article 11 of Regulation (EU) No 1025/2012.

Article 67  Compliant AI systems which present a risk

1. Where, having performed an evaluation under Article 65, after consulting the relevant national public authority referred to in Article 64(3), the market surveillance authority of a Member State finds that although a high-risk AI system is in compliance with this Regulation, it presents a risk to the health or safety of persons, fundamental rights, or to other aspects of public interest protection, it shall require the relevant operator to take all appropriate measures to ensure that the AI system concerned, when placed on the market or put into service, no longer presents that risk without undue delay, within a period it may prescribe.

2. The provider or other relevant operators shall ensure that corrective action is taken in respect of all the AI systems concerned that they have made available on the market throughout the Union within the timeline prescribed by the market surveillance authority of the Member State referred to in paragraph 1.

3. The Member States shall immediately inform the Commission and the other Member States. That information shall include all available details, in particular the data necessary for the identification of the AI system concerned, the origin and the supply chain of the AI system, the nature of the risk involved and the nature and duration of the national measures taken.

4. The Commission shall without undue delay enter into consultation with the Member States concerned and the relevant operator and shall evaluate the national measures taken. On the basis of the results of that evaluation, the Commission shall decide whether the measure is justified or not and, where necessary, propose appropriate measures.

5. The Commission shall immediately communicate its decision to the Member States concerned and to the relevant operators. It shall also inform of the decision all other Member States.

1. Where the market surveillance authority of a Member State makes one of the following findings, it shall require the relevant provider to put an end to the non-compliance concerned, within a period it may prescribe:

(a) the CE marking has been affixed in violation of Article 49;

(b) the CE marking has not been affixed;

(ea)  the registration in the EU database has not been carried out;

(eb) where applicable, the authorised representative has not been appointed.

(ec) the technical documentation is not available

2. Where the non-compliance referred to in paragraph 1 persists, the market surveillance authority of the Member State concerned shall take appropriate and proportionate measures to restrict or prohibit the high-risk AI system being made available on the market or ensure that it is recalled or withdrawn from the market without delay.

Article 68a   EU AI testing support structures in the area of artificial intelligence

1. The Commission shall designate one or more EU AI testing support structures to perform the tasks listed under Article 21(6) of Regulation (EU) 1020/2019 in the area of artificial intelligence.

2. Without prejudice to the tasks referred to in paragraph 1, EU AI testing support structure shall also provide independent technical or scientific advice at the request of the Board, the Commission, or market surveillance authorities.

Chapter 3b(new) Remedies

Article 68 a  Right to lodge a complaint with a market surveillance authority

1. Without prejudice to other administrative or judicial remedies, complaints to the relevant market surveillance authority may be submitted by any natural or legal person having grounds to consider that there has been an infringement of the provisions of this Regulation. In accordance with Regulation (EU) 2019/1020, complaints shall be taken into account for the purpose of conducting the market surveillance activities and be handled in line with the dedicated procedures established therefore by the market surveillance authorities

Chapter I   Supervision, investigation, enforcement and monitoring in respect of providers of general purpose AI Models

Article A Enforcement of obligations on providers of general purpose AI models 

1. The Commission shall have exclusive powers to supervise and enforce Chapter/Title [general purpose AI models] taking into account the procedural guarantees by virtue of Article H. The Commission shall entrust the implementation of these tasks to the European AI Office, without prejudice to the powers of organisation of the Commission and the division of competences between Member States and the Union based on the Treaties. 

2. Without prejudice to Article 63a paragraph 3, market surveillance authorities may request to the Commission to exercise the powers laid down in this Chapter, where this is necessary and proportionate to assist with the fulfilment of their tasks under this Regulation.

Article B Monitoring actions 

For the purposes of carrying out the tasks assigned to it under this Chapter, the AI Office may take the necessary actions to monitor the effective implementation and compliance with this Regulation by providers of general purpose AI models, including adherence to approved codes of practice. 2.

Downstream providers shall have the right to lodge a complaint alleging an infringement of this Regulation. A complaint shall be duly reasoned and at least indicate: (a) the point of contact of the provider of the general purpose AI model concerned; (b) description of the relevant facts, the provisions of this Regulation concerned and the reason why the downstream provider considers that the provider of the general purpose AI model concerned infringed this Regulation; (c) any other information that the downstream provider that sent the request considers relevant, including, where appropriate, information gathered on its own initiative.

Article C Alerts of systemic risks by the scientific panel 

1. The scientific panel may provide a qualified alert to the AI Office where it has reason to suspect that (a) a general purpose AI model poses concrete identifiable risk at Union level; or (b) a general purpose AI model meets the requirements referred to in Article [Classification of general purpose AI models with systemic risk…].

2. Upon such qualified alert, the Commission, through the AI Office and after having informed the AI Board, may exercise the powers laid down in this Chapter for the purpose of assessing the matter. The AI Office shall inform the Board of any measure according to Articles [D-H]. 

