ai

Greece launches public AI literacy guide for citizens

Greece’s Ministry of Digital Governance and Artificial Intelligence has launched ‘Artificial Intelligence for All’, a public guide designed to improve understanding and use of AI tools.

The guide was developed through cooperation between leading AI scientists, the Ministry of Digital Governance and Artificial Intelligence, the National Council for Research, Technology and Innovation, and the Special Secretariat for Long-Term Planning. The guide is available free of charge through the digital platform of the Special Secretariat for Artificial Intelligence and Data Governance.

According to the ministry, the initiative aims to support digital education, responsible AI use, and a broader understanding of AI systems.

The material introduces basic concepts related to AI and large language models through practical examples and simplified explanations. The guide explains how AI systems can process different forms of data and generate outputs, including recommendations, summaries, and digital content.

The project forms part of Greece’s broader digital strategy focused on digital skills development and public familiarity with emerging technologies.

Officials also highlighted collaboration with the members of the Greek scientific community in Greece and abroad, with the objective of making advanced technological tools more accessible to the wider population.

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Environmental group raises concerns over AI data centre emissions in Scotland

Environmental charity APRS has criticised the Scottish Government over how greenhouse gas emissions linked to hyperscale AI data centres are assessed within existing planning and climate frameworks.

According to APRS, earlier lifecycle emissions assessments focused primarily on broadband and smaller-scale digital infrastructure before the recent expansion of generative AI-related facilities.

The concerns are linked to a proposed 212MW AI data centre project in Edinburgh, currently involved in a planning appeal process.

APRS argued that the term ‘green data centre’ lacks a clear policy definition in relation to large-scale AI infrastructure projects. The organisation said Scotland does not yet have a dedicated policy framework addressing hyperscale AI data centres.

APRS stated that multiple large-scale data centre proposals are currently under consideration across Scotland. The group warned that growing electricity demand linked to data centre expansion could have implications for energy planning and climate objectives.

APRS also called for updated lifecycle emissions assessments and revised planning guidance for hyperscale AI infrastructure projects.

Why does it matter?

The debate highlights a widening policy gap between the rapid expansion of AI infrastructure and existing environmental planning frameworks. Many national climate assessments were created before the emergence of hyperscale generative AI systems, meaning governments may be underestimating the energy, emissions, and resource demands associated with large-scale AI deployment.

It also demonstrates how AI is no longer only a digital or technological policy challenge, but increasingly an environmental, infrastructure, and energy governance issue.

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Singapore pushes trusted AI governance with KPMG AI centre

Singapore’s Ministry of Digital Development and Information has highlighted trust and accountability as key factors in AI adoption during the launch of KPMG’s new Trusted AI Centre of Excellence. Minister of State Jasmin Lau said governments and businesses should ensure AI adoption benefits workers, citizens, and smaller enterprises alongside larger organisations.

The new centre will focus on AI governance, monitoring systems, and AI-related assurance processes as organisations deploy increasingly advanced AI models. KPMG said it is using AI tools internally across audit, tax, and advisory services before broader deployment to clients.

Singapore also reiterated its goal of strengthening its role in regional AI governance and standards development. Officials highlighted efforts involving ASEAN cooperation, AI testing capabilities, and governance initiatives such as AI Verify. According to officials, transparency, explainability, and accountability will remain important factors influencing public confidence in AI systems.

The discussions also reflected broader concerns about AI-related economic disruption, governance challenges, and public trust. Officials noted that businesses and workers continue to face uncertainty regarding AI governance, compliance, and the economic effects of AI adoption.

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European Patent Office expands AI use in patent examination

The European Patent Office (EPO) has presented new AI-related initiatives aimed at supporting quality and efficiency within the European patent system during the latest meeting of the SACEPO Working Party on Quality.

The online gathering brought together 71 representatives from around the world to discuss examination standards, AI integration and long-term improvements to patent procedures. EPO President António Campinos described quality as a central element of the European patent system during the meeting.

The EPO also provided updates on its Quality Action Plan 2026, including examiner training, access to prior-art information, and examination harmonisation efforts. Officials also discussed insights drawn from quality audits and decisions issued by the Boards of Appeal.

