Future of Life Institute (FLI), The Future Society, Global Center on AI Governance, Center for Long-Term Cybersecurity (CLTC) AI Security Initiative, AI Safety Connect, Fathom, AI Safety Asia, Collective Intelligence Project, Future Shift Labs, World Council of Churches, Singapore AI Safety Hub, ILINA Program, Pour Demain

The first Global Dialogue will have succeeded if it translates the UN's convening legitimacy, in which all Member States participate equally, into visible, inclusive progress on AI governance that no unilateral or regional process can replicate. AI development today is shaped by powerful forces: optimization for user engagement, competition to capture value from automation, and divergent national and commercial approaches. A successful Dialogue would demonstrate that Member States, acting together, can direct this momentum toward human well-being, equitable benefit-sharing, and the protection of human rights and fundamental freedoms, ensuring that the benefits of AI are broadly shared rather than a concentrated few. Several indicators would signal success. One would be a shared articulation of the values underpinning AI governance, consistent with UN instruments: human agency; shared prosperity and equitable access; human dignity; human rights and self-determination; and responsibility and accountability. Safe, secure and trustworthy AI systems make these values achievable, supported by a shared understanding of the risks of common concern and of foundational safety principles that can guide AI development globally. Another would be convergence on governance itself, the Dialogue's mandate. This would look like Member States exchanging frameworks and regulatory experience across regions, surfacing common principles, and identifying practical avenues for cooperation that build on existing commitments. Useful signals would include convergence around governance approaches, shared risk taxonomies, regulatory cooperation, capacity-building, access to AI's benefits, bridging digital divides, and safeguards for human rights and fundamental freedoms. A further indicator would be an accountable path forward which could include a manageable set of follow-up workstreams, regionally balanced co-leadership, a clear reporting cycle, and a defined route for stakeholders to inform future deliberations.

• Safe, secure and trustworthy AI
• Interoperability of governance approaches
• Protection and promotion of human rights
• Transparency, accountability, and human oversight

While all these areas warrant urgent attention, we're best positioned to contribute meaningfully in these four areas, with AI capacity-building as a cross-cutting enabler: 1. Safe, secure and trustworthy AI: Human well-being is enabled through AI systems that we can understand, control and that enhance rather than harm. Safety and security is the prerequisite. When States establish a shared understanding of unacceptable risks, safety becomes a competitive advantage, preventing fragmentation and enabling trustworthy development across all countries. 2. The interoperability and compatibility of artificial intelligence governance approaches; As AI governance efforts multiply, fragmentation increases. National, regional, and international initiatives are emerging rapidly, often without clear paths to coordination. With effective coordination, differing approaches can be made complementary, providing coherence for governments, companies, regulators, civil society and the public. The Dialogue can serve as a space to share experiences and develop governance approaches that support coordination across jurisdictions and help ensure meaningful protections for people, while respecting the diversity of national and regional frameworks. Additionally, the Dialogue should underscore that effective assurance and verification infrastructure is needed to give AI governance approaches practical effect. 3. Protection and promotion of human rights: Safe, secure and trustworthy AI cannot be achieved through technical measures alone. Human rights protections are integral to it. Building on longstanding international commitments such as the Universal Declaration of Human Rights, AI development must respect, protect and fulfill civil and political, as well as economic, social and cultural rights, advancing human agency, dignity and self-determination. These rights are foundational to AI governance, grounding its development. 4. Transparency, accountability and human oversight: Credible governance empowers all States to understand AI systems and decisions, hold actors accountable for harms and ensure that humans retain meaningful control and oversight over AI models. Through transparency and peer learning, safety standards can be verified, capacity-building outcomes can be audited and human rights can be protected globally.