3. A qualified alert shall be duly reasoned and at least indicate: (a) the point of contact of the provider of the general purpose AI model with systemic risk concerned; (b) a description of the relevant facts and reasons for the suspicion of the scientific panel; (c) any other information that the scientific panel considers relevant, including, where appropriate, information gathered on its own initiative.

Article D  Power to request documentation and information 

1. The Commission may request the provider of the general purpose AI model concerned to provide the documentation drawn up by the provider according to Article [Obligations for providers of general purpose AI models] and [Obligations on providers of general purpose AI models with systemic risk] or any additional information that is necessary for the purpose of assessing compliance of the provider with this Regulation.

2. Before the request for information is sent, the AI Office may initiate a structured dialogue with the provider of the general purpose AI model. 

3. Upon a duly substantiated request from the scientific panel, the Commission may issue a request for information to a provider of a general purpose AI model, where the access to information is necessary and proportionate for the fulfilment of the tasks of the scientific panel according to Article [Scientific panel](2).

4. The request for information shall state the legal basis and the purpose of the request, specifying what information is required and set the period within which the information is to be provided, and the fines provided for in Article [fines] for supplying incorrect, incomplete or misleading information. 5.    The provider of the general purpose AI model concerned or their representatives and, in the case of legal persons, companies or firms, or where they have no legal personality, the persons authorised to represent them by law or by their constitution shall supply the information requested on behalf of the provider of the general purpose AI model concerned. Lawyers duly authorised to act may supply the information on behalf of their clients. The latter shall remain fully responsible if the information supplied is incomplete, incorrect or misleading.

Article E Power to conduct evaluations 

1. The AI Office, after consulting the Board, may conduct evaluations of the general purpose AI model concerned (a) to assess compliance of the provider with the obligations under this Regulation, where the information gathered pursuant to Article D [Power to request information] is insufficient; or (b) to investigate systemic risks at Union level of general purpose AI models with systemic risk, in particular following a qualified report from the scientific panel in accordance with point (c) of Article [Enforcement of obligations on providers of general purpose AI models and general purpose AI models with systemic risk](3) .

2. The Commission may decide to appoint independent experts to carry out evaluations on its behalf, including from the scientific panel pursuant to Article [scientific panel of independent experts]. All independent experts appointed for this task shall meet the criteria outlined in Article 58b, paragraph 2. 

3. For the purpose of paragraph 1, the Commission may request access to the general purpose AI model concerned through application programming interfaces (‘API’) or further appropriate technical means and tools, including through source code.

4. The request for access shall state the legal basis, the purpose and reasons of the request and set the period within which the access is to be provided, and the fines provided for in Article [fines] for failure to provide access.

5. The providers of the general purpose AI model concerned and, in the case of legal persons, companies or firms, or where they have no legal personality, the persons authorised to represent them by law or by their constitution shall provide the access requested on behalf of the provider of the general purpose AI model concerned.

6. The modalities and the conditions of the evaluations, including the modalities for involving independent experts and the procedure for the selection of the latter, shall be set out in implementing acts. Those implementing acts shall be adopted in accordance with the examination procedure referred to in Article xx(x). 

7. Prior to requesting access to the general purpose AI model concerned, the AI Office may initiate a structured dialogue with the provider of the general purpose AI model to gather more information on the internal testing of the model, internal safeguards for preventing systemic risks, and other internal procedures and measures the provider has taken to mitigate such risks.

Article F Power to request measures 

1. Where necessary and appropriate, the Commission may request providers to (a) take appropriate measures to comply with the obligations set out in Title/Chapter [Obligations for provider of general purpose AI models]; (b) require a provider to implement mitigation measures, where the evaluation carried out in accordance with Article [Power to conduct evaluations] has given rise to serious and substantiated concern of a systemic risk at Union level; (c) restrict the making available on the market, withdraw or recall the model.  

2. Before a measure is requested, the AI Office may initiate a structured dialogue with the provider of the general purpose AI model. 

3. If, during the structured dialogue under paragraph 2, the provider of the general purpose AI model with systemic risk offers commitments to implement mitigation meausres to address a systemic risk at Union level, the Commission may by decision make these commitments binding and declare that there are no further grounds for action.

Article H Procedural rights of economic operators of the general purpose AI model 

Article 18 of the Regulation (EU) 2019/1020 apply by analogy to the providers of the general purpose AI model without prejudice to more specific procedural rights provided for in this Regulation.

Article 68 c A right to explanation of individual decision-making

1. Any affected person subject to a decision which is taken by the deployer on the basis of the output from an high-risk AI system listed in Annex III, with the exception of systems listed under point 2, and which produces legal effects or similarly significantly affects him or her in a way that they consider to adversely impact their health, safety and fundamental rights shall have the right to request from the deployer clear and meaningful explanations on the role of the AI system in the decision-making procedure and the main elements of the decision taken.

