WomenInTech

The first Global Dialogue on AI Governance would be successful if it produces outcomes that balance innovation, competition, and ethical responsibility. Using Porter's Five Forces, the dialogue should address: Competitive Rivalry: Promote collaboration over a race-to-the-bottom among AI developers and nations. Threat of New Entrants: Support responsible innovation while setting clear standards to prevent unsafe or biased AI. Bargaining Power of Suppliers: Ensure fair access to high-quality, unbiased datasets and AI talent, especially in underrepresented regions. Bargaining Power of Buyers: Enable transparency and explainability so governments, institutions, and citizens can make informed decisions. Threat of Substitutes: Encourage alternative technologies and safeguards to reduce systemic risks from overreliance on a few AI systems. Aligned with Microsoft's AI governance principles including fairness, reliability and safety, privacy and security, inclusiveness, transparency, and accountability, the dialogue should produce: Frameworks for bias-free data and inclusive participation Guidelines for transparent and accountable AI deployment Cross-border collaboration channels and measurable indicators of ethical AI adoption Success will be measured by actionable policies and practical tools that ensure AI drives innovation and economic growth while safeguarding fairness, inclusion, and societal trust globally.

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

I believe the first Global Dialogue on AI Governance must focus on safe, secure, and trustworthy AI. Building AI capacity is critical so emerging markets and young scholars can participate meaningfully in shaping AI's future. Addressing the social, economic, ethical, cultural, linguistic, and technical implications ensures AI systems reflect the realities of diverse communities. Transparency, accountability, and human oversight are essential safeguards to prevent harm, build trust, and guide responsible deployment. These elements are not optional, they are the foundation of governance resolutions that make AI adoption equitable, inclusive, and beneficial for all.

Ethical data practices and bias-free datasets, highlighting fairness and representative data as central to AI governance. AI education and literacy for youth and scholars. This will support proactive engagement and societal preparedness. Public-private collaboration in AI governance . Including thematic areas that combine ethics, inclusion, capacity-building, and practical governance frameworks, which go beyond just "technical interoperability" or open-source access.

In Nigeria, gaps in safe, secure, and trustworthy AI risk amplifying inequalities, especially in banking, healthcare, and public services, where bias and lack of oversight remain challenges. Limited AI capacity-building in schools and universities constrains young scholars from engaging meaningfully with AI, while many systems fail to reflect Nigeria's cultural, linguistic, and socio-economic context. The absence of transparency, accountability, and human oversight further increases risks of misuse and erodes public trust. These challenges also present opportunities: by investing in inclusive governance frameworks, AI literacy, and context-aware ethical systems, Nigeria can foster innovation, build trust, and ensure AI benefits all citizens. Proactive engagement in these areas is critical to shaping a responsible AI ecosystem for the nation's growing digital economy.

AI dialogue can play a vital role in advancing international cooperation on AI governance by creating spaces for open conversation, trust, and shared understanding. Prof. Pat Utomi often stresses that dialogue is key to nation-building, helping people exchange ideas, build consensus, and strengthen institutions. The same principle applies globally: countries and organizations need to talk openly about AI risks, ethical standards, and responsible use to avoid fragmented or unilateral approaches. Through dialogue, stakeholders can share experiences, identify common challenges, and co-create governance frameworks that balance innovation with accountability. This is especially important for emerging markets, where resources and regulatory capacity may differ, yet the need for fair, transparent AI systems is urgent. By enabling honest, inclusive discussions, AI dialogue also builds trust, reduces misunderstandings, and encourages collaborative solutions, ensuring AI governance is not just technically sound, but socially responsible and globally aligned. In short, just as dialogue strengthens nations, it can strengthen the global AI ecosystem, helping us cooperate, learn from each other, and create AI that benefits everyone responsibly.

