AI Governance: Ensuring equity and accountability in the digital economy (UNCTAD)

Arguments

Governance solutions for AI and SDGs need to comply with the specific nature and requirements of the system in question

Supporting facts:

• Mention of the One Goal initiative for governance

• Analogy of fusion cuisine and careful blending of different solutions

• Emphasis on understanding the system topology and maintaining nutritional balance

Topics: AI governance, SDGs, system integration

Concern about the allocation and coordination of governance of AI within the UN family to avoid waste of time and forum shopping.

Topics: Artificial Intelligence, UN Governance, ITU, UNCTAD

African economies may not need AI regulations and governance seen from the Western lens

Supporting facts:

• AI regulation and governance mainly focus on the needs of developed economies

• AI strategies seem to work better for these economies to help them catch up

• Some of these economies already have laws such as data protection laws and labor laws that could potentially handle AI

Topics: AI regulations, AI governance, African economies, Developing economies

AI regulations and governance might not be necessary for emerging economies

Supporting facts:

• The speaker is working in Kenya, an emerging economy, and sees that the situation on the ground might not necessitate AI regulations and governance

• The speaker thinks that the discussion should be more around AI strategies and how to build these economies using AI tools

Topics: AI regulation, Emerging Economies, AI Governance

The environmental impacts of AI and machine learning need to be addressed

Supporting facts:

• Machine learning accounted for 15% of total energy use over the last three years

Topics: AI, Machine Learning, Environmental impact, Energy Usage

Report

The analysis examines various perspectives on governance solutions for artificial intelligence (AI) and Sustainable Development Goals (SDGs). One speaker stresses the importance of considering the specific characteristics and requirements of each system when developing governance solutions. They argue that effective solutions must take into account the unique nature of AI and the diverse range of SDGs.

To illustrate their point, they use the analogy of fusion cuisine, highlighting the need for careful blending of different solutions to ensure coherence and effectiveness. However, another speaker urges caution when integrating diverse governance solutions without thorough consideration and analysis.

They raise concerns about the potential problems that could arise from adopting AI strategies that resemble fusion cuisine. Instead, they recommend careful planning and detailed analysis to prevent any detrimental consequences. In terms of UN governance, there are concerns about the allocation and coordination of AI governance within the UN family.

It is argued that avoiding wastage of time and forum shopping is crucial. To address this, the creation of an agreement within the UN family is suggested to assign workload for AI governance effectively. The necessity of distinct AI regulations and governance for developing economies, particularly in Africa, is called into question by one speaker.

They assert that the current Western lens through which AI regulations and governance are viewed may not adequately address the needs of African economies. They highlight that some of these economies already have laws in place, such as data protection and labour laws, which could potentially handle AI effectively.

Similarly, another speaker argues that emerging economies should prioritise building their economies using AI tools before considering AI governance and regulations. They believe it is premature to focus on governance and regulations when there are other ways to bring these economies to the table.

Instead, they advocate for utilising AI strategies and tools to foster economic growth and development. The environmental impacts of AI and machine learning are brought to attention. It is highlighted that machine learning has accounted for as much as 15% of total energy use over the past three years.

This serves as a concern and emphasises the importance of addressing the environmental implications of AI and machine learning. Lastly, the principle that AI innovation should align with sustainable development goals and not solely serve the interests of big corporations is advocated by one speaker.

They propose that AI should be harnessed to support sustainable development and address societal challenges beyond corporate interests. In conclusion, the analysis provides a comprehensive overview of various perspectives on governance solutions for AI and SDGs. It highlights the need to consider the specific nature and requirements of each system, the importance of careful integration and analysis of diverse solutions, concerns about the allocation and coordination of AI governance within the UN family, doubts about the necessity of distinct AI regulations and governance for developing economies, the environmental impacts of AI and machine learning, and the call for AI innovation to align with sustainable development goals.

Arguments

A lot is happening in the AI governance, and countries are active in the field.

Supporting facts:

• Countries didn’t waste time in being active

• ITU has been involved in many national, regional or global discussions

Topics: AI governance, National efforts, AI Development

The AI challenges are not solely for the big tech industries to fix, governments also need to get involved.