Participants discussed the increasing use of AI-supported tools within the patent-granting process. According to the EPO, AI systems are being developed to assist with tasks including pre-search procedures, drafting support, legal queries, and preparation of oral proceedings documentation.

Participants also highlighted the importance of confidentiality, accountability, and human oversight in AI-supported systems.

The EPO stated that final patent examination decisions remain under human responsibility in line with its human-centric AI policy. The meeting additionally examined broader adoption of AI tools across patent and legal sector workflows, quality assurance and secure handling of sensitive intellectual property information.

Why does it matter?

The integration of AI into patent examination highlights how intellectual property systems are adapting to growing technological complexity and increasing volumes of patent applications worldwide. Faster and more consistent examination processes could strengthen innovation ecosystems across Europe, particularly in AI, semiconductors, biotechnology and digital industries.

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Pope Leo XIV releases first encyclical focused on AI and human dignity

Pope Leo XIV has released his first encyclical, Magnifica humanitas: On Safeguarding the Human Person in the Time of Artificial Intelligence, positioning AI as one of the defining moral, political and social challenges of the modern era.

Published by Vatican on the 135th anniversary of Rerum novarum, the document argues that AI must remain centred on human dignity, social justice and peace instead of becoming a tool for domination, exclusion or concentrated power.

The encyclical states that technological systems reflect the priorities and values of those responsible for their design, financing, and governance. The Pope also warned against forms of technocratic governance and excessive concentration of technological power.

The document highlighted concerns related to surveillance, digital inequality, manipulation of public opinion, and concentration of technological infrastructure.

The encyclical also addressed labour, education, and social justice implications linked to AI-driven automation. According to the document, technological systems should support human well-being and dignity rather than undermine workers’ autonomy and social participation. He also called for stronger protections for vulnerable groups, ethical oversight of AI deployment and fair access to digital opportunities.

The Vatican also stressed the importance of critical thinking, creativity, and moral judgement in education systems increasingly influenced by AI technologies.

The document additionally discussed geopolitical and military dimensions of AI, including concerns surrounding autonomous weapons systems. Pope Leo XIV rejected the growing use of autonomous weapons and criticised efforts to normalise AI-assisted warfare.

The encyclical called for stronger international cooperation and ethical governance frameworks related to AI development and deployment. According to the Pope, humanity faces a decisive choice between technological systems that strengthen human flourishing or systems that weaken freedom, solidarity and peace.

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Kazakhstan launches UNESCO AI readiness assessment initiative

The United Nations Educational, Scientific and Cultural Organization has announced the launch of its AI Readiness Assessment Methodology in Kazakhstan to evaluate the country’s preparedness for AI governance and development.

The framework is intended to help countries align AI governance approaches with UNESCO Recommendation on the Ethics of AI. Representatives from government, academia, business, civil society, and expert organisations participated in the launch discussions.

Participants discussed Kazakhstan’s digital transformation priorities and plans related to AI ecosystem development. According to UNESCO representatives, the assessment process will address issues including human rights, inclusion, gender equality, and transparency in AI governance.

A national stakeholder group involving ministries, universities, business associations, and civil society organisations will support implementation and policy recommendations. The launch event was held at Astana Hub in Kazakhstan.

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Anthropic says AI system identified thousands of critical software flaws

Anthropic has published an update on Project Glasswing, a cybersecurity initiative focused on identifying software vulnerabilities using AI systems.

According to Anthropic, partner organisations used Claude Mythos Preview to identify thousands of high- and critical-severity vulnerabilities across software platforms and infrastructure systems.

The company said the initiative demonstrated how AI systems are increasing the speed and scale of vulnerability discovery processes. Anthropic reported that participating organisations observed substantial increases in software vulnerability detection capabilities during testing.

Evaluations cited by Anthropic suggested the system performed strongly in vulnerability identification and exploit-detection tasks compared with earlier AI cybersecurity models.

Anthropic also said the model analysed more than 1,000 open-source projects and identified vulnerabilities affecting widely used software components. The company highlighted a vulnerability identified in the open-source cryptography library wolfSSL as one example from the project.

According to Anthropic, the vulnerability was patched after disclosure.

