Ministry of Preschool and School Education

A successful Global Dialogue on AI Governance should lead to practical, inclusive, and action-oriented outcomes rather than just high-level discussions. One key outcome would be a shared understanding among countries and stakeholders on core principles for responsible AI, especially around fairness, accountability, and human oversight. It should also result in clear commitments to support capacity-building in developing countries, ensuring that AI benefits are accessible and not limited to a few regions. Another important outcome would be the creation of collaborative platforms where governments, academia, and practitioners can continue to exchange knowledge and best practices beyond the dialogue. From my perspective, voices from the education sector and the Global South must be meaningfully included, as they are often most affected by rapid technological changes but underrepresented in decision-making spaces. Finally, the dialogue should promote actionable steps toward integrating AI responsibly in sectors like education, where it can enhance learning while safeguarding inclusion, equity, and ethical use. Success would mean moving from ideas to implementation, with a strong focus on long-term impact and global cooperation.

• AI capacity-building
• Social, economic, ethical, cultural, linguistic and technical implications of AI
• Transparency, accountability, and human oversight
• Protection and promotion of human rights

These priorities reflect both the urgency of managing AI risks and the need to ensure its benefits are shared equitably. AI capacity-building is essential, particularly for developing countries, so that institutions, educators, and policymakers can effectively understand, use, and regulate AI technologies. Without this, existing global inequalities may deepen. The protection and promotion of human rights is equally critical, as AI systems can unintentionally reinforce bias, discrimination, or exclusion if not carefully designed and monitored. This connects closely with the need for transparency, accountability, and human oversight, ensuring that AI systems remain understandable, fair, and subject to human control. Finally, understanding the broader social, economic, ethical, and cultural implications of AI is crucial. AI does not operate in isolation; it shapes education systems, labour markets, and social structures. From my experience in education, it is important that AI tools are inclusive, culturally responsive, and aligned with ethical teaching and learning practices. Together, these priorities support a balanced approach that promotes innovation while safeguarding people and societies.

One important cross-cutting issue is the growing impact of AI on education systems, particularly in terms of equity, access, and learning outcomes. While AI has the potential to personalize learning and improve access to quality education, there is also a risk of widening the digital divide if access to technology and digital literacy is uneven across regions and communities. Another emerging concern is the ethical use of AI-generated content, including issues related to misinformation, academic integrity, and the reliability of information. This is especially relevant for young learners and educators who are still adapting to these technologies. Additionally, there is a need to address the environmental impact of AI systems, as large-scale models require significant energy and resources. Sustainable AI development should therefore be part of global discussions. Finally, more attention should be given to the inclusion of underrepresented languages and cultural contexts in AI systems. Ensuring linguistic and cultural diversity in AI development is essential to prevent marginalization and to make AI truly global and inclusive.

In the education sector, particularly in developing and transitioning contexts, gaps in AI governance are already having visible impacts. One of the main challenges is the lack of clear guidelines on the ethical and responsible use of AI in classrooms. Educators and institutions are increasingly using AI tools, but often without sufficient training or regulatory direction, which raises concerns around data privacy, bias, and academic integrity. Another key challenge is unequal access to digital infrastructure and AI literacy. While some institutions can adopt advanced technologies, others are left behind, widening the digital divide and limiting equitable learning opportunities. Additionally, limited awareness of AI governance frameworks means that many stakeholders are not fully equipped to critically assess or regulate AI systems. At the same time, these developments present significant opportunities. AI has strong potential to enhance teaching and learning through personalized education, improved assessments, and more efficient administrative processes. It can also support teacher training and capacity building, especially in resource-constrained environments. From a broader perspective, there is an opportunity for countries and sectors to proactively shape AI governance frameworks that are inclusive, context-sensitive, and aligned with human rights principles. Strengthening capacity-building initiatives, promoting digital literacy, and encouraging collaboration between governments, educators, and technology developers can help ensure that AI is used responsibly and equitably. Overall, addressing these governance gaps is essential to maximize the benefits of AI while minimizing its risks.

The AI Dialogue can play a crucial role in strengthening international cooperation by providing an inclusive platform where diverse stakeholders-governments, academia, practitioners, and civil society-can come together to share perspectives, align priorities, and co-create solutions. One of its key contributions would be bridging the gap between developed and developing countries by ensuring that all voices are represented in shaping global AI governance frameworks. It can also help foster trust and coordination by encouraging the exchange of best practices, policy approaches, and lessons learned across regions. This is particularly important given the fast-paced nature of AI development, where fragmented or inconsistent regulations can create challenges. Additionally, the Dialogue can support the development of shared principles and voluntary guidelines that promote responsible, ethical, and human-centred AI. It can act as a catalyst for capacity-building initiatives, helping countries strengthen their institutional and technical readiness to govern AI effectively. Importantly, the AI Dialogue can move beyond discussion to enable collaboration through partnerships, joint initiatives, and knowledge-sharing networks. By connecting global, regional, and local efforts, it can help ensure that AI governance is not only coordinated at the international level but also relevant and adaptable to different contexts. Ultimately, its role should be to promote cooperation that is inclusive, practical, and focused on long-term impact.