2. Paragraph 1 shall not apply to the use of AI systems for which exceptions from, or restrictions to, the obligation under paragraph 1 follow from Union or national law in compliance with Union law. 3. . This Article shall only apply to the extent that the right referred to in paragraph 1 is not already provided for under Union legislation.

Article 68 d  Amendment to Directive (EU) 2020/1828 

In Annex I to Directive (EU) 2020/1828 of the European Parliament and of the Council 1a, the following point is added: “(67a) Regulation xxxx/xxxx of the European Parliament and of the Council [laying down harmonised rules on artificial intelligence (Artificial Intelligence Act) and amending certain Union legislative acts (OJ L …)]”.             1a Directive (EU) 2020/1828 of the European Parliament and of the Council of 25 November 2020 on representative actions for the protection of the collective interests of consumers and repealing Directive 2009/22/EC (OJ L 409, 4.12.2020, p. 1).

Article 68 e   Reporting of breaches and protection of reporting persons 

Directive (EU) 2019/1937 of the European Parliament and of the Council shall apply to the reporting of breaches of this Regulation and the protection of persons reporting such breaches.

TITLE IX CODES OF CONDUCT

Article 69   Codes of conduct for voluntary application of specific requirements

1. The AI Office, and the Member States shall encourage and facilitate the drawing up of codes of conduct, including related governance mechanisms, intended to foster the voluntary application to AI systems other than high-risk AI systems of some or all of the requirements set out in Title III, Chapter 2 of this Regulation taking into account the available technical solutions and industry best practices allowing for the application of such requirements.

2. The AI Office and the Member States shall facilitate the drawing up of codes of conduct concerning the voluntary application, including by deployers, of specific requirements to all AI systems, on the basis of clear objectives and key performance indicators to measure the achievement of those objectives, including elements such as, but not limited to: (a) applicable elements foreseen in European ethic guidelines for trustworthy AI;   (b) assessing and minimizing the impact of AI systems on environmental sustainability, including as regards energy-efficient programming and techniques for efficient design, training and use of AI; (c) promoting AI literacy, in particular of persons dealing with the development, operation and use of AI; (d) facilitating an inclusive and diverse design of AI systems, including through the establishment of inclusive and diverse development teams and the promotion of stakeholders’ participation in that process; (e) assessing and preventing the negative impact of AI systems on vulnerable persons or groups of persons, including as regards accessibility for persons with a disability, as well as on gender equality.

3. Codes of conduct may be drawn up by individual providers or deployers of AI systems or by organisations representing them or by both, including with the involvement of deployers and any interested stakeholders and their representative organisations, including civil society organisations and academia. Codes of conduct may cover one or more AI systems taking into account the similarity of the intended purpose of the relevant systems.

4. The AI Office, and the Member States shall take into account the specific interests and needs of SMEs, including start-ups, when encouraging and facilitating the drawing up of codes of conduct.

TITLE X   CONFIDENTIALITY AND PENALTIES

Article 70   Confidentiality

1. The Commission, market surveillance authorities and notified bodies and any other natural or legal person involved in the application of this Regulation shall, in accordance with Union or national law, respect the confidentiality of information and data obtained in carrying out their tasks and activities in such a manner as to protect, in particular;

(a) intellectual property rights, and confidential business information or trade secrets of a natural or legal person, including source code, except the cases referred to in Article 5 of Directive 2016/943 on the protection of undisclosed know-how and business information (trade secrets) against their unlawful acquisition, use and disclosure apply;

(b) the effective implementation of this Regulation, in particular for the purpose of inspections, investigations or audits;

(ba)  public and national security interests

(c) integrity of criminal or administrative proceedings.

(da) the integrity of information classified in accordance with Union or national law.

(db) 1a. The authorities involved in the application of this Regulation pursuant to paragraph 1 shall only request data that is strictly necessary for the assessment of the risk posed by the AI system and for the exercise of their powers in compliance with this Regulation and Regulation 2019/1020. They shall put in place adequate and effective cybersecurity measures to protect the security and confidentiality of the information and data obtained and shall delete the data collected as soon as it is no longer needed for the purpose it was requested for, in accordance with applicable national or European legislation .

2. Without prejudice to paragraph 1 and 1a, information exchanged on a confidential basis between the national competent authorities and between national competent authorities and the Commission shall not be disclosed without the prior consultation of the originating national competent authority and the deployer when high-risk AI systems referred to in points 1, 6 and 7 of Annex III are used by law enforcement, border control, immigration or asylum authorities, when such disclosure would jeopardise public and national security interests. This exchange of information shall not cover sensitive operational data in relation to the activities of law enforcement, border control, immigration or asylum authorities.

