Lucid Pattern & IGF MAG Strategy Committee

A successful inaugural Global Dialogue on AI Governance would deliver outcomes that meaningfully advance coherence, equity, and trust in the global governance of artificial intelligence. First, success requires a shared, cross‑stakeholder articulation of global priorities, grounded in the mandate of Resolution 79/325. This includes a clear understanding of where the international community aligns on human‑rights‑centered governance, transparency, accountability, and robust human oversight, as well as where further work is needed. Second, the Dialogue should produce actionable pathways for capacity‑building, particularly for Member States facing constraints in high‑performance computing, data access, and workforce readiness. Leveraging existing UN and multistakeholder mechanisms—including the IGF—would demonstrate a commitment to reducing AI divides and ensuring that all countries can meaningfully participate in and benefit from AI ecosystems. Third, the Dialogue should establish interoperable governance reference points that help bridge the current fragmentation across national strategies, sectoral frameworks, and ethical guidelines. These reference points need not be prescriptive, but they should offer a coherent structure that supports compatibility, fosters trust, and enables cross‑border cooperation. Fourth, the Dialogue should ensure that the Independent International Scientific Panel's inaugural report directly informs policy discussions, rather than remaining adjacent to them. Integrating scientific evidence into governance deliberations is essential for legitimacy and long‑term impact. Fifth, success requires transparent, consistently applied procedures and rules of engagement that apply equally to all participants. Adherence to these modalities is foundational for fairness, credibility, and the multistakeholder trust that underpins global governance processes. Finally, the Dialogue should conclude with a mechanism for ongoing collaboration beyond July, including opportunities for co‑creation, shared evaluation frameworks, and partnerships that illustrate both the opportunities and challenges of AI governance. Together, these outcomes would position the Global Dialogue as a durable, inclusive, and future‑oriented platform capable of shaping AI for the benefit of all.

• Transparency, accountability, and human oversight
• Safe, secure and trustworthy AI
• Social, economic, ethical, cultural, linguistic and technical implications of AI
• Interoperability of governance approaches

From my perspective, several thematic areas identified in General Assembly Resolution 79/325 require urgent action and active engagement, both for their intrinsic importance and for their role in shaping coherent global governance. First, the development of safe, secure, and trustworthy AI systems is an immediate priority. Without baseline safety, security, and trustworthiness, no governance framework-technical, ethical, or institutional-can function effectively. This includes attention to robustness, misuse prevention, and the institutional conditions that support trustworthy deployment. Second, the social, economic, ethical, cultural, linguistic, and technical implications of AI demand sustained engagement. These dimensions determine how AI systems shape equity, well-being, legitimacy, and social cohesion. They also influence how different communities experience AI, and whether AI contributes to or undermines the Sustainable Development Goals. This area aligns closely with my work in industrial-organizational psychology and my upcoming SIOP presentation on AI and the SDGs. Third, the interoperability and compatibility of AI governance approaches is essential for reducing fragmentation across jurisdictions. Interoperability enables cooperation, reduces compliance burdens, and supports global alignment on shared principles while respecting national contexts. It is also a core strength of the Internet Governance Forum model, which has long demonstrated how multistakeholder processes can support coherence without imposing uniformity. Fourth, transparency, accountability, and robust human oversight are critical for institutional trust and public legitimacy. These mechanisms ensure that AI systems remain aligned with human values, organizational responsibilities, and international law. Across all of these areas, human rights remain non-negotiable. They are not a thematic option but the foundation upon which all other governance priorities must rest.

Yes. In addition to the themes outlined in Resolution 79/325, there are several cross-cutting and emerging issues that warrant explicit attention. First, the future of work must be treated as a core governance concern rather than a downstream economic effect. AI systems are reshaping job design, managerial control, worker autonomy, and the psychological contract at a structural level. These changes influence economic opportunity, labor market stability, and global development trajectories. Ensuring that AI contributes to decent work, fair conditions, and sustainable livelihoods is essential for achieving the SDGs and for maintaining social cohesion. Second, AI governance must address the evolving question of human identity and what it means to be human in an era of increasingly agentic systems. As AI systems mediate decision-making, communication, creativity, and care work, they influence dignity, agency, and the boundaries of human contribution. These impacts cut across safety, ethics, culture, and rights, and should inform how we define acceptable risk, appropriate oversight, and the limits of automation. Third, the interdependence of safety, governance, and economic opportunity is an emerging issue that requires integrated treatment. Decisions about safety thresholds, transparency requirements, and oversight mechanisms directly shape who benefits from AI, who bears the risks, and how equitably opportunities are distributed across countries and communities. Finally, while human rights are already embedded in the mandate, they should be recognized as non-negotiable and foundational, informing every thematic area rather than functioning as a standalone pillar. Together, these cross-cutting issues highlight the need for governance approaches that are not only technically sound, but also socially grounded and aligned with the realities of human work, identity, and dignity.