Supporting facts:

• Initial discussions were focused on tech industry fixing problems

• The government’s role in AI governance is increasingly recognized

Topics: AI governance, Public and private sector involvement, Technology industry

There are tools in our toolbox that we can leverage for AI governance.

Supporting facts:

• International technical standards can be leveraged

Topics: AI governance, International technical standards

Most AI governance efforts are concentrated in a handful of countries and companies which could exacerbate further inequalities.

Supporting facts:

• A lot of efforts are concentrated in a handful of countries and companies

Topics: AI governance, Inequality

UN and its organizations like ITU, UNCTAD and UNESCO can play an important role in AI discussions and governance.

Supporting facts:

• UN organizations are a good platform to convene AI governance discussions

• ITU has AI for Good platform with 40 UN partners focusing on AI benefits and governance

Topics: UN, ITU, UNCTAD, UNESCO, AI governance

No single entity can manage AI on its own

Supporting facts:

• Doreen suggests that multiple stakeholders need to work together for AI regulation and management

Topics: AI, Regulation, Cooperation

Need to identify right ingredients amongst different initiatives for global benefit

Supporting facts:

• Doreen mentions that different initiatives can contribute to a collective effort for global benefit

Topics: AI, Global initiatives, Cooperation

Need to focus on more inclusive conversations and capacity development

Supporting facts:

• Doreen highlights the importance of including those not currently at the table, particularly from developing countries

Topics: Inclusivity, Capacity Development

Governments must hold their stakeholders accountable

Supporting facts:

• AI and internet are a borderless conversation, hence the need for accountability

Topics: AI, Internet, Regulations, Accountability

Need for engagement of policymakers and regulators

Topics: AI, Regulations, Policy Makers, Accountability

Transparency and accountability should be built at national, regional, and global level

Topics: Transparency, AI, Regional Cooperation, Global Standards

Advocate for democratizing AI through development, benefits, and governance

Supporting facts:

• ITU has launched series of competitions influencing AI innovation

• Awarded a young African startup Tolby, using AI for soil assessment

• ICT Policymakers and regulators in many countries are taking leadership roles in AI

Topics: AI, Standards, Software Engineers, Developers, Innovation, Inclusive AI benefits, Governance, Transparency, Accountability

Plans to include developing countries in regulating AI issues

Supporting facts:

• AI for good was conceptualized from the very beginning, all about the SDGs and how you can use artificial intelligence to accelerate and help to achieve each and every SDG

• Global Symposium for Regulators is a critical event for the global ICT regulatory community.

Topics: AI for good, SDG framework, ICT regulatory community

UN agencies working on AI, convened by ITU and UNESCO, and documenting use cases

Supporting facts:

• 40 UN agencies are working in AI

• Interagency group led by ITU and UNESCO

• Over 300 use cases documented from UN agencies

Topics: AI, United Nations, ITU, UNESCO

Awaiting recommendations from SG’s body on AI

Supporting facts:

• SG’s body on AI is convening in New York

Topics: AI, United Nations, SG’s body on AI, Recommendations

AI and digital sector contribute to greenhouse gas emissions, but can also help reduce them

Supporting facts:

• Digital sector’s greenhouse gas emissions is between 2.1 and 3.9%

• Green standards and interventions can help reduce these emissions to between 15 to 20%

Topics: AI, Climate Change, Greenhouse gas emissions

Promotion of green digital track initiative at COP focused on energy efficiency, e-waste, early warning systems and reducing greenhouse gases

Supporting facts:

• Green digital track launched at COP

Topics: COP, Green digital track, Energy efficiency, e-waste

Closing the digital divide is necessary for being part of AI revolution

Supporting facts:

• Not being a part of the digital revolution means missing out on the AI revolution

Topics: Digital divide, AI revolution

Report

A lot is happening in the field of AI governance, with countries actively involved. The International Telecommunication Union (ITU) has been playing a significant role in many national, regional, and global discussions on AI governance. This highlights the urgency and importance placed on addressing the challenges and implications of AI.

While big tech industries have been at the forefront of AI development, it is essential for governments to also get involved in AI governance. The initial focus was on the tech industry fixing problems, but the government’s role is increasingly recognized.