When the law enforcement, immigration or asylum authorities are providers of high-risk AI systems referred to in points 1, 6 and 7 of Annex III, the technical documentation referred to in Annex IV shall remain within the premises of those authorities. Those authorities shall ensure that the market surveillance authorities referred to in Article 63(5) and (6), as applicable, can, upon request, immediately access the documentation or obtain a copy thereof. Only staff of the market surveillance authority holding the appropriate level of security clearance shall be allowed to access that documentation or any copy thereof.

3. Paragraphs 1, [1a] and 2 shall not affect the rights and obligations of the Commission, Member States and their relevant authorities, as well as notified bodies, with regard to the exchange of information and the dissemination of warnings, including in the context of cross-border cooperation, nor the obligations of the parties concerned to provide information under criminal law of the Member States.

4. The Commission and Member States may exchange, where necessary and in accordance with relevant provisions of international and trade agreements, confidential information with regulatory authorities of third countries with which they have concluded bilateral or multilateral confidentiality arrangements guaranteeing an adequate level of confidentiality.

Article 71   Penalties

1. In compliance with the terms and conditions laid down in this Regulation, Member States shall lay down the rules on penalties and other enforcement measures, which may also include warnings and non-monetary measures, applicable to infringements of this Regulation by operators, and shall take all measures necessary to ensure that they are properly and effectively implemented and taking into account the guidelines issued by the Commission pursuant to Article 82b. The penalties provided for shall be effective, proportionate, and dissuasive. They shall take into account the interests of SMEs including start-ups and their economic viability.

2. The Member States shall without delay notify the Commission and at the latest by the date of entry into application of those respective rules and of those respective measures and shall notify them, without delay, of any subsequent amendment affecting them.

3. Non compliance with the prohibition of the artificial intelligence practices referred to in Article 5 shall be subject to administrative fines of up to 35 000 000 EUR or, if the offender is a company, up to 7 % of its total worldwide annual turnover for the preceding financial year, whichever is higher:

4. Non-compliance of an AI system with any of the following provisions related to operators or notified bodies, other than those laid down in Articles 5, shall be subject to administrative fines of up to 15 000 000 EUR or, if the offender is a company, up to 3% of its total worldwide annual turnover for the preceding financial year, whichever is higher:

(b)   obligations of providers pursuant to Article 16;

(d) obligations of authorised representatives pursuant to Article 25;

(e) obligations of importers pursuant to Article 26;

(f) obligations of distributors pursuant to Article 27;

(g) obligations of deployers pursuant to Article 29, paragraphs 1 to 6a;

(h) requirements and obligations of notified bodies pursuant to Article 33, 34(1), 34(3), 34(4), 34a;

(i) transparency obligations for providers and users pursuant to Article 52.

5. The supply of incorrect, incomplete or misleading information to notified bodies and national competent authorities in reply to a request shall be subject to administrative fines of up to 7 500 000 EUR or, if the offender is a company, up to 1 % of its total worldwide annual turnover for the preceding financial year, whichever is higher.

5a. In case of SMEs, including start-ups, each fine referred to in this Article shall be up to the percentages or amount referred to paragraphs 3, 4 and 5, whichever of the two is lower.

6. When deciding whether to impose an administrative fine and on the amount of the administrative fine in each individual case, all relevant circumstances of the specific situation shall be taken into account and, as appropriate, regard shall be given to the following:

(a) the nature, gravity and duration of the infringement and of its consequences, taking into account the purpose of the AI system, as well as, where appropriate, the number of affected persons and the level of damage suffered by them;

(b) whether administrative fines have been already applied by other market surveillance authorities of one or more Member States to the same operator for the same infringement;

(ba) whether administrative fines have been already applied by other authorities to the same operator for infringements of other Union or national law, when such infringements result from the same activity or omission constituting a relevant infringement of this Act;

(c) the size, the annual turnover and market share of the operator committing the infringement;

(ca) any other aggravating or mitigating factor applicable to the circumstances of the case, such as financial benefits gained, or losses avoided, directly or indirectly, from the infringement.

(ca) the degree of cooperation with the national competent authorities, in order to remedy the infringement and mitigate the possible adverse effects of the infringement;

(cb) the degree of responsibility of the operator taking into account the technical and organisational measures implemented by them;

(ce) the manner in which the infringement became known to the national competent authorities, in particular whether, and if so to what extent, the operator notified the infringement;

(cf)  the intentional or negligent character of the infringement;

(cg) any action taken by the operator to mitigate the harm of damage suffered by the affected persons;

7. Each Member State shall lay down rules on to what extent administrative fines may be imposed on public authorities and bodies established in that Member State.

8. Depending on the legal system of the Member States, the rules on administrative fines may be applied in such a manner that the fines are imposed by competent national courts or other bodies as applicable in those Member States. The application of such rules in those Member States shall have an equivalent effect.

8a.  The exercise by the market surveillance authority of its powers under this Article shall be subject to appropriate procedural safeguards in accordance with Union and Member State law, including effective judicial remedy and due process.