In the United States and across the broader ecosystem of organizational psychology, workforce development, and AI governance, the gaps and rapid advances in the thematic areas I identified—safe and trustworthy AI, socio‑technical impacts, interoperability, and transparency and oversight—are already producing significant structural effects. First, the absence of consistent standards for safe, secure, and trustworthy AI is creating uneven adoption across sectors. Organizations with advanced technical capacity are moving quickly, while others lack the safeguards, evaluation tools, or institutional clarity needed to deploy AI responsibly. This unevenness increases operational risk and widens competitive and developmental gaps. Second, the social, economic, ethical, cultural, linguistic, and technical implications of AI are reshaping the U.S. labor market and the psychological experience of work. AI‑mediated decision‑making affects hiring, performance evaluation, and job design, raising concerns about fairness, autonomy, and worker well‑being. These impacts are especially visible in sectors experimenting with algorithmic management or generative‑AI‑driven productivity tools. The governance gaps here directly influence institutional trust and the legitimacy of organizational practices. Third, the lack of interoperability across governance approaches creates compliance uncertainty for organizations operating across jurisdictions. Divergent regulatory models—state‑level, national, and international—make it difficult to implement coherent governance frameworks, increasing administrative burden and slowing innovation. Fourth, gaps in transparency, accountability, and human oversight are affecting both public trust and organizational readiness. Many institutions lack clear mechanisms for documenting model behavior, monitoring downstream impacts, or ensuring meaningful human control. This is particularly consequential in high‑stakes contexts such as employment, healthcare, and public services. Finally, an emerging cross‑cutting challenge is the impact of AI on the future of work and human identity. As AI systems increasingly mediate creativity, judgment, and interpersonal interaction, they raise foundational questions about dignity, agency, and what constitutes meaningful human contribution. These issues are not fully captured in existing governance themes but are already shaping workforce expectations, economic opportunity, and societal cohesion. Together, these gaps underscore the need for coherent, human‑centered, interoperable governance frameworks that can support innovation while safeguarding rights, equity, and institutional trust.

What role can the AI Dialogue play in advancing international cooperation on AI governance? The Global Dialogue can play a pivotal role in advancing international cooperation by creating a coherent, inclusive, and interoperable governance space—one that brings together the fragmented efforts currently unfolding across regions, sectors, and institutions. To do this effectively, the Dialogue must not operate in isolation, but rather build upon and fully integrate the multistakeholder mechanisms that already exist and have proven their legitimacy. A central part of this is ensuring that the Internet Governance Forum (IGF) is recognized as a full partner—if not the primary mechanism—for sustained global cooperation on AI governance. The IGF has nearly two decades of experience convening governments, civil society, academia, the private sector, and the technical community as peers. Its processes are transparent, inclusive, and grounded in procedural fairness—exactly the qualities required for legitimate AI governance. Leveraging the IGF's infrastructure, expertise, and culture of co‑creation would allow the Dialogue to move beyond one‑off consultations and toward a durable, globally trusted governance ecosystem. Substantively, the Dialogue can advance cooperation by establishing shared reference points in the areas where gaps are most consequential: - Safe, secure, and trustworthy AI, - The social, economic, ethical, cultural, linguistic, and technical implications of AI, - Interoperability of governance approaches, and - Transparency, accountability, and meaningful human oversight. These themes cut across borders and sectors, and no single country can address them alone. The Dialogue can help align expectations, reduce regulatory fragmentation, and support capacity‑building—especially for countries facing constraints in high‑performance computing, data access, and workforce readiness. Finally, the Dialogue can strengthen cooperation by ensuring that procedures and rules of engagement are applied consistently to all participants, reinforcing trust in the process itself. When combined with the IGF's established multistakeholder DNA, this creates a governance environment capable of supporting innovation while safeguarding human rights, dignity, and the future of work.