Anthropic said AI-assisted vulnerability discovery may increasingly shift cybersecurity challenges toward verification, disclosure, and remediation processes. The company also said similar AI cybersecurity capabilities are likely to become more widely available across the industry.

Why does it matter?

The rapid growth of AI-driven cybersecurity is becoming increasingly important as AI is fundamentally changing the balance between cyber defence and cyber threats. Systems such as Anthropic’s Project Glasswing demonstrate that advanced AI models can identify software vulnerabilities at a speed far beyond traditional human-led security testing, potentially making critical infrastructure, financial systems, cloud platforms, and open-source software both safer and more exposed at the same time.

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European Commission advances AI transparency code under EU AI Act

The European Commission’s AI Office has convened a new round of working group meetings and workshops on the forthcoming Code of Practice on Marking and Labelling of AI-Generated Content.

The discussions brought together providers of generative AI systems and models, technology companies, industry representatives, civil society organisations and academic experts. Feedback from the meetings will inform the third and final draft of the code, expected in early June.

The code is intended to support transparency obligations under the AI Act, including requirements linked to marking, labelling, disclosure and detectability of AI-generated content. It covers issues such as synthetic media, deepfakes and certain AI-generated text.

Working Group 1 focused on marking and detection obligations for providers, including a revised multi-layered approach, technical feasibility, benchmarking, compliance frameworks and possible third-party assessments. Industry participants raised concerns over compliance burdens, innovation and feasibility, while civil society and academic experts called for stronger safeguards in the public interest.

Working Group 2 examined disclosure obligations for deployers of generative AI systems, particularly deepfakes and certain AI-generated text. Discussions covered origin disclosure, user-facing labels, proportionality, governance measures, editorial control and the possible development of a uniform EU label.

Additional workshops explored how machine-readable marks, provenance data, visible labels, watermarking systems and an EU-wide icon could work together across the AI value chain. Participants also discussed coordination with other EU rules, including the Digital Services Act, while stressing the need to balance transparency, legal clarity, accessibility and innovation.

Why does it matter?

The code of practice will help determine how AI-generated content is marked, labelled and disclosed across the EU. Its development highlights the practical difficulty of turning transparency obligations into workable rules, particularly when regulators, companies and civil society disagree over technical feasibility, compliance costs, user experience and safeguards against deceptive synthetic media.

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South Korea launches tripartite committee on AI and labour

South Korea’s Economic, Social and Labor Council (ESLC), a presidential advisory body, has launched a tripartite committee to examine the impact of AI on labour and workplaces. The committee brings together labour, business, government, and public interest representatives for a year-long dialogue on AI-related workplace changes.

The committee held its first meeting in Seoul and will examine how AI adoption may affect employment patterns and industrial workplaces. The 17-member body is chaired by former presidential jobs secretary Hwang Deok-soon and includes labour, business, government and public interest representatives.

According to the ESLC, discussions will focus on AI adoption, changes to jobs and work tasks, worker data collection, and support measures linked to workforce transitions. The initiative is expected to include expert consultations and workplace assessments examining practical uses of AI technologies.

The launch comes amid broader public debate about automation, humanoid robotics, and potential labour-market disruption linked to AI technologies. ESLC Chair Kim Ji-hyung said the discussions aim to balance technological development, industrial competitiveness, and labour market stability in South Korea.

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World Bank highlights ‘Small AI’ for farmers and rural communities

According to Hindustan Times, World Bank President Ajay Banga highlighted the potential of ‘Small AI’ systems to support farmers and rural communities through locally deployed and lower-cost technologies.

Examples discussed included farmers in India using mobile phones to share images of diseased crops and receive agricultural advice remotely. Banga also referred to healthcare workers in Indonesia using basic internet connections to access local diagnostic support systems in remote areas.

At the summit, entrepreneur Saurav Mukherjee said AI adoption was expanding into sectors including agriculture and food production. Mukherjee said AI tools may support agricultural decision-making through analysis of seed quality and environmental conditions such as soil, weather, and water availability.

He also noted that wider internet connectivity and 5G access could support wider AI adoption in underserved regions. However, he cautioned that shortages of skilled workers could limit implementation capacity in some regions.

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