The AI Dialogue should build upon existing initiatives such as UNESCO's AI Ethics Guidelines, the African Union's Digital Transformation Strategy, World Bank AI for Development programs, and platforms like Microsoft's AI for Good and Women in Tech initiatives, which focus on inclusion, ethical AI, and capacity-building. In Nigeria, partnerships between government, academia, and industry, such as the National Information Technology Development Agency (NITDA) AI policy framework, provide an important foundation for standards, policy guidance, and local adoption. The Dialogue could add value by creating a truly global, multi-stakeholder platform that connects these efforts, amplifies underrepresented voices from emerging markets, and promotes context-aware governance frameworks. It can facilitate knowledge exchange, identify gaps in ethical and technical standards, and support practical implementation tools for AI governance. By bridging policy, technical expertise, and societal perspectives, the AI Dialogue can accelerate responsible AI adoption while ensuring that systems are inclusive, transparent, and accountable, particularly in regions where local context and capacity remain underrepresented in global conversations.

Different stakeholders, governments, private sector, academia, civil society, and local communities can contribute to the AI Dialogue by bringing diverse perspectives, expertise, and lived experiences.The Dialogue should prioritize inclusive, respectful, and structured engagement, where each participant can voice insights, challenge assumptions, and co-create solutions. The private sector can provide technical expertise and data insights, governments can offer regulatory guidance and policy frameworks, academia can contribute research and ethical frameworks, and civil society can represent social and cultural perspectives. Active listening, interest-based dialogue, and collaborative problem-solving, should guide discussions to ensure trade-offs are understood and consensus is reached on key governance issues. In terms of format and structure, the AI Dialogue could include: Thematic breakout sessions on ethics, bias, transparency, and inclusion. Case study discussions for practical, real-world application. Structured negotiation sessions to explore competing interests and policy options. Open plenary forums to synthesize insights and share recommendations. This approach ensures that the Dialogue is inclusive, actionable, and capable of producing practical, context-aware frameworks for AI governance that are relevant to both emerging markets and global stakeholders.

Currently, voices from emerging markets, women, youth, and marginalized communities are significantly underrepresented in global AI governance discussions. In Africa, for example, many AI policies and systems are designed without sufficient input from local experts, scholars, or communities, resulting in technologies that often fail to reflect local languages, cultures, and socio-economic realities. In line with my advocacy for inclusive, context-aware AI, these perspectives can be amplified by: Proactively including local researchers, educators, and civil society in policy dialogues. Integrating youth and scholars through AI literacy and capacity-building programs to ensure the next generation shapes governance frameworks. Engaging women in technology and leadership roles, reflecting research from thought leaders like Timnit Gebru and Kate Crawford, who emphasize that diversity in AI design and policy reduces bias and strengthens ethical outcomes. Establishing multi-stakeholder advisory boards and consultation mechanisms that actively seek input from underrepresented regions and communities. Incorporating these voices ensures AI governance frameworks are equitable, culturally relevant, and socially responsible, preventing the global deployment of AI systems that unintentionally reinforce inequalities.

Meaningful engagement during the AI Dialogue can be fostered through a mix of interactive and inclusive formats. Structured panels and roundtables allow experts from governments, industry, academia, and civil society to debate key AI governance issues. Workshops and scenario-based exercises enable participants to explore ethical dilemmas and regulatory trade-offs hands-on. Breakout groups and thematic labs provide space for diverse or underrepresented voices, while digital tools, like real-time polling, collaborative whiteboards, and hybrid participation, ensure broader engagement across geographies. Case studies and knowledge-sharing sessions translate principles into practical governance lessons, connecting global standards to local contexts. By combining structured discussion with interactive, inclusive, and technology-enabled formats, AI Dialogue can generate trust, collaboration, and actionable insights that advance responsible AI governance worldwide.

AI governance uses frameworks, practices, and platforms to manage risks like bias and ethics. Frameworks NIST AI RMF: Risk-focused, customizable oversight. EU AI Act: Risk-based rules, audits. ISO/IEC 42001: Certifiable ethics standard. Practices Cross-functional teams, bias audits, lifecycle checks. Platforms Microsoft Copilot OneTrust: Risk automation. Holistic AI: Testing/compliance. Mirantis: Policy-as-code.