8b.   Member States shall, on an annual basis, report to the Commission about the administrative fines they have issued during that year, in accordance with this Article, and any related litigation or judicial proceedings;

Article 72   Administrative fines on Union institutions, agencies and bodies

1. The European Data Protection Supervisor may impose administrative fines on Union institutions, agencies and bodies falling within the scope of this Regulation. When deciding whether to impose an administrative fine and deciding on the amount of the administrative fine in each individual case, all relevant circumstances of the specific situation shall be taken into account and due regard shall be given to the following:

(a) the nature, gravity and duration of the infringement and of its consequences;, taking into account the purpose of the AI system concerned as well as the number of affected persons and the level of damage suffered by them, and any relevant previous infringement;

(aa) the degree of responsibility of the Union institution, agency or body, taking into account technical and organisational measures implemented by them;

(ab) any action taken by the Union institution, agency or body to mitigate the damage suffered by affected persons;

(b) the degree of cooperation with the European Data Protection Supervisor in order to remedy the infringement and mitigate the possible adverse effects of the infringement, including compliance with any of the measures previously ordered by the European Data Protection Supervisor against the Union institution or agency or body concerned with regard to the same subject matter;

(c) any similar previous infringements by the Union institution, agency or body;

(ca) the manner in which the infringement became known to the European Data Protection Supervisor, in particular whether, and if so to what extent, the Union institution or body notified the infringement;

(cb)  the annual budget of the body;

2. Non compliance with the prohibition of the artificial intelligence practices referred to in Article 5 shall be subject to administrative fines of up to EUR 1 500 000.

(a) deleted (aa) deleted

(b) deleted

3. the non-compliance of the AI system with any requirements or obligations under this Regulation, other than those laid down in Articles 5, shall be subject to administrative fines of up to EUR 750 000.

4. Before taking decisions pursuant to this Article, the European Data Protection Supervisor shall give the Union institution, agency or body which is the subject of the proceedings conducted by the European Data Protection Supervisor the opportunity of being heard on the matter regarding the possible infringement. The European Data Protection Supervisor shall base his or her decisions only on elements and circumstances on which the parties concerned have been able to comment. Complainants, if any, shall be associated closely with the proceedings.

5. The rights of defense of the parties concerned shall be fully respected in the proceedings. They shall be entitled to have access to the European Data Protection Supervisor’s file, subject to the legitimate interest of individuals or undertakings in the protection of their personal data or business secrets.

6. Funds collected by imposition of fines in this Article shall contribute to the general budget of the Union. The fines shall not affect the effective operation of the Union institution, body or agency fined.

6a.   the European Data Protection Supervisor shall, on an annual basis, notify the Commission of the administrative fines it has imposed pursuant to this Article and any litigation or judicial proceedings;

Article 72a   Fines for providers of general purpose AI models

1. The Commission may impose on providers of general purpose AI models fines not exceeding 3% of its total worldwide turnover in the preceding financial year or 15 million EUR whichever is higher. Fines should be imposed one year after the entry into application of the relevant provisions in this Regulation in order to allow providers sufficient time to adapt when the Commission finds that the provider intentionally or negligently:

(a) infringes the relevant provisions of this Regulation;

(b) fails to comply with a request for document or information pursuant to Article [Power to request documentation and information], or supply of incorrect, incomplete or misleading information;

(b) fails to comply with a measure requested under Article [Power to request measures];

(c) fails to make available to the Commission access to the general purpose AI model or general purpose AI model with systemic risk with a view to conduct an evaluation pursuant to Article [Power to conduct evaluations].

In fixing the amount of the fine or periodic penalty payment, regard shall be had to the nature, gravity and duration of the infringement, taking due account of the principles of proportionality and appropriateness. The Commission shall also into account commitments made in accordance with Article F(3) or in relevant codes of practice in accordance with Article [Codes of practice].

2. Before adopting the decision pursuant to paragraph 1 of this Article, the Commission shall communicate its preliminary findings to the provider of the general purpose AI model or general purpose AI model with systemic risk and give opportunity to be heard.

2a.  Fines imposed in accordance with this article shall be proportionate, dissuasive and effective.

2b.  The information on the fines shall be also communicated to the Board as appropriate.

3. The Court of Justice of the European Union shall have unlimited jurisdiction to review decisions whereby the Commission has fixed a fine. It may cancel, reduce or increase the fine imposed.

4. The Commission shall adopt implementing acts concerning the modalities and      practical arrangements for the proceedings in view of possible adoptions of decisions pursuant      to paragraph 1. Those implementing acts shall be adopted in accordance with the examination procedure referred to in Article xx(x).

