TeachSomebody's Input for the Global Dialogue on AI Governance

This submission is respectfully provided as an input to the United Nations Global Dialogue on AI Governance. It presents practical recommendations for strengthening international AI governance through adaptive, evidence-based, and collaborative approaches. The complete submission is available here:

UN Global Dialogue on AI Governance – Written Inputs

We hope these recommendations contribute to an inclusive and action-oriented dialogue that supports responsible AI development and international cooperation.

1. In your opinion, what outcomes would make the first Global Dialogue on AI Governance a success?

A successful first Global Dialogue on AI Governance would not be defined by a treaty or strict regulations, but by alignment, clarity, and a shared foundation for future cooperation.Firstly, success would mean establishing a unified language and definitions. Today, countries and organizations use different meanings for terms like AI, AI governance, risk, safety, and alignment. Without common terminology, global cooperation is extremely difficult. Agreeing on baseline definitions would be one of the most important outcomes.Secondly, the dialogue should produce shared governance principles that most jurisdictions can support. These could include transparency, accountability, safety, human oversight, fairness, privacy protection, and sustainability. The goal would not be identical laws, but compatible principles that countries can implement within their own legal systems.Thirdly, a key outcome would be agreement that AI governance must respect fundamental human rights across all jurisdictions. Even if regulatory approaches differ, there should be global consensus that AI systems must not undermine human dignity, freedom, privacy, or democratic processes.Fourthly, success would include identifying what issues require global cooperation (e.g., frontier AI safety, misuse, autonomous weapons, cross-border data, standards) versus what can remain national regulation.Finally, the dialogue would be successful if it creates ongoing structures for cooperation; working groups, standards bodies, information-sharing mechanisms, and future meetings; so this is the beginning of a process, not a one-time event.In short, success would not be immediate regulation, but a shared vocabulary, common principles, human-rights commitments, and a roadmap for global coordination on AI governance.

Thematic Priorities

2. From your perspective, which of the following thematic areas identified by the General Assembly Resolution 79/325 for the AI Dialogue reflect your priorities for urgent action and active engagement?

Safe, secure and trustworthy AI; AI capacity-building; Protection and promotion of human rights; Transparency, accountability, and human oversight

3. Please briefly explain your selection.

Yes, there are several cross-cutting and emerging issues that are not always fully captured by standard AI governance themes but are increasingly important for global AI discussions.One important cross-cutting issue is compute governance and access to AI infrastructure. The development of advanced AI systems is increasingly dependent on large-scale computing power and access to high-quality data. This creates concentration of power in a small number of companies and countries. Governance discussions should therefore also address fair access to compute, cloud infrastructure, and datasets, as this will shape global participation in AI development and the global digital economy.Another emerging issue is environmental and energy impact of AI. Training and operating large AI models consumes significant amounts of energy and water. As AI adoption grows, its environmental footprint will become a major policy issue. Sustainable AI development and transparency about environmental impact should be part of future governance frameworks.A third cross-cutting issue is the impact of AI on labour markets and economic inequality. AI has the potential to transform jobs, productivity, and economic structures. Without proper policies, AI could increase inequality between countries and within societies. Governance discussions should therefore include workforce transition, education, reskilling, and fair distribution of AI benefits.Finally, an emerging issue is human-AI interaction and societal dependence on AI systems, including risks related to misinformation, manipulation, over-reliance on automated systems, and impacts on education and critical thinking. These societal and cultural impacts are often less visible than technical risks but may have very large long-term consequences.Generally speaking, beyond technical safety and governance frameworks, access to compute, environmental sustainability, economic impacts, and societal dependence on AI are important cross-cutting issues that should be included in global AI governance discussions.

5. How are the governance gaps and related developments/advances in the thematic areas you selected above affecting your country, region, or sector? Please highlight the most significant challenges.

Governance gaps and developments in safe and trustworthy AI, human rights, transparency, and AI capacity-building are already significantly affecting Western Europe, including the Netherlands, particularly in terms of implementation capacity and regulatory alignment.At the European level, the EU AI Act contributes to the development of safe, secure and trustworthy AI and strengthens transparency, accountability and the protection of fundamental rights through a risk-based regulatory framework. However, a major governance gap lies in implementation and enforcement capacity, as many organisations and public institutions still lack the technical expertise and governance structures needed to comply with the new requirements.In the Netherlands, the Strategic Action Plan for Artificial Intelligence supports AI capacity-building through investments in education, skills development, research and innovation, and public-private partnerships, while also strengthening the foundations for trustworthy and human-centric AI, including ethics, human rights, transparency, and safety.The Netherlands has also developed governance tools such as the AI Impact Assessment, which supports transparency, accountability, and human oversight in AI projects, and the Fundamental Rights and Algorithms Impact Assessment, which specifically addresses risks to fundamental rights when algorithms are used, particularly in the public sector.The most significant challenge in Western Europe is therefore operationalising AI governance frameworks and building implementation capacity, while the main opportunity is positioning the region as a global leader in trustworthy, human-centric AI governance and responsible AI innovation.

