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A successful Global Dialogue could be based on five outcomes: 1. Capacity building to develop local AI skills and usability. 2. Reliable AI adoption for public services, ensuring transparency and security. 3. Improved service quality through accountable AI integration. 4. A clear framework for deploying AI in the education sector. 5. Follow-through mechanisms with measurable benchmarks and continued support. These outcomes would transform AI from a source of exclusion into a tool for equitable development, stability, and institutional rebuilding.

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

My selection reflects the potential successful of Global Dialogue, for example, grounded in Libya's perspective as a country navigating fragility and aspiring for equitable development. AI capacity-building is the foundation. Without investing in local skills, infrastructure, and usability, countries like Libya cannot meaningfully participate in AI governance or deployment. Capacity-building ensures we move from being passive recipients to active shapers of AI's role in our society. Safe, secure and trustworthy AI is essential because AI adoption for public services-such as healthcare, administration, and infrastructure-must be reliable. In fragile contexts, untrustworthy systems risk undermining public confidence and exacerbating instability rather than supporting rebuilding efforts. Transparency, accountability, and human oversight directly supports the goal of improved service quality. Public services powered by AI must remain subject to human judgment and clear accountability mechanisms. This is particularly critical in sectors like education and governance, where decisions affect vulnerable populations. Social, economic, ethical, cultural, linguistic and technical implications of AI addresses the broader societal dimensions. Deploying AI in education, for example, requires a framework sensitive to local culture, language, and ethical considerations. This priority ensures that AI integration does not widen inequalities but instead supports inclusive, context-appropriate development. Together, these four priorities form a coherent package: building capacity, ensuring safety and trust, maintaining accountability, and addressing the full range of societal implications. They reflect a practical, people-centered approach to AI governance that prioritizes stability, equity, and institutional rebuilding-outcomes that would make the Global Dialogue truly meaningful for Libya and nations in similar contexts.

In my opinion, two cross-cutting issues are not fully captured by the listed themes: 1. Digital sovereignty and equitable infrastructure. While "AI capacity-building" touches on skills, it does not explicitly address the structural inequities in access to computational resources, data, and foundational AI models. For example ، for countries like Libya, success depends on ensuring that AI governance includes mechanisms for affordable, equitable access to the infrastructure that underpins AI development-preventing a new form of technological dependency. 2. AI governance in fragile and conflict-affected contexts. The listed themes focus largely on stable settings. However, in fragile states, ungoverned spaces can enable AI misuse such as autonomous systems, disinformation campaigns, or algorithmic bias that deepens social divisions. A cross-cutting principle is needed that addresses how governance frameworks apply in contexts where institutions are weak, and how AI can be leveraged for stabilization and rebuilding rather than exploitation. These issues intersect all thematic areas and should be embedded as cross-cutting considerations throughout the Dialogue's outcomes.

To be practical, countries like in Libya, governance gaps across the four selected thematic areas present significant challenges but also opportunities for meaningful progress. AI capacity-building . The most immediate challenge is the absence of structured AI education, technical training, and digital infrastructure. This leaves Libya dependent on external expertise and unable to shape AI applications to local needs. However, the opportunity lies in building a new generation of skilled professionals who can drive digital transformation as part of national rebuilding efforts. Safe, secure and trustworthy AI. With weak institutional oversight, there is a real risk that AI tools, such as autonomous systems or disinformation algorithms , could be deployed without safeguards, potentially exacerbating instability. The opportunity is to establish early frameworks that prioritize safety and trust, positioning Libya to adopt AI responsibly rather than reactively. Transparency, accountability, and human oversight. Currently, there are no clear mechanisms for ensuring AI systems used in public services are auditable or subject to human review. This gap risks eroding public trust in institutions already facing legitimacy challenges. The opportunity is to embed accountability principles from the outset, building AI governance that strengthens institutional credibility. Social, economic, ethical, cultural, linguistic and technical implications. AI tools developed elsewhere often fail to account for Libya's cultural and linguistic diversity, risking exclusion or bias. The opportunity lies in developing context-sensitive frameworks—particularly in education and public services, that ensure AI serves all communities equitably. Addressing these gaps through the Global Dialogue would transform AI from a potential source of risk into a tool for stability, inclusion, and long-term development.

