Technology for Inspiration Initiative

First, success would mean achieving a shared baseline understanding of responsible AI principles across diverse stakeholders—governments, civil society, private sector, and academia. While frameworks like those from UNESCO and the OECD already exist, the Dialogue should move toward convergence, especially on transparency, accountability, human rights, and safety. Second, it should produce clear, actionable commitments. This could include agreement on priority areas such as risk classification, data governance standards, and safeguards against harms like bias, misinformation, and surveillance abuse. Even non-binding, these commitments should be specific enough to guide national and regional policies. Third, inclusion must be a defining outcome. Ensuring meaningful participation from the Global South, including countries like Nigeria, would signal legitimacy and fairness. Success would mean that underrepresented regions shape not just receive AI governance norms, particularly around equity, access, and local context. Fourth, the Dialogue should catalyze multi-stakeholder collaboration mechanisms. This could take the form of working groups, policy labs, or ongoing platforms that continue beyond the event, ensuring continuity and accountability. Fifth, tangible support for capacity building is essential. Commitments to fund technical expertise, regulatory readiness, and digital infrastructure—especially for low- and middle-income countries—would demonstrate seriousness about equitable AI governance. Finally, success would be reflected in measurable next steps: a roadmap, timelines, and a follow-up process to track progress.

• Safe, secure and trustworthy AI
• AI capacity-building
• Social, economic, ethical, cultural, linguistic and technical implications of AI
• Interoperability of governance approaches

These priorities reflect the urgent need to ensure that AI development and deployment are safe, inclusive, and accountable, particularly in emerging and under-resourced contexts. Safe, secure, and trustworthy AI is foundational, as the rapid adoption of AI systems without adequate safeguards can amplify risks such as misinformation, bias, and cybersecurity threats. Establishing trust is critical for sustainable adoption. AI capacity-building is essential to address global inequalities. Many countries, including Nigeria, face gaps in technical expertise, infrastructure, and regulatory readiness. Investing in skills development, institutional strengthening, and local innovation ecosystems ensures that no region is left behind. Protection and promotion of human rights must remain central to AI governance. AI systems can unintentionally reinforce discrimination or enable surveillance if not properly regulated. A rights-based approach ensures that technologies uphold dignity, equity, and inclusion. Finally, transparency, accountability, and human oversight are critical to responsible AI. Clear mechanisms for explaining AI decisions, assigning responsibility, and maintaining human control help prevent misuse and build public confidence.

First, data sovereignty and digital self-determination are increasingly critical. Many countries, including Nigeria, risk becoming data suppliers without equitable control or benefit. Governance frameworks should address who owns, accesses, and profits from data, particularly in cross-border contexts. Second, infrastructure inequality remains a major barrier. AI governance often assumes stable power, connectivity, and compute capacity, which are not universally available. Without addressing these structural gaps, global AI governance risks reinforcing existing digital divides. Third, linguistic and cultural representation is underemphasized. AI systems are still heavily biased toward dominant languages and contexts, marginalizing local knowledge systems and African languages. This raises concerns about inclusivity, accuracy, and cultural preservation. Fourth, environmental and climate impacts of AI are an emerging concern. The energy consumption of large-scale AI systems and data centers has implications for sustainability, particularly in regions already vulnerable to climate change. Fifth, labor and economic displacement requires deeper focus. Beyond job loss, AI is reshaping informal economies, digital labor, and creative industries in ways that are not yet fully captured in governance discussions. Finally, context-sensitive governance and policy localization is essential. Global frameworks must be adaptable to local realities, ensuring that implementation reflects socio-economic, political, and cultural contexts rather than a one-size-fits-all model.

Governance gaps in AI are already shaping both the risks and opportunities within countries like Nigeria and across the broader African region, particularly in the civic tech, health, and nonprofit sectors. A major challenge is the limited regulatory and institutional capacity to oversee AI systems. While adoption is growing, there is often no clear guidance on standards for safety, accountability, or ethical use. This creates risks such as biased AI systems in health or education, weak data protection practices, and limited recourse when harm occurs. Another key gap is low AI capacity and infrastructure. Many organizations lack access to technical expertise, compute resources, and funding needed to responsibly develop or deploy AI solutions. This limits local innovation and increases dependence on external technologies that may not reflect local realities. Human rights concerns are also significant. Without strong safeguards, AI systems can reinforce inequalities, enable surveillance, or exclude marginalized populations especially young people and women who are already underserved in digital ecosystems. At the same time, these gaps present important opportunities. AI can significantly expand access to health information, education, and civic participation, particularly through digital platforms and localized tools. In the nonprofit sector, there is growing potential to use AI for data-driven advocacy, service delivery, and community engagement. There is also an opportunity to leapfrog legacy systems by embedding ethical and inclusive governance from the outset. By investing in capacity-building, local datasets, and youth-driven innovation, countries like Nigeria can help shape context-relevant AI governance models.