6. What role can the AI Dialogue play in advancing international cooperation on AI governance?

The AI Dialogue can play an important role in advancing international cooperation on AI governance by serving as a platform for coordination, knowledge sharing, and the development of common approaches to AI governance across different regions and regulatory systems. First, the Dialogue can help develop a shared understanding and common terminology around key concepts such as AI, AI governance, risk, safety, transparency, and human oversight. A common vocabulary is essential to enable meaningful international cooperation and avoid fragmentation in governance approaches. Second, the Dialogue can support the development of non-binding common principles and best practices for safe, trustworthy, and human-centric AI. Not all countries will adopt the same regulations, but alignment on core principles; such as safety, accountability, transparency, human rights, and human oversight; can help ensure interoperability between different governance frameworks. Third, the Dialogue can facilitate capacity-building and knowledge exchange, particularly supporting developing countries in building regulatory capacity, technical expertise, and governance frameworks for AI. This can help prevent a global AI governance gap and promote more inclusive participation in AI development and governance. Fourth, the Dialogue can help identify areas that require international coordination, such as frontier AI risks, standards development, evaluation and auditing methods, compute governance, and cross-border AI systems. Finally, the Dialogue can serve as a bridge between governments, industry, academia, and civil society, ensuring that AI governance is developed through multi-stakeholder cooperation. In addition, the AI Dialogue can play a key role in reducing regulatory fragmentation, promoting shared principles, supporting capacity-building, and creating ongoing international cooperation mechanisms for AI governance.

7. What are some of the existing initiatives, partnerships, or mechanisms that the AI Dialogue should build upon or connect with, and what added value could the AI Dialogue bring?

The AI Dialogue should build upon existing international initiatives, partnerships, and governance frameworks to avoid duplication and promote coherence in global AI governance.Important initiatives include the work of the OECD on AI principles and policy guidance, the Global Partnership on AI which focuses on responsible AI and international collaboration, and the UNESCO Recommendation on the Ethics of Artificial Intelligence. Regulatory developments such as the EU AI Act and risk management frameworks developed by the National Institute of Standards and Technology are also influencing global AI governance approaches.In addition, technical standard-setting bodies such as the International Organization for Standardization and the International Electrotechnical Commission play an important role in developing AI standards, for example ISO/IEC 42001, which specifies requirements for establishing, implementing, maintaining, and continually improving an Artificial Intelligence Management System (AIMS) within organizations. Such standards are important for translating high-level governance principles into practical organisational processes and compliance mechanisms.Therefore, the AI Dialogue should connect policy initiatives, regulatory frameworks, and technical standards, and thereby help to reduce fragmentation and improve interoperability between different governance approaches.The added value of the AI Dialogue would be to provide a global and inclusive platform under the United Nations to align terminology, share best practices, support capacity-building, and identify governance gaps that require international cooperation. It could also help bridge the gap between policy, technical standards, and implementation practices, contributing to a more coherent global AI governance ecosystem.

8. How can different stakeholders contribute to the AI Dialogue? Please share recommendations for the format and structure of the AI Dialogue.

Different stakeholders can contribute to the AI Dialogue by bringing complementary expertise, perspectives, and practical experience in AI development, deployment, governance, and societal impacts. Effective AI governance requires a multi-stakeholder approach, involving governments, international organisations, private sector companies, academia, technical standard-setting bodies, and civil society organisations.Governments can contribute by sharing regulatory approaches, national strategies, and lessons learned from implementing AI governance frameworks. The private sector can provide technical expertise, practical implementation experience, and insights into innovation and market developments. Academia and research institutions can contribute independent research, risk assessments, and evaluation methodologies. Civil society organisations can help ensure that human rights, inclusion, consumer protection, and societal impacts are adequately considered. Technical standard-setting organisations can contribute by developing standards, metrics, and certification approaches that support the implementation of AI governance frameworks.Regarding the format and structure, the AI Dialogue could be organised as a multi-stakeholder platform with thematic working groups, for example on AI safety, human rights, standards and evaluation, capacity-building, and governance frameworks. Regular plenary meetings could be complemented by technical workshops, expert panels, and regional consultations to ensure broad participation.It would also be useful to create knowledge-sharing mechanisms, such as a repository of best practices, case studies, policy frameworks, standards, and impact assessment tools. Capacity-building sessions and training workshops could support countries with less developed AI governance frameworks.Lastly, the dialogue should not be a one-time event but a continuous process, with clear outputs such as recommendations, best practice guidelines, and voluntary frameworks that can support international cooperation on AI governance.Overall, a structured, multi-stakeholder, and continuous dialogue process would help ensure inclusive, practical, and internationally coordinated AI governance.

