Indiana University

The first Global Dialogue on AI Governance would be a success if it establishes a legitimate, inclusive, and actionable foundation for sustained multilateral cooperation, rather than rushing toward premature binding agreements. This means ensuring meaningful participation from the Global South, small states, civil society, academia, and industry, so that governance is not dictated by a few technologically dominant powers. Delegates should leave with a shared vocabulary and risk taxonomy, enabling future negotiations to progress on common ground. Success also requires alignment—not duplication—with existing frameworks such as the Global Digital Compact, UNESCO's AI Ethics Recommendation, the OECD AI Principles, and regional instruments like the EU AI Act. Tangible deliverables should include a clear roadmap, working groups on capacity building, scientific assessment, and incident reporting, along with concrete commitments to bridge the capacity divide through funding, technical support, and training, so developing nations can participate as rule-makers rather than rule-takers. Ultimately, the Dialogue will be judged a success if it institutionalizes recurring, transparent engagement that builds the trust necessary for future commitments on safety, accountability, and equitable benefit-sharing of AI's opportunities

• Safe, secure and trustworthy AI
• AI capacity-building
• Social, economic, ethical, cultural, linguistic and technical implications of AI
• Transparency, accountability, and human oversight

These four priorities were chosen because they collectively address the most urgent risks, structural inequities, and operational safeguards needed to ensure AI benefits humanity equitably and responsibly.Safe, secure and trustworthy AI is the foundational prerequisite for public trust and responsible adoption. As AI systems become increasingly embedded in critical sectors-healthcare, finance, infrastructure, education, and security-addressing risks such as misuse, bias, cyber vulnerabilities, misinformation, and unintended consequences is essential. Without credible safety and security guarantees, the legitimacy of AI deployment and global cooperation itself is undermined. AI capacity-building is indispensable for inclusive governance. Without deliberate investment in infrastructure, talent, data ecosystems, and institutional readiness-particularly in the Global South-AI risks deepening existing digital divides. Capacity-building ensures that all nations and communities can participate as co-creators of norms and beneficiaries of innovation, not passive recipients of technologies designed elsewhere. The social, economic, ethical, cultural, linguistic and technical implications of AI must be addressed holistically. AI is not merely a technical artifact; it reshapes labor markets, cultural expression, linguistic diversity, and social cohesion. Prioritizing this area ensures governance is human-centered and context-sensitive, safeguarding underrepresented languages, cultures, and communities from marginalization in AI development. Transparency, accountability, and human oversight translate principles into practice. Clear disclosure obligations, auditability, redress mechanisms, and meaningful human control over high-stakes decisions are the operational safeguards that make trust, safety, and rights enforceable rather than aspirational.Together, these priorities form a coherent agenda: safety builds trust, capacity enables inclusion, holistic analysis ensures relevance, and transparency secures accountability.

While the themes identified in Resolution 79/325 provide a comprehensive foundation, several cross-cutting and emerging issues deserve explicit attention to ensure the Dialogue remains forward-looking and responsive to rapidly evolving realities. 1. Environmental Sustainability of AIThe ecological footprint of AI-energy consumption, water use for data center cooling, rare-earth mineral extraction, and e-waste-is escalating rapidly with the rise of large-scale models. Aligning AI governance with climate commitments and the Sustainable Development Goals is urgent but underrepresented in current themes. 2. AI and Information IntegrityThe proliferation of generative AI, deepfakes, and synthetic media poses unprecedented risks to democratic processes, public discourse, and social trust. Safeguarding information ecosystems, electoral integrity, and media pluralism requires dedicated attention beyond generic "trustworthy AI." 3. AI's Impact on Labor and Economic InequalityThe future of work-including automation-driven displacement, algorithmic management, gig economy dynamics, and the concentration of AI-generated economic value-demands focused governance to prevent widening inequality within and between nations. 4. Concentration of Compute, Data, and Market PowerThe increasing concentration of AI capabilities in a few corporations and jurisdictions raises concerns about monopolistic control, geopolitical dependencies, and barriers to entry. Governance must address competition, access to compute, and equitable distribution of AI's foundational resources. 5. Children's Rights and AIThe impact of AI on children and youth-through education, social media, targeted advertising, and mental health-warrants specific protections grounded in the Convention on the Rights of the Child. 6. AI in Peace, Security, and Military ApplicationsThe use of AI in autonomous weapons, surveillance, and conflict raises existential questions requiring coordinated international attention, including linkages with disarmament frameworks. 7. Intergenerational and Long-Term RisksFinally, governance should consider long-horizon risks, including frontier AI safety and obligations to future generations.