The AI Dialogue can advance international cooperation by serving as a platform that bridges structural divides and translates principles into practice. First, it can operationalize capacity-building as a shared responsibility. Cooperation must move beyond declarations to deliver concrete commitments, such as shared computational resources, open training datasets, and technical exchange programs, that enable countries like Libya to participate meaningfully in AI governance rather than remain passive recipients. Second, it can establish mechanisms for inclusive standard-setting. International cooperation often reflects the priorities of advanced economies. The Dialogue can ensure that governance frameworks, particularly around safety, transparency, and accountability, are co-created with input from fragile and developing contexts, reflecting diverse social, cultural, and linguistic realities. Third, it can create rapid-response frameworks for AI-related risks in vulnerable regions. Cross-border threats such as disinformation, algorithmic bias, or misuse of autonomous systems require coordinated responses. The Dialogue can establish protocols for information sharing, technical assistance, and early warning systems tailored to contexts with limited institutional capacity. Finally, it can embed accountability into cooperation structures. Success requires follow-through mechanisms, measurable benchmarks, peer reviews, and sustained funding, that ensure international cooperation does not fade after the Dialogue concludes. This would transform AI governance from a forum of discussion into a durable partnership for equitable development.

Existing initiatives to build upon: · Global Digital Compact. The first universal UN agreement on AI governance, establishing foundational principles for the Dialogue and the Independent International Scientific Panel on AI. · UNESCO Recommendation on the Ethics of AI. Adopted by 193 countries, providing practical tools like AI Readiness Assessments, Ethical Impact Assessments, and the AI Experts Without Borders network. · Global Partnership on AI (GPAI) / OECD. Offers established working groups, expert communities, and frameworks such as the SAFE Project on generative AI safety. · AI for Good Global Summit (ITU) . Focuses on applying AI to global challenges since 2017. · UNDP country-level work. In Libya and elsewhere, supporting digital transformation and AI adoption for public services. Added value the AI Dialogue can bring: · Universal participation. The UN ensures every country, including the Global South, has a seat at the table. · Policy-science-capacity integration. Connects policy discussions with the Independent Scientific Panel and potential Global Fund for AI Capacity Development. · Interoperability coordination. Aligns diverse governance approaches across initiatives to prevent fragmentation and create coherent global standards.

How stakeholders can contribute: · Member States – Shape norms, commit to implementation, and ensure inclusive delegations. · Civil society and academia – Provide expertise, ethical guidance, and grassroots perspectives. · Private sector – Share technical expertise, best practices, and contribute to capacity-building. · UN entities – Coordinate across sectors and leverage existing frameworks. · Local communities and youth – Bring lived experience and ensure governance addresses real needs. Recommendations for format and structure: · Regional preparatory meetings – Ensure diverse voices shape the agenda before the main Dialogue. · Hybrid participation – Enable remote access for those facing mobility or infrastructure constraints. · Multi-stakeholder roundtables – Mix government, civil society, academia, and private sector in discussions. · Dedicated spaces for fragile contexts – Address unique challenges for conflict-affected countries. · Continuous engagement mechanisms – Establish working groups that operate between sessions. · Language and accessibility – Provide interpretation and materials for non-English speakers.