Identifying where international coordination is required: AI capabilities are improving rapidly, with gains in mathematics, coding, and autonomous operations arriving faster than safety benchmarks can track. As systems become more capable, the International AI Safety Report 2026 notes risks are becoming harder to detect before deployment, making shared understanding of which capabilities warrant collective attention urgent. The Dialogue, building on the work of the Independent International Scientific Panel on AI, can help States identify priority domains, including but not limited to risks to children, large-scale manipulation and threats to information integrity, the challenge of maintaining human oversight as AI systems become more capable and autonomous, and AI applications affecting fundamental rights and justice. Some AI risks extend beyond the Dialogue's mandate into areas addressed by other UN processes. Coherence across these processes will be essential to effective global AI governance. The Dialogue presents an opportunity to identify which risks are cross-border in character and facilitate exchange on where coordination is required. Cross-border incident communication and response: Currently, no clear diplomatic or technical path exists for communicating AI incidents with cross-border implications. Most incident discovery is reactive and even post-hoc monitoring and documentation remains geographically imbalanced. Countries lacking technical infrastructure have no established forum to raise concerns internationally. The Dialogue could explore how Member States might better communicate and coordinate when AI incidents have cross-border implications. Equitable distribution of AI's economic benefits: Building on the AI capacity-building theme, the Dialogue should also include a focus on ensuring that AI's economic benefits are broadly and equitably shared. This includes frameworks that make AI-related economic opportunities accessible to all and participatory approaches embedded early in AI development so that affected communities can shape how benefits are distributed.

Governance gaps are producing measurable harms today that become increasingly difficult to reverse as AI integrates into critical decisions. Early governance action is more effective than later correction and can help avoid large-scale harm. These harms persist in part because governance capacity is unevenly distributed, resulting in AI policymaking that may not adequately reflect affected communities or the broader public interest. Harms to vulnerable populations: AI systems lack adequate safeguards for children and women, expanding new forms of violence. Chatbots engage in sexualized exchanges with minors, provide self-harm and suicide guidance and generate exploitative material, while deepfakes and AI-enabled harassment produce non-consensual sexual imagery and sextortion targeting women and girls. These harms arise from design choices: minimal content restrictions, engagement-optimized algorithms affirming harmful narratives and platform policies framing abusive outputs as user misuse. Labor and Economic Dignity: Algorithmic management systems control hiring, compensation, work allocation and performance monitoring without adequate human oversight. AI-driven job displacement threatens tens of millions globally without transition support. Labor-intensive sectors like call centers or IT back office functions face elimination. Data annotation proceeds with minimal compensation and inadequate protections. Bias in Critical Systems: AI deployed in hiring, criminal justice and financial services reproduces existing inequalities. Marginalized communities bear harms from biased decisions in systems they cannot shape. Lack of Transparency AI systems are producing consequential outputs that are often difficult to explain, independently verify or contest. These outputs increasingly shape decisions in housing, education, employment, public benefits, and criminal justice. Information Integrity: AI-generated deepfakes, scams and targeted manipulation enable misinformation at scale. No adequate global governance frameworks prevent targeted disinformation campaigns, which risk undermining democratic values and public trust. Cultural and Linguistic Erasure: AI systems developed on limited linguistic and cultural data risk undermining cultural diversity and linguistic rights essential to human dignity. Environmental Harms: Compute infrastructure consumes energy and water without accountability for environmental impact, disproportionately impacting resource-scarce regions. The associated materials required to construct and develop physical infrastructure are in direct competition with resources needed for renewable energy transition.

The UN Global Dialogue can advance international cooperation on AI governance in a way that complements other international efforts, drawing on the convening power of a universal forum. It reinforces shared values that steer AI development to serve humanity, and provides a reference point for governance efforts at national, regional and international levels. It promotes human rights-grounded governance that can drive transparency, accountability, and meaningful human oversight in AI systems. Member States can respond coherently rather than in isolation, reducing risk of fragmentation when serious risks emerge. The Dialogue can also enable Member States to learn from one another's experience: which governance approaches are working, where implementation challenges arise, where divergences are emerging. This transparency supports voluntary convergence and identifies gaps requiring collective attention. One such gap is the absence of a shared approach to prevention. From disaster risk reduction to public health, international experience shows that early action is more effective and less costly than response after harms have materialized. This is especially salient for AI, where certain risks, whether to essential services, public health systems, or information integrity, may be irreversible and cross borders rapidly. The Dialogue can create space for exchanging on preventive approaches that remain attentive to the capacity constraints and development priorities of all Member States. Moving from shared frameworks to meaningful implementation requires capacity. Without sustained support for AI governance capacity building, particularly for States that lack AI Safety Institutes or comparable national bodies, shared frameworks risk uneven implementation with the burden of harm falling on States least equipped to detect and respond.