This shift in perspective acknowledges that AI challenges cannot be solely addressed by the private sector; a collaborative effort involving multiple stakeholders is required. An important aspect of AI governance is the establishment and implementation of international technical standards. These standards provide a framework and guidance for the responsible and ethical use of AI.

Leveraging these standards can ensure consistency and coherence in AI governance practices globally. However, a concerning issue is the concentration of AI governance efforts in a handful of countries and companies. This concentration raises concerns about the potential exacerbation of existing inequalities.

Efforts must be made to ensure that AI governance is not monopolized by a few powerful entities, but rather encompasses a diverse range of countries and companies, promoting inclusivity and reducing inequalities. The United Nations (UN), through its agencies such as ITU, UNCTAD, and UNESCO, can play a crucial role in AI discussions and governance.

These organizations provide a platform for convening discussions, sharing best practices, and documenting use cases. They also work collectively to advise countries on AI challenges and promote global cooperation in AI governance. Multiple stakeholders need to collaborate and work together for effective AI regulation and management.

This acknowledges the complexity and multifaceted nature of AI governance, which requires input and expertise from various sectors, including industry, academia, civil society, and policymakers. No single entity can manage AI on its own, highlighting the importance of partnerships and collaboration.

Inclusivity is another key aspect of AI governance. It is crucial to have more inclusive conversations and ensure the participation of stakeholders from developing countries. This promotes a diversity of perspectives and avoids the risk of biased decision-making or the exclusion of certain populations.

ITU, with its unique position of having multi-stakeholder members, has an advantage in addressing the challenges of AI governance. The involvement of the private sector, civil society, academia, and other stakeholders allows for a comprehensive and balanced approach to AI governance.

Governments must hold their stakeholders accountable in the AI and internet conversation. This accountability ensures that ethical and responsible practices are upheld, preventing any misuse or harm caused by AI technologies. A balance between regulation and innovation is necessary to avoid stifling the development and potential of AI.

Heavy-handed regulation could impede innovation and hinder the progress of AI technologies. It is important to strike a balance that promotes responsible AI development while allowing for innovation and growth. Transparency and accountability should be integrated at various levels – national, regional, and global.

This ensures that AI technologies and their applications are transparent, accountable, and aligned with principles of fairness and justice. Democratizing AI is advocated, with a focus on development, benefits, and governance. This encompasses making AI accessible and beneficial to a wider population and ensuring that its development and deployment are guided by ethical considerations.

Addressing climate change is also a concern in AI governance. The digital sector, including AI technologies, contributes to greenhouse gas emissions. However, it also presents opportunities to reduce emissions through green standards and interventions. This highlights the potential for AI to contribute to sustainable development and climate action.

Developing countries need to play an active role in AI governance by creating their own AI policies and strategies. By becoming creators rather than just consumers of AI technologies, they can contribute to all aspects of AI development, including testing and safety design.

Efforts should be made to close the digital divide to ensure that countries and populations are not left behind in the AI revolution. Closing the digital divide is crucial for inclusive participation and access to the benefits of AI technologies.

Overall, AI governance requires collaboration, inclusivity, transparency, and accountability. It is a complex and evolving field that requires collective efforts and multi-stakeholder engagement. The involvement of international organizations, governments, tech industries, and civil society is crucial to ensure responsible, ethical, and beneficial AI development and deployment.

Arguments

Estonia’s experience in digital government has informed AI governance frameworks at national and EU levels.

Supporting facts:

• Estonia is entering the preparation of their third strategy for AI.

• Estonia remains a proof that technology can bring good.

• Clear principles and regulation for privacy, access to information, interoperability were set in Estonia at the end of the 90s and early 2000s.

Topics: AI Governance, Digital Government, EU

AI governance cannot be approached without a resolved data governance system.

Supporting facts:

• Many countries do not have settled rules around how data should be collected, shared, accessed, archived, updated.

• There is no possibility to ‘leapfrog’ and go straight to AI, without settling data governance.