Challenges Safe, secure and trustworthy AI: The absence of harmonized safety standards and independent evaluation mechanisms exposes users to biased, unreliable, or insecure systems, especially when foreign-developed models are deployed without local testing or cultural adaptation. Cybersecurity risks, AI-enabled fraud, and model misuse are rising faster than regulatory capacity can respond. AI capacity-building: Persistent gaps in compute infrastructure, high-quality local data, skilled talent, and research funding leave many regions dependent on external providers. This dependency limits sovereignty over critical systems, constrains innovation, and risks entrenching a technological divide that mirrors historical inequities. Social, economic, ethical, cultural, and linguistic implications: Most frontier AI models are trained predominantly on English-language and Western-centric data, marginalizing low-resource languages, Indigenous knowledge, and local cultural contexts. This threatens linguistic diversity, perpetuates bias, and reduces the relevance and accuracy of AI tools for underserved populations. Labor market disruptions and unequal distribution of AI-driven productivity gains further strain social cohesion.Transparency, accountability, and human oversight: Limited disclosure requirements, opaque algorithmic decision-making in public services (e.g., welfare, immigration, policing), and weak redress mechanisms erode public trust and create accountability vacuums when harms occur. Opportunities Despite these challenges, significant opportunities exist:Leapfrogging through targeted investment in AI for health, agriculture, education, and climate adaptation.Developing locally grounded AI ecosystems—including sovereign compute, multilingual datasets, and regional models.Establishing regional regulatory cooperation to pool expertise and harmonize standards.Leveraging AI to accelerate progress on the SDGs while embedding human rights and inclusion by design.Closing governance gaps collaboratively can transform these challenges into shared, equitable gains…

The Global Dialogue on AI Governance can serve as the central, inclusive, and legitimate multilateral platform for advancing international cooperation on AI, complementing rather than duplicating existing initiatives. As a UN-convened forum, it can ensure that all Member States—especially those underrepresented in venues like the G7, G20, GPAI, or OECD—have an equal voice, amplifying perspectives from the Global South, civil society, and vulnerable communities. The Dialogue can bridge today's fragmented governance landscape by fostering interoperability among frameworks such as the Global Digital Compact, UNESCO's Ethics Recommendation, the OECD AI Principles, and regional instruments like the EU AI Act—reducing duplication without imposing uniformity. By establishing shared vocabularies, risk taxonomies, and evidence bases (anchored in the work of the Independent International Scientific Panel on AI), it can build the trust needed for deeper cooperation. It can also mobilize financial, technical, and educational resources to close capacity gaps, ensuring developing nations participate as rule-makers rather than rule-takers. As a recurring, transparent process, the Dialogue can sustain momentum, track progress, surface emerging risks, and hold stakeholders accountable—ultimately transforming AI governance from fragmented competition into coordinated global stewardship of a shared transformative technology.

The AI Dialogue should build upon a rich ecosystem of existing initiatives while adding distinct value through its universal legitimacy and convening power. Key frameworks to connect with include UN-led efforts such as the Global Digital Compact, UNESCO's Recommendation on the Ethics of AI, the work of the UN High-Level Advisory Body on AI, and ITU's AI for Good; multilateral and plurilateral instruments like the OECD AI Principles, GPAI, the G7 Hiroshima AI Process, G20 AI commitments, and the Council of Europe Framework Convention on AI; regional frameworks including the EU AI Act, the African Union Continental AI Strategy, and the ASEAN Guide on AI Governance and Ethics; and scientific and multi-stakeholder bodies such as the Independent International Scientific Panel on AI, the network of AI Safety Institutes, and standards organizations like IEEE and ISO/IEC. The AI Dialogue's added value lies in its ability to universalize participation—ensuring all 193 Member States, especially those in the Global South, shape global norms; bridge fragmentation by mapping linkages across technical, ethical, human rights, and development tracks; anchor legitimacy in the UN Charter and international human rights law; integrate development priorities such as capacity-building and equitable access; and sustain coherence through recurring engagement informed by impartial scientific evidence. Rather than duplicating existing efforts, the Dialogue can serve as the connective tissue that translates diverse initiatives into a coherent, inclusive, and legitimate global governance architecture.

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