The Dialogue should complement and build on a wide range of existing efforts including: International governance frameworks: UN Global Digital Compact; UNESCO Recommendation on the Ethics of AI; UN Global Principles for Information Integrity, and the UN Guiding Principles on Business and Human Rights; ASEAN Guide on AI Governance and Ethics; Hiroshima AI Process; Bletchley, Seoul, Paris, and Delhi AI Summit outcomes; AU Continental AI Strategy; EU AI Act and other pieces of national legislation or strategies; Council of Europe Framework Convention on Artificial Intelligence and Human Rights, Democracy and the Rule of Law, OECD AI Principles and OECD-integrated Global Partnership on AI (GPAI), Santiago/Montevideo Declarations on the Ethics of AI in Latin America and the Caribbean. (See OECD.AI Policy Navigator and the Center for AI and Digital Policy's "AI Policy Sourcebook" for overviews of AI policies and practices worldwide.) Technical standards: ITU's AI technical recommendations; ISO/IEC standards; relevant IEEE frameworks. Implementation and capacity building networks: Regional development bodies and capacity building initiatives; emerging national AI authorities, including AI safety institutes. Research and expert networks: Independent International Scientific Panel on AI, the International AI Safety Report, the Singapore Consensus on AI Safety Research Priorities, the International Association for Safe and Ethical AI (IASEAI), Partnership on AI (PAI), the Global South Network for Trustworthy AI. The UN Global Dialogue can offer a space in which to coordinate fragmented technical and regional initiatives, create transparency about alignment and gaps, enable political backing for implementation, and foster a forum for peer learning.

To ensure civil society, affected communities, researchers, technical experts, industry, and regional bodies have equitable, substantive and sustained opportunities for genuine influence, not merely consultative input, thematic discussions should be structured to allow them to present evidence (including through demonstrations of AI capabilities), raise concerns, identify gaps, and propose approaches that directly inform governmental conclusions. Critically, an annual two-day convening, while symbolically important, is insufficient for genuine international cooperation on AI governance. Without ongoing channels to carry work forward between annual meetings, the Dialogue risks becoming a one-off event where reflections are shared but implementation remains unclear. The Dialogue could be strengthened by complementing the annual gathering with continuous stakeholder coordination throughout the year to maintain momentum through: -Thematic multistakeholder working groups carrying governance work forward between annual Dialogues, with dedicated subgroups on specialized technical issues -Structured progress reporting on implementation of prior year recommendations -Rapid response capacity to address emerging issues and mitigate risks -A standing channel for independently held AI governance and policy conferences to submit their outputs to the Dialogue, ensuring the latest thinking and research informs its work This approach could help translate annual Dialogue reflections into concrete action and demonstrate accountability for follow-through.

The broader public is currently underrepresented, especially vulnerable and marginalized populations, individuals and communities directly affected by AI harms, and professionals within the AI industry with firsthand knowledge of system failures and safety concerns. Global South civil society organizations, researchers, and policy actors also face structural disadvantages in international AI governance forums, including resource constraints, time zone exclusion and limited access to documentation in working languages. This could be addressed through funded participation for under-resourced organizations; regional Dialogue hubs beyond New York and Geneva and translation of working documents in all six UN languages. Religious and faith communities, theologians and interfaith organizations are also largely absent. Their ethical traditions contribute substantively to debates on dignity, community, responsibility, and the ethics of new technologies, and their networks often reach communities formal civil society does not. Structured engagement building on existing UN channels for dialogue with faith-based actors would enable meaningful contribution. Rather than one-off consultations, formal, ongoing channels can enable these underrepresented actors to organize independently and feed their priorities into governance: virtual listening sessions across time zones with Dialogue Co-Chairs; open comment windows accepting submissions in multiple languages and formats (written, video, audio); and accessible multilingual summaries documenting how stakeholder feedback shaped outcomes. Certain institutional actors are also underrepresented: sector-specific regulatory authorities from diverse jurisdictions, bringing practical implementation experience; the judicial sector (judges, legal scholars, court systems), whose perspectives on adjudication, liability, and rights enforcement are critical as AI-related disputes increase; and independent technical researchers and safety experts from academia, civil society research institutions, who can provide assessments independent of commercial interest. Structured channels such as formal presentations, facilitated dialogue sessions, and technical working groups would enable these actors to contribute effectively, creating more robust and inclusive decision-making processes.