Topics: AI Governance, Data Governance

Before implementing AI, companies and countries need to ensure that they have set the necessary groundwork

Supporting facts:

• The micro and macro groundwork needs to be established prior to the implementation of AI

• This includes creating user-friendly services that are accessible when needed

• Clear principles and regulations need to be set

Topics: Artificial Intelligence, Digital Infrastructure

Citizens need to have a sense of security with digital systems

Supporting facts:

• Providing access to personal data held by the government can increase trust

• Instances where data misuse has been discovered and dealt with has helped increase trust

• Trust needs to be earned and built through practice

Topics: Data Security, Citizens Trust

The private sector data poses a different set of challenges compared to public sector data

Supporting facts:

• The private and public space are merging and it’s posing many challenges

• Achievements in public sector data security may not be easily replicated in the private sector

Topics: Private Sector Data, Public Sector Data

The market for AI solutions is crowded

Supporting facts:

• There are different levels of regulation at national and original level

• Small and medium sized companies may struggle to follow all these developments and regulations

Topics: Artificial Intelligence, Regulation

Too many different regulations could harm small and medium-sized companies

Supporting facts:

• Small and medium-sized companies may not be able to follow all different developments or regulations

Topics: SMEs, Artificial Intelligence, Regulation

Smaller countries and entities can develop AI without needing ‘big data’.

Supporting facts:

• Estonia has a few companies like Bolt and Wise that produce comparatively big data

• Estonia uses AI solution that simply detects personal data in public documents, which doesn’t necessitate Google, Amazon, or similar big entities

Topics: AI development, big data, small nations, Estonia

The fear of doing something wrong is a major obstacle in utilising AI.

Supporting facts:

• A survey among Estonian public institutions revealed that their main concern was fear of non-compliance with legislative requirements

Topics: AI usage, public sector, fear, legal requirements

Concerned about the ability to test new technologies in smaller countries and companies

Supporting facts:

• Coming from a small country

Topics: AI, Innovation, Regulation

Report

Estonia’s experience in digital government has had a significant impact on the development of AI governance frameworks, both at the national and EU levels. Its strong approach towards digital governance and AI serves as a model for other countries. Since the late 1990s and early 2000s, Estonia has set clear principles and regulations for privacy, access to information, and interoperability.

These strategies and regulations have influenced relevant regulations within the EU. One of the significant challenges in implementing AI governance is the lack of settled rules around data governance. Many countries do not have clear guidelines on data collection, sharing, access, archiving, and updating.

It is crucial to establish a solid foundation in data governance before effectively approaching AI governance. Estonia recognizes this and emphasizes the importance of resolving data governance systems before implementing AI. Estonia understands the value of technology but also acknowledges the associated risks.

The country has taken measures to ensure the safety and security of the virtual space, as not all actors have good intentions when using technology. Establishing the necessary groundwork is crucial before implementing AI. This includes creating user-friendly and accessible services, as well as setting clear principles and regulations.

Building trust in digital systems should be a priority, achieved through useful, user-friendly, and reliable systems, consequences for data misuse, and transparency in data use. The private sector poses unique challenges in terms of data security compared to the public sector.

Achievements in public sector data security may not easily translate to the private sector due to different circumstances and requirements. To manage risks and maximize AI’s opportunities, there is a need for global principles. The spread of disinformation, for example, cannot be eliminated solely through regulation limited to specific borders.

Discussions on AI regulation are taking place in various contexts, highlighting the necessity for a cohesive approach. The market for AI solutions is crowded, presenting challenges for companies, especially small and medium-sized enterprises (SMEs). With different levels of regulation at national and regional levels, smaller companies may struggle to navigate and comply with the various developments and regulations.

Smaller countries like Estonia have demonstrated that AI development can occur without relying heavily on “big data.” Estonia has successfully developed AI solutions that detect personal data in public documents without needing the resources of big entities such as Google or Amazon.

The fear of non-compliance with legislative requirements is identified as a major obstacle to utilizing AI. A survey among Estonian public institutions highlighted fear of not meeting legal requirements as their main concern. Expanding participation in AI governance beyond dominant international organizations and countries is crucial.

These entities currently tend to control AI governance. Including a wider range of perspectives is necessary for more comprehensive and inclusive decision-making. Smaller countries and companies express concerns about their ability to test new technologies and keep pace with innovations in AI.

The ability to test new technologies is considered essential for continued growth and innovation. Advocates for AI and data regulation call for a risk-based approach that balances regulation and innovation. Such an approach allows for continued innovation while addressing potential risks and ensuring responsible and ethical use of AI.