TITLE XI   DELEGATION OF POWER AND COMMITTEE PROCEDURE

Article 73   Exercise of the delegation

1. The power to adopt delegated acts is conferred on the Commission subject to the conditions laid down in this Article.

2. The power to adopt delegated acts referred to in [Article 4, Article 7(1), Article 11(3), Article 43(5) and (6) and Article 48(5)] shall be conferred on the Commission for a period of five years from … [the date of entry into force of the Regulation].The Commission shall draw up a report in respect of the delegation of power not later than 9 months before the end of the five-year period. The delegation of power shall be tacitly extended for periods of an identical duration, unless the European Parliament or the Council opposes such extension not later than three months before the end of each period.

3. The delegation of power referred to in {Article 7(1), Article 7(3), Article 11(3), Article 43(5) and (6) and Article 48(5)] may be revoked at any time by the European Parliament or by the Council. A decision of revocation shall put an end to the delegation of power specified in that decision. It shall take effect the day following that of its publication in the Official Journal of the European Union or at a later date specified therein. It shall not affect the validity of any delegated acts already in force.

4. As soon as it adopts a delegated act, the Commission shall notify it simultaneously to the European Parliament and to the Council.

5. Any delegated act adopted pursuant to [Article 4], Article 7(1), Article 11(3), Article 43(5) and (6) and Article 48(5) shall enter into force only if no objection has been expressed by either the European Parliament or the Council within a period of three months of notification of that act to the European Parliament and the Council or if, before the expiry of that period, the European Parliament and the Council have both informed the Commission that they will not object. That period shall be extended by three months at the initiative of the European Parliament or of the Council.

Article 74   Committee procedure

1. The Commission shall be assisted by a committee. That committee shall be a committee within the meaning of Regulation (EU) No 182/2011.

2. Where reference is made to this paragraph, Article 5 of Regulation (EU) No 182/2011 shall apply.

TITLE XII  FINAL PROVISIONS

Article 75   Amendment to Regulation (EC) No 300/2008

In Article 4(3) of Regulation (EC) No 300/2008, the following subparagraph is added:

“When adopting detailed measures related to technical specifications and procedures for approval and use of security equipment concerning Artificial Intelligence systems in the meaning of Regulation (EU) YYY/XX [on Artificial Intelligence] of the European Parliament and of the Council*, the requirements set out in Chapter 2, Title III of that Regulation shall be taken into account.”

* Regulation (EU) YYY/XX [on Artificial Intelligence] (OJ …).”“

Article 76   Amendment to Regulation (EU) No 167/2013

In Article 17(5) of Regulation (EU) No 167/2013, the following subparagraph is added:

“When adopting delegated acts pursuant to the first subparagraph concerning artificial intelligence systems which are safety components in the meaning of Regulation (EU) YYY/XX [on Artificial Intelligence] of the European Parliament and of the Council*, the requirements set out in Title III, Chapter 2 of that Regulation shall be taken into account.

* Regulation (EU) YYY/XX [on Artificial Intelligence] (OJ …).”

Article 77   Amendment to Regulation (EU) No 168/2013

In Article 22(5) of Regulation (EU) No 168/2013, the following subparagraph is added: “           When adopting delegated acts pursuant to the first subparagraph concerning Artificial Intelligence systems which are safety components in the meaning of Regulation (EU) YYY/XX on [Artificial Intelligence] of the European Parliament and of the Council*, the requirements set out in Title III, Chapter 2 of that Regulation shall be taken into account.

* Regulation (EU) YYY/XX [on Artificial Intelligence] (OJ …).”

Article 78  Amendment to Directive 2014/90/EU

In Article 8 of Directive 2014/90/EU, the following paragraph is added:

“4. “For Artificial Intelligence systems which are safety components in the meaning of Regulation (EU) YYY/XX [on Artificial Intelligence] of the European Parliament and of the Council*, when carrying out its activities pursuant to paragraph 1 and when adopting technical specifications and testing standards in accordance with paragraphs 2 and 3, the Commission shall take into account the requirements set out in Title III, Chapter 2 of that Regulation.

* Regulation (EU) YYY/XX [on Artificial Intelligence] (OJ …).”.

         

Article 79   Amendment to Directive (EU) 2016/797

In Article 5 of Directive (EU) 2016/797, the following paragraph is added: “12. “When adopting delegated acts pursuant to paragraph 1 and implementing acts pursuant to paragraph 11 concerning Artificial Intelligence systems which are safety components in the meaning of Regulation (EU) YYY/XX [on Artificial Intelligence] of the European Parliament and of the Council*, the requirements set out in Title III, Chapter 2 of that Regulation shall be taken into account.

* Regulation (EU) YYY/XX [on Artificial Intelligence] (OJ …).”.

         

Article 80   Amendment to Regulation (EU) 2018/858

In Article 5 of Regulation (EU) 2018/858 the following paragraph is added: “4.

“When adopting delegated acts pursuant to paragraph 3 concerning Artificial Intelligence systems which are safety components in the meaning of Regulation (EU) YYY/XX [on Artificial Intelligence] of the European Parliament and of the Council *, the requirements set out in Title III, Chapter 2 of that Regulation shall be taken into account.

