Centre for AI and Multidiscipline Solutions in Africa (CAIMSA)

A successful first Global Dialogue on AI Governance would deliver both concrete outcomes and a strong foundation for ongoing cooperation. First, it should produce a shared set of guiding principles that reflect broad consensus across governments, industry, academia, and civil society. These principles should emphasize transparency, accountability, fairness, human rights, and safety, while remaining flexible enough to adapt to rapid technological change. Second, the dialogue should lead to practical commitments. This could include agreements on baseline safety standards, responsible data use, and mechanisms for auditing and evaluating AI systems. Establishing pathways for interoperability between national and regional frameworks would also be a key achievement, helping to reduce fragmentation and regulatory gaps. Third, inclusivity must be central. Success would mean meaningful participation from the Global South, ensuring that perspectives from regions like Africa are reflected in global AI governance. Capacity-building initiatives, knowledge sharing, and support for local innovation ecosystems should be clearly outlined. Fourth, the dialogue should result in a roadmap for continued engagement. This includes forming working groups, setting timelines for follow-up actions, and identifying responsible stakeholders to drive implementation. Finally, trust-building is essential. If the dialogue fosters mutual understanding, reduces geopolitical tensions around AI, and encourages collaboration rather than competition, it will have achieved a critical milestone. In essence, success lies not only in what is agreed upon, but in the momentum created for sustained, inclusive, and action-oriented global cooperation on AI governance.

• Safe, secure and trustworthy AI
• AI capacity-building
• Protection and promotion of human rights
• Transparency, accountability, and human oversight

My selection reflects a commitment to responsible, inclusive, and impactful AI development. Safe, secure and trustworthy AI is a top priority because public confidence in AI systems depends on their reliability, resilience, and alignment with ethical standards. Without trust, adoption and long-term benefits of AI will remain limited. AI capacity-building is essential to ensure that all regions, particularly developing economies, can actively participate in and benefit from AI advancements. Strengthening skills, infrastructure, and institutional readiness helps bridge the global digital divide and supports sustainable innovation. The protection and promotion of human rights is central to ensuring that AI systems do not perpetuate bias, discrimination, or exclusion. Embedding human rights principles in AI design and deployment safeguards dignity, equality, and fairness across societies. Finally, transparency, accountability, and human oversight are critical for maintaining control and responsibility over AI systems. Clear governance mechanisms, explainability, and human-in-the-loop approaches help ensure that AI decisions can be understood, challenged, and improved where necessary. Together, these priorities create a balanced framework that promotes innovation while ensuring ethical integrity, inclusivity, and long-term societal benefit.

Yes, there are several cross-cutting and emerging issues that are not fully captured by the listed themes but are increasingly important for global AI governance. One key area is environmental sustainability of AI systems. The growing computational demands of large-scale AI models raise concerns about energy consumption, carbon emissions, and resource use. AI governance should therefore include standards for energy efficiency, green computing, and sustainable infrastructure development. Another emerging issue is data sovereignty and cross-border data governance. As AI systems rely heavily on large datasets, questions around where data is stored, how it is shared, and who has jurisdiction over it are becoming more critical, especially for developing countries seeking to protect national interests while enabling innovation. Cybersecurity and AI misuse risks also deserve stronger emphasis. Beyond general "safe and secure AI," there is a need to address AI-enabled cyberattacks, deepfakes, misinformation, and other malicious uses that can undermine trust in digital ecosystems and democratic processes. Additionally, labor market transformation and future of work is a significant cross-cutting concern. AI is rapidly reshaping employment patterns, requiring proactive policies for reskilling, social protection, and just transition strategies to avoid widening inequalities. Finally, global coordination and enforcement mechanisms remain a gap. While principles and frameworks are important, effective governance will depend on practical enforcement tools, monitoring systems, and international cooperation structures that ensure compliance and accountability. Addressing these emerging issues alongside the existing themes will strengthen the comprehensiveness and resilience of global AI governance frameworks.

In my context, the existing governance gaps in AI particularly around safety standards, capacity-building, human rights safeguards, and accountability frameworks are having both constraining effects and creating new opportunities. One of the most significant challenges is the limited local regulatory and technical capacity to effectively assess, audit, and govern rapidly evolving AI systems. This creates dependency on external tools and frameworks, which may not fully reflect local priorities, cultural contexts, or development needs. As AI adoption increases across sectors such as education, finance, public services, and communication, this gap raises concerns about bias, data privacy, and algorithmic accountability. Another challenge is the uneven access to AI infrastructure and skills. Many institutions and professionals in the region are still in early stages of AI literacy, which slows down responsible adoption and limits the ability to fully benefit from AI-driven innovation. This also increases the risk of misuse or unregulated deployment of AI tools. At the same time, there are important opportunities. The growing global focus on AI capacity-building is opening pathways for training, partnerships, and knowledge transfer. This can accelerate local expertise development and support innovation ecosystems. Efforts to strengthen human rights based and transparent AI governance also provide an opportunity to build more trusted digital systems from the start, rather than retrofitting safeguards later. This is particularly important for improving public service delivery and digital trust. Additionally, increased international dialogue on AI governance is creating space for greater regional inclusion and representation, enabling countries in the Global South to influence global standards and ensure they are more equitable and context aware. Overall, while governance gaps present real risks, they also offer a critical opportunity to build more inclusive, resilient, and locally relevant AI ecosystems.