In conclusion, Estonia’s experience in digital government has significantly influenced AI governance frameworks. Its strong approach towards digital governance and AI serves as an example for others. However, challenges related to data governance, the crowded AI market, compliance with regulations, and the need for global principles require attention.

Building trust in digital systems and expanding participation in AI decision-making are essential for successful implementation. Additionally, adopting a risk-based approach to regulation can encourage innovation while mitigating potential risks.

Arguments

Transparency is key in the artificial intelligence world to understand what is behind the algorithms

Supporting facts:

• Artificial intelligence is emerging with rise in computing power and data

• Efficiency in using computing power and data opens up huge potential

Topics: Artificial Intelligence, Algorithms

AI for development is a very important part

Topics: Artificial Intelligence, Development

The biggest risk is not having all stakeholders at the table for effective decision making

Supporting facts:

• Inclusion has to be in the broadest sense

• Developing countries need to be included for seeing this as a common project

Topics: Inclusion, Collaboration

Clarity of vision and intent is significant in the AI governance

Supporting facts:

• Managing the risks and recognising the transformative potential of AI

• Embed safety by design in AI development

Topics: AI governance, Transparency, Accountability

Targeted focus in tackling specific aspects of AI is necessary

Supporting facts:

• Focusing on risks around frontier AI, misuse, misinformation

Topics: AI governance, AI risks

Inclusiveness is vital in the AI debate

Supporting facts:

• Decision to include China in the AI Summit at Bletchley park

Topics: AI governance, Inclusivity

Report

The analysis of the speeches revealed several important points about artificial intelligence (AI) and its governance. It was noted that AI is rapidly emerging as computing power and data continue to advance. This development presents immense potential for various applications and advancements.

Transparency was highlighted as a crucial aspect in the AI world. Speakers emphasized the need to understand the algorithms behind AI systems to build trust and ensure ethical and accountable AI operations. Collaboration was identified as key in managing the risks associated with frontier AI.

The Bletchley Park summit was mentioned as an example of a collaborative effort involving governments, businesses, academia, and civil society to address AI risks. Inclusion emerged as a recurring theme, with speakers stressing the importance of involving all stakeholders in the AI debate.

This inclusive approach brings diverse perspectives and experiences to effective decision making. Clarity of vision and intent in AI governance was highlighted as significant. By embedding safety measures in AI development, potential risks can be mitigated, and the transformative potential of AI can be maximized.

A targeted focus on specific aspects of AI in governance efforts was seen as necessary. By addressing risks associated with frontier AI, such as misuse and misinformation, resources can be allocated more efficiently. The analysis also emphasized the importance of involving China in the global AI conversation.

China’s expertise and contributions can enhance the comprehensive and diverse approach to AI governance. In conclusion, the analysis highlights transparency, collaboration, inclusion, clarity of vision and intent, targeted focus, and involvement of China as essential factors in AI governance. By addressing these aspects, stakeholders can harness the potential of AI while ensuring ethical and accountable AI systems.

Arguments

Governance in artificial intelligence is controversial with a lot of differing ideas.

Topics: Artificial Intelligence, Governance

There’s a need for robust governance mechanisms in AI to ensure that developing countries are not left behind.

Topics: Artificial Intelligence, Governance, Developing Countries

The technological revolution from AI will impact all our lives and goes beyond just technology.

Topics: Artificial Intelligence, Technological Revolution

Transparency is key in the artificial intelligence world

Supporting facts:

• Nele Leosk points out how Estonia’s government gave citizens the ability to see their data and how it’s been used as an example of transparency

• Many challenges arise from the blurred lines between public and private sector data

Topics: Artificial Intelligence, Transparency, Data Privacy

Understanding practical examples can help contextualize problems and circumstances

Supporting facts:

• Leosk provides the example of Estonia’s government showing data usage and disclosure as an active effort to regulate use and misuse of information

Topics: Public Policy, Data Privacy, Artificial Intelligence

Inclusion of China and other developing countries is vital in AI related discussions and debates

Supporting facts:

• Simon Manley emphasized the importance of including China in the Bletchley Park AI summit

• Isabelle Kumar mentioned the importance of Joe Biden and Xi Jinping’s discussions

Topics: AI, China’s Inclusion, Developing Countries

AI can be a source for good

Supporting facts:

• Big players are working in that field

Topics: Artificial Intelligence, Innovation

Report

Governance of artificial intelligence (AI) continues to be a contentious issue, with various perspectives and controversy surrounding the topic. It is crucial to establish robust mechanisms for governing AI to ensure that developing countries are not left behind in the technological advancements.