The Dialogue could organize a dedicated space featuring interactive demonstrations where AI safety experts showcase research on risks from advanced capabilities, while promising applications in poverty reduction, health, education or climate action are also shared. This dual approach, presenting both risks and opportunities through live, hands-on demonstrations enables participants to understand AI's trajectory comprehensively rather than through abstract discussion alone. Thematic roundtables bringing together policymakers, experts from civil society and industry, and affected stakeholders would ensure diverse perspectives inform discussions with dedicated segments centering the voices of those directly impacted. For example, human rights experts, AI developers and policymakers could examine cases where AI deployment has impacted human rights, including harms to children. A labor-focused roundtable could likewise bring together economists, displaced workers, trade unions and government officials, grounded in lived experience alongside economic analysis. Those experiencing AI harms firsthand hold knowledge that technical analysis alone cannot capture; their participation in solution design is foundational to building interventions that actually work. Structured tabletop exercises, e.g., walking through how jurisdictions would coordinate in response to an AI system producing unintended consequences across borders could surface gaps and generate practice-grounded recommendations. Similarly, sessions on risks from advanced AI systems, including those arising when deployment outpaces safeguards, could feed into further initiatives to identify, mitigate and manage these risks. Across all formats, it's important that the Dialogue treat expertise and lived experience from underrepresented regions and affected communities as cross-cutting sources of governance knowledge, integral to how risks, benefits, and harms are identified.

Government approaches reflect diverse policy priorities and institutional contexts: Brazil: rights-based approach through PL 2338/2023 (pending enactment); prohibits excessive-risk AI; establishes rights to explainability and human review. China: comprehensive regulatory approach through PIPL (2021), Algorithm Recommendation Provisions (2022), and Interim Measures on Generative AI (2023); mandates algorithmic transparency, content moderation and security assessment; actively advancing international governance through Global AI Governance Initiative. EU: legally binding risk-based governance through EU AI Act; prohibits "unacceptable risk" practices including manipulation causing harm, public-sector social scoring and certain biometric identification; mandates conformity assessments, post-market monitoring and human oversight. India: "techno-legal" approach combining baseline data protection safeguards, sectoral regulation and technical controls; emphasizes inclusion and digital public infrastructure through IndiaAI Mission rather than single overarching AI law. Singapore: innovation-enabling approach through Model AI Governance Framework (including 2024 Generative AI guidance) and open-source AI Verify testing framework; emphasizes voluntary adoption and interoperability. South Africa: human-centric, ethics-first approach through National AI Policy Framework (2024), emphasizing Ubuntu principles, inclusion and alignment with AU Continental AI Strategy . South Korea: innovation-led approach through AI Basic Act (2026) with risk-based obligations for "high-impact AI", active international coordination through AI Safety Institute and Seoul Summit. UAE: innovation-first positioning through the National AI Strategy 2031 and dedicated AI Minister (since 2017); substantial investment in domestic capacity and active international AI engagement. USA: innovation-first approach without federal omnibus AI legislation; combines voluntary NIST AI Risk Management Framework, targeted federal statutes (TAKE IT DOWN Act) and active state legislation (California SB 53, Texas Responsible AI Governance Act, New York RAISE Act, Virginia SB 384 / HB 797). Using key building blocks of AI governance as a comparative framework, the Dialogue can identify which are working in practice, where capacity gaps persist and which safeguards should become interoperable across jurisdictions: https://global-governance.ai/.