Underrepresented voices and communities: · Fragile and conflict-affected states – Countries like Libya are often absent from AI governance discussions due to institutional instability, yet they face unique risks such as AI-enabled disinformation or autonomous systems in ungoverned spaces. · Global South and developing nations – Perspectives from Africa, Latin America, and parts of Asia are frequently marginalized, resulting in governance frameworks that do not reflect diverse socio-economic realities. · Indigenous communities – Indigenous knowledge systems, languages, and cultural contexts are rarely considered in AI development and governance. · Women and youth – Despite being disproportionately affected by AI-related risks, their voices remain peripheral in high-level policy forums. · Local civil society and grassroots organizations – These groups understand on-the-ground impacts but lack resources to participate in international processes. · Linguistic minorities – Discussions are often dominated by English speakers, excluding non-English perspectives. How to include them: · Targeted outreach and funding – Provide financial support for travel, translation, and participation to enable representatives from underrepresented communities to attend. · Regional and national consultations – Hold inclusive preparatory meetings at local levels to gather input before global gatherings, ensuring diverse voices shape the agenda. · Language accessibility – Offer interpretation, translated materials, and multilingual platforms throughout the Dialogue. · Dedicated representation mechanisms – Reserve speaking slots, advisory roles, and working group seats for civil society, youth, Indigenous representatives, and fragile-state participants. · Sustained engagement structures – Create ongoing advisory bodies with diverse membership rather than one-time consultations, ensuring continuous inclusion beyond the Dialogue itself.

1. Interactive scenario-based workshops Rather than traditional panels, convene small-group sessions where stakeholders collaboratively respond to realistic AI governance scenarios—such as deploying AI in a fragile state or responding to a cross-border AI incident. This format surfaces practical challenges and builds shared understanding across diverse perspectives. 2. Digital participatory platforms Create an accessible online space where participants can contribute ideas, vote on priorities, and co-draft recommendations before and during the Dialogue. This allows voices from remote or resource-constrained settings to engage meaningfully without requiring full-time presence. 3. Reverse mentorship pairings Pair senior policymakers with youth, civil society, or grassroots representatives in structured mentorship exchanges. This flips traditional hierarchies, ensuring decision-makers hear directly from those most affected by AI governance outcomes. 4. AI-powered real-time synthesis Use AI tools to aggregate input from multiple sessions, languages, and formats—providing live visualizations of emerging themes, areas of convergence, and divergence. This helps participants see how their contributions connect to the broader dialogue. 5. Regional parallel sessions with global feed Hold synchronized regional hubs that feed insights into a central plenary. Each hub can address context-specific challenges—such as AI in fragile contexts—while contributing to a shared outcome document. 6. Solutions-focused innovation labs Dedicate time to collaborative problem-solving labs where multi-stakeholder teams develop concrete proposals on specific challenges (e.g., AI capacity-building fund mechanisms or accountability frameworks for public services), with commitments to pilot or implement outcomes. 7. Storytelling and lived experience sessions Create dedicated spaces for individuals from underrepresented communities to share personal experiences of AI's impact—grounding abstract policy discussions in human realities.

As my experiences as a consultant for UNESCWA. In libya to strategy. I reviews Several practical approaches offer concrete solutions for effective AI governance. For examples: Readiness and assessment tools. UNESCO's Readiness Assessment Methodology helps countries evaluate their AI ecosystem across legal, social, economic, and technological dimensions, identifying institutional gaps and providing tailored recommendations. The Ethical Impact Assessment evaluates specific AI systems at the micro-level. Risk management frameworks. The OECD's Due Diligence Guidance for Responsible AI provides a practical framework for enterprises: embedding responsible conduct, identifying adverse impacts, preventing harms, tracking implementation, and enabling remediation. Safety and risk platforms . The Global Risk and AI Safety Preparedness platform maps over 80 risk types-including malicious use and societal harms-linking them to mitigation strategies through an interactive database. Global South collaboration. The Smart Africa-Wadhwani AI partnership develops inclusive, context-led AI solutions for health, agriculture, education, and public services, while establishing AI Digital Public Goods platforms for sharing proven solutions. Country-level practice . In Libya, UNDP supports digital transformation and AI adoption for public services, advancing AI readiness, capacity building, and financial inclusion. Similar approaches in Togo used AI to target financial aid during the pandemic via satellite imagery and telecom metadata. These examples demonstrate that effective AI governance combines diagnostic tools, practical frameworks, accessible risk resources, and context-sensitive implementation.