The impact of the AI technological revolution extends beyond technology, affecting different aspects of our lives. Transparency is paramount in the AI world, as it promotes accountability and trust. Estonia’s government has been lauded for its efforts in promoting data transparency, allowing citizens to access and monitor their personal data usage.

This example serves as a model for other nations to follow, highlighting the significance of transparency. To better understand the practical implications of AI governance, it is essential to examine concrete examples. Estonia’s government actively regulates the use and misuse of information, demonstrating a commitment to data privacy.

Practical examples like this allow for a contextualized view of the challenges and circumstances surrounding AI regulation. The Bletchley Park AI summit holds great importance in the field of AI governance. It showcases the UK’s leadership in AI and brings together global leaders to discuss and address the challenges and opportunities presented by AI.

The presence of influential figures at the summit underscores its significance as a platform for important discussions and collaborations. Inclusion of China and other developing countries in AI discussions is crucial for comprehensive and representative decision-making. Prominent figures, such as Simon Manley, emphasize the importance of including China in the Bletchley Park AI summit, while Isabelle Kumar highlights the significance of discussions between Joe Biden and Xi Jinping.

These discussions and collaborations ensure diverse perspectives are considered in AI-related debates. However, concerns have been raised regarding smaller nations like Estonia being overshadowed in AI discussions. To avoid marginalization, it is crucial to give voice to these smaller countries and consider their contributions and perspectives.

By taking a practical approach and implementing regulations on AI and data, smaller countries can bridge the digital divide and ensure their voices are heard. On a positive note, AI has the potential to bring about positive change. Major players in the field are already working towards harnessing AI’s capabilities for beneficial outcomes.

Despite the controversies and differing opinions, the positive potential of AI is unmistakable, and efforts are underway to ensure responsible and ethical use. In conclusion, AI governance is a complex issue with varying perspectives. Robust mechanisms are necessary to prevent the marginalization of developing countries in the AI revolution.

Transparency, practical examples, inclusive discussions, and the involvement of smaller nations are essential components of effective AI governance. By regulating and innovating, smaller countries can bridge the digital divide and make their voices heard. Ultimately, AI has the potential to drive positive change, and measures are being taken to harness its power responsibly.

Arguments

China is trying to find a balance between AI governance and development

Supporting facts:

• Chinese government published a lot of policy to encourage the industry

• The National Internet Information Office also published the the management management measures for generative artificial intelligence service.

Topics: AI governance, AI development, China

The Chinese government has published policies to control data transfer cross borders and to enforce companies providing general AI services to get a license

Supporting facts:

• Two important policies released end of last year and this year: to control data transfer cross borders and requiring companies providing general AI services to get government license

Topics: AI Governance, Data Security, Global Data Transfer

The Chinese government found it impossible to evaluate the data if it is okay to transfer cross borders or not, and similarly to evaluate the algorithm

Topics: Data Governance, Data Security, AI Evaluation

China needs more time to practice and refine its AI governance model.

Topics: AI Governance, Policy Making

AI economies should have a say in discussions on AI governance

Supporting facts:

• Internet penetration rate in developing countries is lower making the discussion for internet infrastructure clear

• Data governance is a bigger issue compared to AI governance

Topics: AI governance, Developing economies, Digital economy

AI is a common challenge for humans that requires a multi-stakeholder, multi-lateral global governance model.

Supporting facts:

• A global platform would allow multiple stakeholders to contribute to the governance process which would foster accountability, inclusivity, and transparency

• Various international organizations such as ITU and UNCTAD need to be involved in the platform

Topics: AI, Global Governance, Policy-making

Report

China is actively working towards finding a harmonious balance between AI governance and development. The Chinese government has published numerous policies to encourage and promote the growth of the AI industry within the country. They have also implemented measures to regulate data transfer and licensing requirements for AI service providers, aiming to strike a delicate equilibrium between fostering innovation and ensuring responsible and ethical AI practices.