The AI Dialogue should build upon and formally integrate several existing initiatives and mechanisms, with the Internet Governance Forum (IGF) playing a significantly expanded and central role. First, the IGF should be recognized not only as a relevant partner, but as the primary multistakeholder mechanism capable of supporting the long‑term, iterative, and globally distributed work that AI governance requires. For nearly two decades, the IGF has demonstrated how governments, civil society, academia, the private sector, and the technical community can engage as peers in transparent, inclusive, and procedurally consistent processes. Its proven modalities, institutional memory, and global network of national and regional IGFs make it uniquely positioned to anchor the AI Dialogue's ongoing work. The Dialogue can add value by elevating IGF outputs, aligning its thematic clusters with IGF best practices, and ensuring that AI governance benefits from the IGF's legitimacy, reach, and multistakeholder DNA. Second, the Dialogue should connect with existing UN capacity‑building mechanisms, including those that provide grants, technical assistance, and consultancy opportunities. These pathways allow the private sector, research institutions, and independent experts to contribute concrete work products—such as safety benchmarks, socio‑technical impact assessments, and open‑source tools—that can be adopted or adapted by Member States. Leveraging these mechanisms would help close capacity gaps, particularly for countries with limited access to high‑performance computing, data resources, or specialized expertise. Third, the Dialogue should build upon initiatives such as the AI for Good Global Summit, UNESCO's Recommendation on the Ethics of AI, and the work of the Independent International Scientific Panel on AI. These efforts provide scientific grounding, ethical frameworks, and practical case studies that can inform governance design. The added value of the AI Dialogue lies in its ability to synthesize these efforts into a coherent global architecture, reduce fragmentation, and create interoperable governance reference points. By anchoring itself in the IGF as the central multistakeholder platform, the Dialogue can ensure that global cooperation on AI governance is inclusive, evidence‑based, and operationally sustainable.

Different stakeholders can contribute to the AI Dialogue in ways that reflect their comparative strengths, provided the process is grounded in transparent, consistently applied procedures and a genuinely multistakeholder architecture. To achieve this, the Dialogue should be anchored in mechanisms that already embody these principles—most notably the Internet Governance Forum (IGF). Governments can contribute by articulating national priorities, identifying capacity gaps, and committing to interoperable governance approaches. Their role is essential for aligning AI governance with international law, human rights, and public accountability. Civil society and academia bring expertise on the social, economic, ethical, cultural, linguistic, and psychological implications of AI—including impacts on the future of work, human identity, and institutional legitimacy. Their contributions ensure that governance frameworks remain grounded in lived experience and empirical evidence. The private sector can contribute through technical expertise, safety evaluations, and the development of open‑source tools and shared scientific infrastructure. To enable this, the Dialogue should leverage UN grants, technical assistance programs, and consultancy pathways that allow companies, research labs, and independent experts to produce concrete work products that support Member States. The technical community plays a critical role in defining safety benchmarks, transparency mechanisms, and human‑oversight architectures that align with real‑world system behavior. Recommendations for Format and Structure The AI Dialogue should adopt the IGF's proven multistakeholder DNA as its structural foundation. This includes dynamic formats, co‑creation spaces, and structured exchanges where all stakeholder groups participate as peers. The IGF's global network of national and regional IGFs should be leveraged to ensure geographic diversity, capacity‑building, and continuity beyond the July meeting. To maintain legitimacy, the Dialogue must apply procedures and rules of engagement consistently to all participants, ensuring fairness, transparency, and trust in the process. Finally, the Dialogue should be structured to synthesize inputs into interoperable governance reference points, practical cooperation models, and ongoing mechanisms for collaboration—anchored in the IGF as the central platform for sustained global engagement on AI governance.