The AI Dialogue can play a central role in strengthening international cooperation by serving as a neutral, inclusive, and action oriented platform for aligning global efforts on AI governance. First, it can help build shared understanding and trust among countries with different levels of technological development, regulatory approaches, and strategic priorities. By facilitating open exchange, the Dialogue can reduce fragmentation and promote convergence on core principles such as safety, human rights, transparency, and accountability. Second, the Dialogue can move beyond high level principles by supporting the development of practical cooperation mechanisms, including shared standards, interoperability guidelines, and common risk assessment approaches. This would help ensure that AI governance frameworks are not only compatible but also mutually reinforcing across jurisdictions. Third, it can strengthen capacity building and knowledge transfer, particularly for developing countries. Through structured partnerships, technical assistance, and collaborative research initiatives, the Dialogue can help reduce global inequalities in AI readiness and enable more equitable participation in AI development and governance. Fourth, the AI Dialogue can act as a bridge between stakeholders, bringing together governments, industry, academia, and civil society in a structured setting. This multi-stakeholder engagement is essential for ensuring that governance frameworks are balanced, inclusive, and responsive to real-world needs. Finally, it can establish a long term roadmap for coordination, including working groups, follow-up mechanisms, and monitoring frameworks that translate dialogue into sustained action. In this way, the AI Dialogue can become a cornerstone of global AI governance by transforming fragmented national efforts into a more coherent, cooperative, and future-oriented international system.

The AI Dialogue should build upon and connect with a range of existing global, regional, and multi-stakeholder initiatives to ensure coherence and avoid duplication. At the international level, it can align with frameworks such as UNESCO's Recommendation on the Ethics of Artificial Intelligence, which provides a strong normative foundation for ethical AI governance. It should also complement the OECD AI Principles and the Global Partnership on Artificial Intelligence (GPAI), both of which promote trustworthy AI development, policy coordination, and practical collaboration among stakeholders. Regionally, the Dialogue should take into account emerging African digital and AI strategies that emphasize capacity-building, digital transformation, and inclusive innovation. In this context, institutions such as the CAIMSA (Centre for AI and Multidiscipline Solutions in Africa) are particularly important. CAIMSA plays a growing role in advancing interdisciplinary AI research, capacity development, and practical solutions tailored to African development priorities. Strengthening collaboration with such centres would ensure that African perspectives, research, and innovation ecosystems are meaningfully integrated into global AI governance discussions in Tanzania. The Dialogue can also build on industry-led AI safety initiatives, open-source AI communities, and academic research networks, which contribute technical expertise, experimentation, and real-world implementation experience. The added value of the AI Dialogue lies in its ability to serve as a global, inclusive coordination platform that bridges fragmented initiatives and ensures equitable participation from both developed and developing countries. It can help harmonize diverse regulatory and ethical approaches, while translating high-level principles into actionable cooperation mechanisms. Importantly, it can also address gaps not fully covered elsewhere, such as global risk monitoring, interoperability of governance frameworks, and equitable access to AI infrastructure and knowledge. In this way, the AI Dialogue can act as a central hub for strengthening synergies across existing efforts, while advancing a more inclusive, balanced, and effective global AI governance ecosystem.

Different stakeholders can contribute to the AI Dialogue in complementary and meaningful ways, ensuring it becomes a truly inclusive and action-oriented platform. Governments should provide policy direction, share national experiences, and work toward aligning regulatory approaches. They can help identify priority risks, define minimum governance standards, and support international coordination on safety, human rights, and accountability. Private sector actors should contribute technical expertise, real-world deployment insights, and innovation perspectives. Their involvement is essential for discussing feasibility, standards for responsible AI development, and mechanisms for transparency, auditing, and safety assurance. Academia and research institutions can provide independent evidence, risk analysis, and methodological frameworks to guide policy decisions. They also play a key role in advancing explainable AI, ethics research, and impact assessment tools. Civil society organizations should ensure that human rights, equity, and public interest considerations remain central. They can amplify voices of affected communities and help monitor the societal impacts of AI systems. Regional institutions and initiatives such as CAIMSA (Centre for AI and Multidiscipline Solutions in Africa) can ensure that regional perspectives, particularly from Africa and the Global South, are integrated. They can also contribute practical research, capacity-building programs, and locally relevant solutions. Recommended format and structure: The AI Dialogue should adopt a multi-stakeholder, multi-level structure combining high-level plenary sessions with thematic working groups. These working groups could focus on key areas such as safety, capacity-building, human rights, interoperability, and emerging risks. It should also include regional consultation tracks to ensure balanced geographic representation and context-specific input. Between sessions, a permanent technical secretariat or coordination hub could support continuity, knowledge sharing, and follow-up on commitments. Finally, the Dialogue should prioritize action-oriented outcomes, including shared frameworks, voluntary commitments, and measurable roadmaps rather than purely declarative statements.