However, a significant challenge faced by the AI industry is the data divide between countries and institutions. Over 130 economies have enacted their own data protection rules, limiting the free flow of data. This poses a considerable obstacle to the AI industry, as data is one of the three key factors essential for AI applications.

The reluctance to share data due to concerns about data value and security further exacerbates the situation. Recognizing the importance of collaboration, the Chinese government acknowledges the need to work hand in hand with the industry, private sectors, and academia.

They understand the need to establish clear responsibilities for data security and determine the appropriate algorithms for data utilization. This collaborative approach promotes transparency and fosters a conducive environment for the advancement of the AI industry. While China has made substantial progress in AI governance, there is still room for improvement.

It is argued that more time is needed to practice and refine the AI governance model. By continuously learning and adapting, China can effectively address the challenges and complexities presented by AI development, ensuring the responsible and ethical use of AI technologies.

On a global scale, there is a suggestion to establish a multi-stakeholder, multi-lateral global platform for AI governance. This platform would allow various stakeholders, including international organizations such as ITU and UNCTAD, to contribute to the governance process. The implementation of such a platform would foster accountability, inclusivity, and transparency in AI governance, recognizing that AI is a common challenge that requires collaboration and joint decision-making.

In conclusion, China is actively working towards finding the right balance between AI governance and development. Through the implementation of policies, collaboration with stakeholders, and continuous refinement of the AI governance model, China aims to ensure responsible and ethical AI practices.

The proposal for a global platform for AI governance reflects the understanding that an inclusive and transparent approach is necessary to address the challenges posed by AI on a global scale.

Arguments

Artificial Intelligence (AI) presents profound opportunities and stark risks

Supporting facts:

• AI’s seamless integration into our social and economic fabric presents both opportunities and risks.

• The advent of AI technology has increased existing divides in the digital realm, raising concerns across digital, data, and innovation sectors.

Topics: Artificial Intelligence, Digital Economy

AI development has led to digital, data, and innovation divides

Supporting facts:

• The digital divide is not just about internet connectivity or bandwidth. It extends to disparities in access to technology based on geography, gender, income, and age.

• The concentration of data collection and usage among a few global entities has created a data divide, placing many developing countries in the role of mere data providers with limited control or benefit.

• This imbalance is further compounded by an innovation divide, where major technological advancements are dominated by a few large platforms, leading to an unequal distribution of economic wealth generated by digital innovations.

Topics: AI, Digital Divide, Data Divide, Innovation Divide

AI should align with universal human rights and shared values

Supporting facts:

• The establishment of the UN Global Digital Compact and the high-level advisory body on AI signify the UN’s commitment to fostering international cooperation and guiding AI towards being a force that unifies rather than divides.

• It is essential that our approach to AI development aligns with the Sustainable Development Goals

Topics: AI, Human Rights

Report

Artificial intelligence (AI) presents profound opportunities and stark risks in our society and economy. The seamless integration of AI technology has raised concerns across various sectors, including digital, data, and innovation. This integration has also highlighted and intensified existing divides in these areas.

One of the key areas of concern is the digital divide. It is not just about internet connectivity or bandwidth; it extends to disparities in access to technology based on factors such as geography, gender, income, and age. This means that certain groups or regions may not have equal access to AI technologies, which can further exacerbate existing inequalities.

Furthermore, the concentration of data collection and usage among a few global entities has led to a data divide. Many developing countries find themselves in the role of mere data providers, with limited control over or benefit from the data they produce.

This imbalance creates an unfair distribution of power and resources, perpetuating technological and economic disparities. In addition to the data divide, there is also an innovation divide. Major technological advancements in the field of AI tend to be dominated by a few large platforms.

This concentration of power results in an unequal distribution of economic wealth generated by digital innovations. Smaller companies and individuals may struggle to compete or benefit from these advancements, reinforcing existing power imbalances. The rapid pace of AI development also poses governance challenges.

Existing frameworks and regulations struggle to keep up with the evolving technology, creating a governance gap. Governments are often lagging behind in regulating AI technologies, leaving ethical, privacy, and security concerns unaddressed. This gap raises the need for a comprehensive global conversation on AI governance to ensure responsible and equitable development and use of AI.