9 Which voices, communities, or perspectives are currently underrepresented in global discussions on AI governance? How could they be included?

Several voices and perspectives are currently underrepresented in global discussions on AI governance, particularly those from developing countries, small and medium-sized enterprises (SMEs), workers and labour organisations, civil society from the Global South, and communities that are directly affected by AI systems rather than developing them. In particular, migrants, asylum seekers, youth, and other vulnerable or marginalised groups are often underrepresented in AI governance discussions, even though they may be disproportionately affected by AI systems used in areas such as border control, migration management, welfare systems, hiring, education, and law enforcement. These groups are often subject to automated decision-making but rarely involved in discussions about how these systems are designed, governed, or evaluated.Young people should also be more actively involved, as they will be most affected by the long-term societal, educational, and labour market impacts of AI. Youth perspectives are important for discussions on education, digital literacy, the future of work, and responsible technology use.To include these groups, the AI Dialogue could support inclusive participation through regional consultations, youth forums, civil society participation mechanisms, and partnerships with NGOs and community organisations that represent affected communities. Financial support for participation, remote participation options, and capacity-building programmes would also help ensure broader representation, particularly for participants from developing countries and underrepresented communities.In sum, including underrepresented voices would help ensure that AI governance is inclusive, human-rights-based, and responsive to real-world societal impacts, rather than being shaped only by governments and large technology companies. This would strengthen the legitimacy, fairness, and effectiveness of global AI governance discussions.

10. What innovative engagement formats could most effectively foster meaningful and dynamic engagement during the AI Dialogue?

Innovative engagement formats could help ensure that the AI Dialogue is interactive, inclusive, and forward-looking rather than limited to traditional conference discussions. A mix of policy discussions, practical workshops, and future-oriented exercises would foster more meaningful engagement.Firstly, multi-stakeholder roundtables and thematic working groups would allow governments, industry, academia, civil society, and technical experts to discuss specific issues such as AI safety, human rights, standards, and capacity-building in smaller, more interactive settings.Secondly, the Dialogue could include policy labs or governance labs, where participants work together on practical case studies, such as conducting an AI impact assessment, designing transparency mechanisms, or developing governance approaches for high-risk AI systems. This would support practical knowledge exchange and capacity-building.Thirdly, strategic foresight workshops, scenario planning exercises, and speculative design sessions could help participants explore long-term AI futures, for example by imagining AI governance challenges 20–50 years from now and identifying what governance mechanisms would be needed today. These formats can support more forward-looking and preventive governance approaches.Fourthly,The Dialogue could also include youth forums, civil society dialogues, and regional consultations to ensure that underrepresented voices are included in dedicated engagement formats.Lastly, hybrid participation formats and online collaboration platforms could allow continuous engagement between meetings and enable participation from stakeholders who cannot travel, particularly from developing countries and smaller organisations.Altogether, combining multi-stakeholder discussions, practical policy labs, and future-oriented engagement formats such as foresight and speculative design would make the AI Dialogue more inclusive, dynamic, and outcome-oriented.

11. Please share examples of policies, practices, platforms, or approaches that promote effective AI governance or offer concrete solutions to addressing its challenges.

One example is the use of algorithm registers by public authorities, such as municipal algorithm registers, which increase transparency by publicly documenting where and how algorithms are used in government decision-making. These registers improve transparency, accountability, and public trust in the use of AI in the public sector.Another important practice is the use of AI impact assessments, which help organisations identify risks related to fundamental rights, safety, and societal impacts before deploying AI systems. Impact assessments support responsible decision-making, documentation, and risk mitigation throughout the lifecycle of AI systems. Regulatory sandboxes are another promising approach. These allow organisations to test AI systems under regulatory supervision in a controlled environment, helping regulators and innovators better understand risks while supporting innovation. Sandboxes are particularly useful for emerging technologies where regulation is still evolving.AI auditing and evaluation practices are also increasingly important. Independent audits, conformity assessments, and evaluation frameworks help ensure that AI systems meet safety, fairness, and transparency requirements and comply with governance frameworks. In addition, multi-stakeholder governance approaches, where governments, industry, academia, and civil society collaborate on standards, guidelines, and best practices, are essential for effective AI governance because AI impacts many sectors and society as a whole. Overall, effective AI governance is not based on a single policy or regulation, but on a combination of transparency tools, impact assessments, regulatory sandboxes, auditing mechanisms, and multi-stakeholder governance approaches, which together help manage risks while supporting responsible innovation.