* Regulation (EU) YYY/XX [on Artificial Intelligence] (OJ …).”.

         

Article 81  Amendment to Regulation (EU) 2018/1139

Regulation (EU) 2018/1139 is amended as follows:

(1) In Article 17, the following paragraph is added: “3.

“Without prejudice to paragraph 2, when adopting implementing acts pursuant to paragraph 1 concerning Artificial Intelligence systems which are safety components in the meaning of Regulation (EU) YYY/XX [on Artificial Intelligence] of the European Parliament and of the Council*, the requirements set out in Title III, Chapter 2 of that Regulation shall be taken into account.

* Regulation (EU) YYY/XX [on Artificial Intelligence] (OJ …).”

(2) In Article 19, the following paragraph is added:

“4.     When adopting delegated acts pursuant to paragraphs 1 and 2 concerning Artificial Intelligence systems which are safety components in the meaning of Regulation (EU) YYY/XX [on Artificial Intelligence], the requirements set out in Title III, Chapter 2 of that Regulation shall be taken into account.”

(3) In Article 43, the following paragraph is added:

“4.     When adopting implementing acts pursuant to paragraph 1 concerning Artificial Intelligence systems which are safety components in the meaning of Regulation (EU) YYY/XX [on Artificial Intelligence], the requirements set out in Title III, Chapter 2 of that Regulation shall be taken into account.”

(4) In Article 47, the following paragraph is added:

“3.     When adopting delegated acts pursuant to paragraphs 1 and 2 concerning Artificial Intelligence systems which are safety components in the meaning of Regulation (EU) YYY/XX [on Artificial Intelligence], the requirements set out in Title III, Chapter 2 of that Regulation shall be taken into account.”

(5) In Article 57, the following paragraph is added:

“        When adopting those implementing acts concerning Artificial Intelligence systems which are safety components in the meaning of Regulation (EU) YYY/XX [on Artificial Intelligence], the requirements set out in Title III, Chapter 2 of that Regulation shall be taken into account.”

(6) In Article 58, the following paragraph is added:

“3.     When adopting delegated acts pursuant to paragraphs 1 and 2 concerning Artificial Intelligence systems which are safety components in the meaning of Regulation (EU) YYY/XX [on Artificial Intelligence] , the requirements set out in Title III, Chapter 2 of that Regulation shall be taken into account..”

Article 82   Amendment to Regulation (EU) 2019/2144

In Article 11 of Regulation (EU) 2019/2144, the following paragraph is added: ”3.

“When adopting the implementing acts pursuant to paragraph 2, concerning artificial intelligence systems which are safety components in the meaning of Regulation (EU) YYY/XX [on Artificial Intelligence] of the European Parliament and of the Council*, the requirements set out in Title III, Chapter 2 of that Regulation shall be taken into account.

* Regulation (EU) YYY/XX [on Artificial Intelligence] (OJ …)..

Article 82a   Guidelines from the Commission on the implementation of this Regulation

1. The Commission shall develop guidelines on the practical implementation of this Regulation, and in particular on:

(a) the application of the requirements and obligations referred to in Articles 8 – 15 and Article 28;

(b) the prohibited practices referred to in Article 5;

(c) the practical implementation of the provisions related to substantial modification;

(d) the practical implementation of transparency obligations laid down in Article 52;

(e) detailed information on the relationship of this Regulation with the legislation referred to in Annex II of this Regulation as well as other relevant Union law, including as regards consistency in their enforcement;

(f) the application of the definition of an AI system as set out in Article 3(1).

When issuing such guidelines, the Commission shall pay particular attention to the needs of SMEs including start-ups, local public authorities and sectors most likely to be affected by this Regulation.

The guidelines referred to in the first subparagraph shall take due account of the generally acknowledged state of the art on AI, as well as of relevant harmonised standards and common specifications that are referred to in Articles 40 and 41, or of those harmonised standards or technical specifications that are set out pursuant to Union harmonisation law.

2. Upon request of the Member States or the AI Office, or on its own initiative, the Commission shall update already adopted guidelines when deemed necessary.

Article 83   AI systems already placed on the market or put into service

1. Without prejudice to the application of Article 5 as referred in Article 85 (3) (-aa) AI systems which are components of the large-scale IT systems established by the legal acts listed in Annex IX that have been placed on the market or put into service before 12 months after the date of application of this Regulation referred to in Article 85(2) shall be brought into compliance with this Regulation by end of 2030.

The requirements laid down in this Regulation shall be taken into account in the evaluation of each large-scale IT systems established by the legal acts listed in Annex IX to be undertaken as provided for in those respective acts and whenever those legal acts are replaced or amended.

2. Without prejudice to the application of Article 5 as referred in Article 85 (3) (-aa ) this Regulation shall apply to operators of high-risk AI systems, other than the ones referred to in paragraph 1, that have been placed on the market or put into service before [date of application of this Regulation referred to in Article 85(2)], only if, from that date, those systems are subject to significant changes in their designs. In the case of high-risk AI systems intended to be used by public authorities, providers and deployers of such systems shall take the necessary steps to comply with the requirements of the present Regulation four years after the date of entry into application of this Regulation.