Several voices, communities, and expert groups remain underrepresented in global discussions on AI governance, and their absence limits the legitimacy, equity, and practical effectiveness of emerging governance frameworks. First, women and gender‑diverse communities continue to be underrepresented across technical, policy, and governance spaces. Their inclusion is essential not only for equity, but for shaping AI systems that reflect the full spectrum of human experience, identity, and labor realities. Second, underrepresented populations within the Global North—including racial and ethnic minorities, low‑income communities, and workers in sectors most affected by automation—are often excluded from formal governance dialogues despite being disproportionately impacted by AI‑mediated decision‑making. Their perspectives are critical for understanding the social, economic, and psychological implications of AI, particularly in relation to the future of work and human dignity. Third, many countries and communities in the Global South lack structured pathways to participate meaningfully in global governance processes. This is especially consequential given the capacity gaps in high‑performance computing, data access, and workforce readiness. Fourth, domain experts—particularly those embedded in labor, finance, education, health, and cultural sectors—are often consulted too late or too narrowly. They should be engaged through the relevant parts of the UN system. For example: - The ILO should partner directly with labor unions, worker associations, and employer groups to shape AI‑related labor and workforce policy. - UNCTAD should work with financial‑sector associations and economic development bodies to understand AI's impact on trade, markets, and global economic opportunity. - UNESCO should engage educators, cultural institutions, scientific bodies, and linguistic communities to ensure AI governance reflects diverse knowledge systems and cultural contexts. To broaden participation, the AI Dialogue should support multiple grants and consultancy pathways that enable contributions from smaller consulting firms, independent experts, and NGOs—not only large, established actors. These opportunities should value knowledge, research contributions, community engagement, NGO involvement, and sector‑specific work history, rather than relying solely on years of consulting experience. This would diversify who can produce work products, frameworks, and tools for Member States. Finally, the Dialogue should leverage the Internet Governance Forum (IGF) and its global network of national and regional IGFs, which already provide inclusive, transparent, and procedurally consistent mechanisms for multistakeholder participation. Ensuring that rules of engagement apply equally to all participants will strengthen legitimacy and ensure that AI governance reflects the diversity of global experience.

To foster meaningful, dynamic, and globally representative engagement, the AI Dialogue should adopt a diverse set of participation formats that meet people where they are, while maintaining the procedural fairness and transparency required for legitimate global governance. First, the Dialogue should be anchored in the Internet Governance Forum (IGF) and its global network of national and regional IGFs. The IGF already provides proven, inclusive, and procedurally consistent mechanisms—open sessions, dynamic coalitions, best‑practice forums, and multistakeholder roundtables—that can be adapted to AI governance. Leveraging this infrastructure ensures continuity, legitimacy, and global reach. Second, the Dialogue should incorporate large‑scale surveys to gather broad input from individuals, organizations, and communities across regions. Surveys can surface priorities, concerns, and lived experiences that may not emerge in formal meetings. Third, survey participants should be invited into focus groups to deepen insights, validate findings, and ensure that underrepresented voices—including women, marginalized populations in the Global North, and communities across the Global South—are meaningfully included. Fourth, the Dialogue should provide structured written‑response opportunities, modeled on the U.S. Federal Register Notice (FRN) process. This format allows stakeholders to submit evidence, analysis, and recommendations in a transparent, publicly accessible manner. It also creates a durable record that can inform the Co‑Chairs' summary and future governance work. Fifth, the Dialogue should use social media and digital communication channels to keep stakeholders informed, share interim findings, and invite ongoing participation. This is essential for transparency and for reaching communities that may not engage through traditional UN processes. Together, these formats—anchored in the IGF and expanded through surveys, focus groups, written submissions, and digital outreach—would create a governance environment that is inclusive, evidence‑based, and responsive to the diversity of global experience.

Around the world, several governance models offer practical, operationally useful approaches to addressing AI's challenges while supporting innovation, safety, and public trust. These examples demonstrate how rights-based frameworks, risk-based regulation, and multistakeholder engagement can work together to create coherent and inclusive governance ecosystems. European Union The EU has developed a comprehensive, risk-based approach that integrates safety, transparency, and human oversight. Key strengths include: - Clear risk tiers that differentiate between minimal-risk, limited-risk, and high-risk AI systems. - Mandatory transparency and documentation for high-risk systems, including requirements for human oversight and technical robustness. - Regulatory sandboxes that allow companies-especially SMEs-to test AI systems under supervision while maintaining innovation pathways. - Strong alignment with fundamental rights, ensuring that AI deployment is consistent with democratic values and social protections. South Korea South Korea's governance model blends ethics, industrial strategy, and public trust. Notable practices include: - National AI Ethics Guidelines that emphasize human-centric design, safety, and accountability. - Sector-specific guidance for education, healthcare, and public services, ensuring that AI deployment aligns with cultural and linguistic contexts. - Investment in workforce development, preparing workers for AI-augmented roles and addressing the psychological and social dimensions of the future of work. Brazil Brazil offers a rights-based, participatory model that integrates digital governance with democratic accountability. Key elements include: - A governance approach grounded in fairness, transparency, and protections for vulnerable populations, reflecting Brazil's broader digital-rights tradition. - A strong data-protection authority that provides oversight, guidance, and enforcement capacity. - Participatory policymaking, drawing on civil society, academia, and community organizations to shape AI norms and ensure that governance reflects diverse lived experiences.