Several voices and perspectives remain underrepresented in global discussions on AI governance, particularly those from the Global South, including many African, Pacific, and parts of Asian and Latin American countries. These regions often face the most immediate impacts of AI adoption but have limited influence in shaping global rules and standards, I prefer to have Full sponsorship toward this dialogue when convenience. Local communities and grassroots users, especially in rural and low-income settings, are also underrepresented. Their experiences are critical for understanding how AI affects access to services, livelihoods, language inclusion, and digital inequality, yet they are rarely directly included in policy discussions. Youth and early-career professionals are another important group whose perspectives are often limited, despite being the most long-term users and innovators of AI systems. Similarly, women and marginalized groups continue to be underrepresented in technical and governance spaces, which can result in systems that do not fully reflect diverse needs or reduce bias effectively. Small and medium enterprises (SMEs) and local innovators are also less represented compared to large global technology companies, even though they play a key role in local AI ecosystems. To include these voices, the AI Dialogue should adopt a multi-layered participation model. This includes structured regional consultations, hybrid physical-digital participation formats, and dedicated funding to support participation from developing countries and under-resourced groups. Partnerships with regional institutions such as CAIMSA (Centre for AI and Multidiscipline Solutions in Africa) can help amplify African and interdisciplinary perspectives and ensure that local research and innovation are integrated into global discussions. Additionally, the Dialogue should incorporate youth panels, civil society tracks, and community-level listening sessions to ensure bottom-up input. Capacity-building support, translation services, and accessible formats will also be essential to remove barriers to participation. Overall, meaningful inclusion requires moving beyond symbolic representation toward structured, continuous, and empowered participation in decision-making processes.

To foster meaningful and dynamic engagement during the AI Dialogue, innovative formats should prioritize inclusivity, interaction, and practical outcomes rather than traditional presentation-heavy sessions. One effective approach is multi-stakeholder "challenge labs", where governments, researchers, industry, and civil society collaboratively work on real-world AI governance problems such as bias detection, AI safety auditing, or data governance models. These labs would encourage co-creation of solutions rather than abstract debate. Another format is regional listening sessions combined with global synthesis forums. Regional dialogues—particularly in Africa, Asia, and Latin America—would allow context-specific issues to be raised. These inputs would then be synthesized at the global level to ensure balanced representation of diverse realities. Scenario-based simulations and policy stress tests could also be highly effective. Participants could explore hypothetical AI risks such as misinformation crises or autonomous system failures, testing how different governance frameworks respond in practice. This would help move discussions from theory to applied governance readiness. The Dialogue could also benefit from youth and innovation showcases, where early-career researchers, startups, and innovators present solutions and perspectives on AI governance challenges. This ensures fresh ideas and long-term thinking are included. A continuous digital engagement platform would further enhance participation between formal sessions. This platform could host discussions, surveys, collaborative drafting of principles, and open consultations, ensuring the Dialogue remains active beyond annual meetings. Importantly, partnerships with regional institutions such as CAIMSA (Centre for AI and Multidiscipline Solutions in Africa) could support localized engagement hubs, ensuring African and multidisciplinary perspectives are systematically integrated into all phases of the Dialogue. Finally, interactive consensus-building tools, such as real-time polling, deliberative voting, and structured negotiation formats, could help translate diverse views into actionable agreements efficiently. Together, these formats would transform the AI Dialogue into a participatory, solutions-driven, and globally inclusive governance process.

At the policy level, the EU AI Act is a leading example of a risk-based regulatory framework that classifies AI systems according to their potential harm and imposes stricter obligations on high-risk applications. It is complemented by GDPR, which strengthens data protection and privacy-both essential for trustworthy AI governance. Internationally, the UNESCO Recommendation on the Ethics of Artificial Intelligence provides a global normative framework emphasizing human rights, transparency, fairness, and inclusivity. Similarly, the OECD AI Principles promote responsible stewardship of trustworthy AI and have influenced policy development across many countries. In terms of practical collaboration, the Global Partnership on Artificial Intelligence (GPAI) supports applied research and multi-stakeholder cooperation on AI issues such as responsible AI, innovation, and data governance. On the technical and industry side, platforms like the Partnership on AI (PAI) and open-source communities contribute guidelines, best practices, and toolkits for explainability, bias mitigation, and model evaluation. These help translate governance principles into operational safeguards. In Africa, emerging initiatives and institutions such as CAIMSA (Centre for AI and Multidiscipline Solutions in Africa) play a key role in advancing interdisciplinary research, capacity-building, and context-specific AI solutions that reflect local development priorities. Additionally, AI audit frameworks, algorithmic impact assessments, and model transparency tools are increasingly being adopted to evaluate risks before and after deployment. These approaches help ensure accountability and continuous monitoring of AI systems.