Association for Responsible AI

A successful first Global Dialogue on AI Governance should lead to clear, practical outcomes—not just discussions. First, it should create a shared understanding of key principles like safety, fairness, and accountability. Even partial alignment would be a strong step forward. Second, it should include real commitments, especially to support developing countries through capacity-building and access to AI resources. Third, success means everyone has a voice—including civil society, youth, and underrepresented communities—not just governments and big tech. Finally, the Dialogue should result in next steps, such as partnerships or follow-up actions, to keep the momentum going.

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

Our priorities focus on ensuring that AI development is inclusive, responsible, and aligned with the needs of underserved communities, particularly in developing contexts such as Haiti. First, safe, secure, and trustworthy AI is essential to build public confidence and prevent harm, especially where digital literacy and regulatory frameworks are still evolving. Second, AI capacity-building is critical. Many communities lack the skills and infrastructure to participate in or benefit from AI systems. Investing in training, education, and local expertise will help bridge the digital divide and empower local innovation. Third, we prioritize the social, economic, ethical, cultural, linguistic, and technical implications of AI. AI systems must reflect local realities, languages, and cultural contexts to avoid reinforcing inequalities or excluding marginalized populations. Finally, transparency, accountability, and human oversight are necessary to ensure that AI systems remain fair and aligned with human values. Clear governance mechanisms and inclusive participation in decision-making processes are key to responsible AI deployment.

One major challenge is the lack of clear rules and local capacity, which increases risks like misinformation, data misuse, and exclusion. Many communities also face low digital literacy, making it harder to benefit from AI. In addition, most AI tools don't support local languages or contexts. At the same time, there are strong opportunities. AI can improve education, services, and create new economic opportunities if used well. It also gives a chance to build more inclusive and locally relevant governance models from the start.

The AI Dialogue can play a key role by creating a neutral space for collaboration among governments, private sector, civil society, and academia. It can help build shared understanding and trust, which is essential for coordinating global approaches to AI governance. By bringing diverse voices together—especially from underrepresented regions—it can ensure that global frameworks are more inclusive and balanced. The Dialogue can also support knowledge sharing and capacity-building, helping countries learn from each other's experiences and strengthen their own policies and systems. Finally, it can drive practical cooperation, such as partnerships, joint initiatives, and follow-up actions that move beyond discussion.

he AI Dialogue should build on existing global and regional efforts such as the UN AI Advisory Body, UNESCO's AI Ethics framework, the OECD AI Principles, and multi-stakeholder initiatives like the Global Partnership on AI (GPAI). It can also connect with regional forums and digital cooperation initiatives that are already supporting capacity-building and policy development. The added value of the AI Dialogue lies in its ability to bring these efforts together in one inclusive space, especially by amplifying voices from developing countries that are often underrepresented. It can help bridge gaps between global principles and local implementation, ensuring that policies are not only agreed upon but also adapted to different contexts.

Governments can share policy experiences and support the development of inclusive frameworks. The private sector can provide technical knowledge, innovation insights, and best practices. Civil society can highlight human rights, ethics, and community impacts, while academia can contribute research and evidence-based recommendations. It is especially important to include voices from youth, local communities, and underrepresented regions. For the format, the AI Dialogue should be interactive and inclusive, not only high-level discussions. It could combine: Plenary sessions for global priorities and shared principles Small working groups focused on specific themes and practical solutions Regional consultations to reflect local realities Open forums to allow broader participation The structure should also include clear outputs, such as recommendations or action points, and a follow-up mechanism to track progress.

These include communities from developing countries, especially in regions like the Caribbean and Africa, as well as local grassroots organizations, youth, women, and speakers of low-resource languages. In addition, small businesses and informal sector workers—who are often directly affected by technological change—are rarely included. Their absence risks creating policies that do not reflect real-world needs and realities. To include these groups, the AI Dialogue should prioritize accessible and inclusive participation. This can be done by: Supporting funding and sponsorships to enable participation from low-income regions Offering multilingual engagement, including interpretation and support for local languages Organizing regional and community-level consultations before global discussions Using hybrid formats (online and in-person) to reduce barriers to access Partnering with local organizations and networks to bring grassroots perspectives into the process It is also important to create safe and meaningful spaces for participation, where these voices are not only present but actively influence outcomes.

To foster meaningful and dynamic engagement during the AI Dialogue, innovative formats should go beyond traditional panels and lectures. 1. Interactive workshops and hackathons: These allow participants to work on real-world AI challenges in small groups, generating practical solutions and encouraging collaboration across sectors. 2. Regional and thematic breakout sessions: Breaking into smaller, focused groups on specific topics—like ethics, capacity-building, or AI for education—ensures deeper discussion and inclusive participation, especially from underrepresented regions. 3. Hybrid participation models: Combining in-person and virtual attendance allows wider access, particularly for stakeholders from developing countries or remote areas. Real-time translation and accessibility tools can further broaden participation. 4. Storytelling and case-study sessions: Allowing communities, youth, or local organizations to share experiences with AI ensures discussions are grounded in real-world impacts, not just theory. 5. Interactive digital platforms: Online tools like polls, Q&A sessions, collaborative documents, and discussion forums can maintain engagement between sessions and provide a space for continuous dialogue. 6. Multi-stakeholder panels with audience participation: Panels including government, private sector, civil society, and academia, combined with live audience input, ensure diverse perspectives are heard and debated. 7. Follow-up "action labs": Short sessions where participants translate discussion outcomes into concrete recommendations or pilot projects can help bridge dialogue and action.

Several policies, practices, and platforms offer effective approaches to AI governance. 1. Ethical frameworks and principles: Initiatives like UNESCO's AI Ethics Recommendations and the OECD AI Principles provide globally recognized guidance on transparency, accountability, fairness, and human rights, helping countries develop responsible AI policies. 2. Multi-stakeholder partnerships: Platforms such as the Global Partnership on AI (GPAI) bring together governments, industry, civil society, and academia to collaborate on AI research, standards, and capacity-building, creating shared solutions to complex challenges. 3. Regulatory sandboxes: Some countries are using AI regulatory sandboxes, which allow companies and governments to test AI systems in controlled environments while ensuring compliance with ethical and legal standards. This encourages innovation without compromising safety. 4. Capacity-building programs: Programs that focus on skills development, digital literacy, and AI education empower communities to use AI responsibly and benefit from its economic and social potential. 5. Transparent reporting and accountability mechanisms: Requiring AI systems to include explainability, auditing, and documentation ensures accountability and builds trust among users and regulators. 6. Inclusive design approaches: Policies that encourage community engagement, language inclusivity, and culturally adapted AI solutions help ensure technologies are accessible and relevant to all populations, reducing bias and exclusion.