3. Providers of general-purpose AI models that have been placed on the market before [date of application of this Regulation referred to in point a) Article 85(3)] shall take the necessary steps in order to comply with the obligations laid down in this Regulation by [2 years after the date of entry into application of this Regulation referred to in point a) of 85(3)].

Article 84   Evaluation and review

1. The Commission shall assess the need for amendment of the list in Annex III, the list of prohibited AI practices in Article 5, once a year following the entry into force of this Regulation, and until the end of the period of the delegation of power. The Commission shall submit the findings of that assessment to the European Parliament and the Council.

2. By two years after the date of application of this Regulation referred to in Article 85(2) and every four years thereafter, the Commission shall evaluate and report to the European Parliament and to the Council on the need for amendment of the following: – the need for extension of existing area headings or addition of new area headings in Annex III, – the list of AI systems requiring additional transparency measures in Article 52 – effectiveness of the supervision and governance system

2a. By three years after the date of application of this Regulation referred to in Article 85(3) and every four years thereafter, the Commission shall submit a report on the evaluation and review of this Regulation to the European Parliament and to the Council. This report shall include an assessment with regard to the structure of enforcement and the possible need for an Union agency to resolve any identified shortcomings. On the basis of the findings that report shall, where appropriate, be accompanied by a proposal for amendment of this Regulation. The reports shall be made public.

3. The reports referred to in paragraph 2 shall devote specific attention to the following:

(a) the status of the financial, technical and human resources of the national competent authorities in order to effectively perform the tasks assigned to them under this Regulation;

(b) the state of penalties, and notably administrative fines as referred to in Article 71(1), applied by Member States to infringements of the provisions of this Regulation.

(ba) ba) adopted harmonised standards and common specifications developed to support this Regulation. bb) the number of companies that enter the market after the enter into application of the regulation and how many of them are SMEs.

(bb) By … [two years after the date of entry into application of this Regulation referred to in Article 85(2)] the Commission shall evaluate the functioning of the AI office, whether the office has been given sufficient powers and competences to fulfil its tasks and whether it would be relevant and needed for the proper implementation and enforcement of this Regulation to upgrade the Office and its enforcement competences and to increase its resources. The Commission shall submit this evaluation report to the European Parliament and to the Council.

3a.      By two years [after the date of application of this Regulation referred to in Article 85(2)] and every four years thereafter, the Commission shall submit a report on the review of the progress on the development of standardization deliverables on energy efficient development of general-purpose models and asses the need for further measures or actions, including binding measures or actions. The report shall be submitted to the European Parliament and to the Council and it shall be made public.

4. Within … [two year after the date of application of this Regulation referred to in Article 85(2)] and every three years thereafter, the Commission shall evaluate the impact and effectiveness of voluntary codes of conduct to foster the application of the requirements set out in Title III, Chapter 2 for AI systems other than high-risk AI systems and possibly other additional requirements for AI systems other than high-risk AI systems, including as regards environmental sustainability;

5. For the purpose of paragraphs 1 to 4 the Board, the Member States and national competent authorities shall provide the Commission with information on its request, without undue delay

6. In carrying out the evaluations and reviews referred to in paragraphs 1 to 4 the Commission shall take into account the positions and findings of the Board, of the European Parliament, of the Council, and of other relevant bodies or sources.

7. The Commission shall, if necessary, submit appropriate proposals to amend this Regulation, in particular taking into account developments in technology, the effect of AI systems on health and safety, fundamental rights and in the light of the state of progress in the information society.

7a.         To guide the evaluations and reviews referred to in paragraphs 1 to 4 of this Article, the Office shall undertake to develop an objective and participative methodology for the evaluation of risk level based on the criteria outlined in the relevant articles and inclusion of new systems in: the list in Annex III, including the extension of existing area headings or addition of new area headings in that Annex; the list of prohibited practices laid down in Article 5; and the list of AI systems requiring additional transparency measures pursuant to Article 52.

7b.    Any amendment to this Regulation pursuant to paragraph 7 of this Article, or relevant future delegated or implementing acts, which concern sectoral legislation listed in Annex II Section B, shall take into account the regulatory specificities of each sector, and existing governance, conformity assessment and enforcement mechanisms and authorities established therein.

7c.     By … [five years from the date of application of this Regulation], the Commission shall carry out an assessment of the enforcement of this Regulation and shall report it to the European Parliament, the Council and the European Economic and Social Committee, taking into account the first years of application of the Regulation. On the basis of the findings that report shall, where appropriate, be accompanied by a proposal for amendment of this Regulation with regard to the structure of enforcement and the need for an Union agency to resolve any identified shortcomings.