The AI Dialogue can build upon a range of existing global and regional initiatives that are already shaping AI governance. These include efforts by international organizations, multilateral forums, and partnerships focused on responsible AI, digital transformation, and sustainable development. For example, frameworks and recommendations developed by organizations such as UNESCO, OECD, and other UN agencies provide important foundations on ethics, human rights, and policy guidance. It can also connect with ongoing capacity-building and research initiatives in education, digital literacy, and AI innovation, particularly those supporting developing countries. Regional collaborations and public-private partnerships are already contributing valuable insights and practical tools that can be scaled or adapted. The added value of the AI Dialogue lies in its ability to bring these fragmented efforts together into a more coordinated and inclusive global conversation. It can help avoid duplication, identify gaps, and promote alignment across different initiatives. Furthermore, it can ensure stronger representation of underrepresented regions and sectors, including education and civil society. By acting as a bridge between policy and practice, the Dialogue can translate existing principles into actionable strategies and foster collaboration across stakeholders. This would enhance coherence in global AI governance and support more effective and equitable implementation of AI-related policies worldwide.

Different stakeholders can contribute to the AI Dialogue by bringing their unique perspectives and practical experiences into the discussion. From my experience in education and teacher training, practitioners and educators can share how AI is actually being used on the ground, including both its benefits and challenges. Governments and policymakers can provide regulatory direction, while researchers and technology developers can contribute technical expertise and innovation. Civil society organizations can ensure that issues of equity, inclusion, and ethics remain central. To make the Dialogue effective, it should be structured in a way that encourages both high-level discussions and practical exchanges. A combination of plenary sessions, thematic breakout groups, and interactive workshops would allow participants to engage more meaningfully. Smaller group discussions are particularly important to ensure that participants from diverse backgrounds feel comfortable sharing their perspectives. It would also be valuable to include regional consultations or parallel sessions to reflect different local contexts. Ensuring opportunities for participants to contribute before and after the Dialogue, through surveys, collaborative platforms, or follow-up working groups, can help maintain continuity and turn discussions into action. Overall, the format should be inclusive, interactive, and focused on real-world impact.

In global discussions on AI governance, several important voices remain underrepresented, particularly those from developing countries, educators, and grassroots practitioners. From my experience working in both India and Uzbekistan, I have seen that those directly implementing AI tools in classrooms or institutions often have limited opportunities to contribute to policy discussions, despite being deeply affected by these technologies. Students and young people are also underrepresented, even though they are among the primary users of AI-driven tools. Their perspectives on learning, digital access, and ethical concerns are critical for shaping responsible AI use. Additionally, communities from linguistically and culturally diverse backgrounds are often overlooked, which can lead to AI systems that do not fully reflect global diversity. To address this, efforts should be made to actively include these groups through targeted outreach, regional representation, and accessible participation formats. This could include offering virtual participation options, language support, and partnerships with local institutions and organizations. Creating safe and inclusive spaces for dialogue, where participants feel their contributions are valued, is equally important. Expanding participation in this way would lead to more balanced, context-sensitive, and effective AI governance.

To foster meaningful and dynamic engagement, the AI Dialogue should move beyond traditional panel discussions and include more interactive and participatory formats. From my experience in teaching and training, interactive methods such as case-based discussions and problem-solving workshops are far more effective in encouraging active participation and deeper understanding. One useful approach could be scenario-based simulations, where participants work through real-world AI governance challenges, such as ethical dilemmas in education or data privacy issues. This would allow stakeholders to better understand different perspectives and practical implications. Another innovative format could be "learning labs" or "practice-sharing sessions," where practitioners, educators, and organizations present real examples of how they are using or regulating AI. This would help bridge the gap between theory and practice. Digital engagement tools, such as live polling, collaborative platforms, and virtual breakout rooms, can also make discussions more inclusive, especially for participants joining remotely. Additionally, incorporating youth panels or storytelling sessions can bring in fresh perspectives and make the Dialogue more engaging. Overall, the goal should be to create a space that is interactive, inclusive, and action-oriented, where participants are not just listeners but active contributors to shaping AI governance.

Several existing policies and practices provide useful examples of how AI governance can be approached effectively. International frameworks such as UNESCO's Recommendation on the Ethics of Artificial Intelligence emphasize human rights, transparency, and inclusivity, offering practical guidance for countries developing their own policies. Similarly, the OECD AI Principles promote responsible and trustworthy AI, encouraging fairness, accountability, and safety in AI systems. From a practical perspective, capacity-building initiatives and digital literacy programs are essential. In the education sector, integrating AI training for teachers and students helps ensure that these tools are used responsibly and effectively. In my own experience, using digital and AI-supported learning platforms in classrooms has shown that when educators are trained and supported, AI can significantly enhance learning outcomes while maintaining ethical standards. Another important approach is the use of human-in-the-loop systems, where AI supports decision-making but does not replace human judgment. This is particularly relevant in education and public services, where fairness and accountability are critical. Open and collaborative platforms also play a key role. Open-source AI tools and shared datasets can increase transparency and allow broader participation, especially from developing contexts. At the same time, clear data protection policies and ethical guidelines are necessary to safeguard privacy and prevent misuse. Overall, effective AI governance requires a combination of strong policy frameworks, practical capacity-building efforts, and inclusive, collaborative approaches that ensure AI benefits society as a whole.