Nevertheless, efforts are being made at an international level to address this issue. The establishment of the UN Global Digital Compact and a high-level advisory body on AI signify the commitment of the United Nations to fostering international cooperation and guiding AI development towards being a force that unifies rather than divides.

These initiatives aim to align AI development with universal human rights and shared values, ensuring that AI technologies are designed and implemented in a manner that benefits all of humanity. In summary, AI presents both opportunities and risks for our society and economy.

However, the integration of AI technology has exacerbated existing divides in the digital, data, and innovation sectors. These divides include the digital divide, data divide, and innovation divide. Additionally, the rapid pace of AI development has created a governance gap that needs to be addressed through comprehensive global conversations on AI governance.

The establishment of international initiatives shows a commitment to ensure that AI aligns with universal human rights and shared values. It is important to approach AI development in a manner that is responsible, ethical, and promotes equitable access and benefits for all.

Arguments

The branding behind AI, using the word ‘intelligence’ to describe this technology is fundamentally flawed.

Supporting facts:

• AI is nothing more than very high-dimensional optimization problems, mathematical processing.

Topics: AI, Branding

Objective for technology should be to create tools that advance society, not compete with human intelligence.

Topics: AI, Societal advancement

Regulating AI is necessary and doesn’t necessarily stifle innovation.

Supporting facts:

• Regulation can potentially halt technology development that competes with human intelligence.

Topics: Regulation, Innovation

There are existing models like internet governance and data governance which can be useful in shaping AI governance.

Supporting facts:

• Internet governance and data governance have been handled at a similar scale.

• Data, which is the raw material for AI, is already governed, indirectly affecting AI regulation.

Topics: AI, Internet governance, Data governance

There are some unique aspects to AI regulation that need to be understood and acknowledged.

Supporting facts:

• AI is data-driven and the current AI is dependent on data.

• The reinforcement of inequality, unfairness and bias is a major issue in AI, linked strongly to data governance.

Topics: AI regulation, Data governance

Zeynep Engin believes making AI regulation profitable should be a priority.

Supporting facts:

• She suggests creating a competitive market for companies to make AI more responsible, safe, and ethical.

Topics: AI regulation, ethical AI, digital economy

Report

One argument highlights that the branding of AI as “intelligence” is fundamentally flawed. It argues that AI is essentially high-dimensional optimization problems and mathematical processing, and using the term “intelligence” to describe it is misleading and inaccurate. Another perspective emphasizes the objective of technology to advance society rather than competing with human intelligence.

It emphasizes the need to develop AI tools that benefit humanity and contribute to societal progress. Regarding regulation, there is a belief that regulating AI is necessary and does not stifle innovation. It acknowledges that AI has the potential to compete with human intelligence and therefore, regulation is essential to address potential risks and ensure responsible use of the technology.

The importance of an iterative development and testing approach for AI in controlled environments is emphasized. This approach is considered more effective than trying to anticipate all challenges in advance. It allows for identifying and resolving issues in a controlled manner, leading to the development of more robust and reliable AI systems.

Existing models such as internet governance and data governance are considered relevant for shaping AI governance. These frameworks have been used to govern internet usage and data handling, which are crucial for the development and regulation of AI. AI regulation needs to address unique aspects such as the reinforcement of inequality, unfairness, and bias in AI systems.

It acknowledges that AI is data-driven and heavily dependent on data, necessitating fair and ethical data governance to address these concerns. The internet and its governance are seen as infrastructure that enables the use of AI on a societal scale.

Many AI technologies would not be prevalent without the internet and its governance framework. Therefore, governing AI should consider the existing framework of internet governance. One proposed solution is to make AI regulation profitable. This approach suggests creating a competitive market for companies to develop more responsible, safe, and ethical AI technologies.

It is believed that incentivizing responsible AI practices through profitability can promote accountability and equity in AI. Overall, the discussions on AI branding, regulation, iterative development, governance, and economic parameters highlight the complex and multifaceted nature of AI technology. These conversations aim to address the challenges and opportunities associated with AI to ensure its responsible and beneficial integration into society.