The Global Dialogue on AI Governance can play a pivotal role as a neutral, inclusive platform for building trust, alignment, and sustained collaboration across countries and sectors. First, it can advance policy coherence and interoperability by helping align existing frameworks and standards developed by institutions such as UNESCO and the OECD. By facilitating dialogue among governments, the private sector, and civil society, it can reduce fragmentation and promote mutually reinforcing approaches to AI governance. Second, the Dialogue can strengthen multi-stakeholder cooperation by creating structured mechanisms—such as working groups, knowledge-sharing platforms, and policy labs—that persist beyond the event. This is particularly important for ensuring that underrepresented regions, including countries like Nigeria, are active contributors to global AI governance rather than passive recipients. Third, it can serve as a catalyst for capacity-building partnerships. By connecting technical experts, funders, and policymakers, the Dialogue can mobilize resources to support skills development, institutional strengthening, and infrastructure in low- and middle-income countries. Fourth, the Dialogue can promote collective responses to transnational risks, such as misinformation, cyber threats, and cross-border data governance challenges. AI systems operate globally, and coordinated international action is essential to manage these shared risks effectively. Finally, it can establish accountability and continuity mechanisms, including shared roadmaps, voluntary commitments, and periodic progress reviews. This ensures that cooperation is not symbolic but results in measurable progress.

The AI Dialogue should build on existing global and regional initiatives to avoid duplication and accelerate progress. Key frameworks include the UNESCO Recommendation on the Ethics of AI and the OECD AI Principles, both of which provide widely endorsed normative foundations. It should also connect with implementation-oriented efforts such as the Global Partnership on AI (GPAI), which advances research and policy collaboration, and the African Union Continental AI Strategy, which reflects Africa's priorities around inclusion, innovation, and sovereignty. In addition, regional policy ecosystems and multi-stakeholder forums such as national AI strategies, digital rights coalitions, and civil society networks offer valuable, context-specific insights. These are particularly important in countries like Nigeria, where local innovation and advocacy communities are actively shaping responsible technology use despite capacity constraints. The added value of the AI Dialogue lies in its ability to connect these fragmented efforts into a more coherent global architecture. It can serve as a bridge between high-level principles and on-the-ground implementation by fostering alignment across initiatives, identifying gaps, and promoting shared priorities. Furthermore, the Dialogue can elevate underrepresented voices, especially from the Global South, ensuring that global governance is more equitable and context-sensitive. It can also mobilize practical support, including funding, technical assistance, and knowledge exchange, to help translate frameworks into action.

Different stakeholders—governments, civil society, private sector, academia, and technical communities can each play a complementary role in advancing the objectives of the AI Dialogue. Governments can provide regulatory perspectives, share national AI strategies, and identify policy gaps. Their active participation ensures that global norms translate into actionable, context-sensitive policies. Civil society organizations can bring insights on human rights, equity, and ethical AI, ensuring that societal impacts, particularly on marginalized groups, are not overlooked. They can also help amplify public awareness and foster inclusive participation. Private sector actors can contribute technical expertise, real-world case studies, and innovation perspectives, highlighting practical challenges in implementing AI responsibly. Their engagement is critical for understanding deployment risks and designing accountability mechanisms. Academia and research institutions can provide evidence-based insights, risk assessments, and best practices, contributing to informed decision-making and capacity-building initiatives. Technical communities and developers can ensure discussions are grounded in feasible technological realities, including model transparency, interoperability, and security considerations. Regarding format and structure, the Dialogue should combine: Plenary sessions to present high-level visions, global trends, and key thematic issues. Interactive workshops and thematic roundtables focused on areas such as safe AI, human rights, transparency, and capacity-building. These should include multi-stakeholder representation to encourage knowledge exchange and collaborative problem-solving. Regional and sectoral breakout sessions to reflect local contexts and sector-specific priorities, ensuring inclusivity and relevance. Public engagement components (online forums or consultations) to solicit inputs from broader civil society and youth groups. Mechanisms for follow-up, including working groups, policy labs, or knowledge-sharing platforms, to translate discussions into tangible actions and track progress over time.

Several voices remain underrepresented in global AI governance discussions, limiting the inclusivity and legitimacy of policymaking. Global South perspectives are often marginalized, despite these regions facing unique challenges related to infrastructure gaps, digital literacy, and socio-economic inequalities. Countries like Nigeria have emerging AI ecosystems, but limited participation in global forums reduces the visibility of their priorities and local innovation. Youth and women, particularly in STEM and digital policy spaces, are frequently excluded. Their perspectives are critical for shaping ethical, equitable, and forward-looking AI policies, especially as they are both major beneficiaries and potential victims of AI systems. Indigenous peoples and linguistic minorities are also underrepresented. AI systems often ignore local languages, cultural norms, and traditional knowledge, raising risks of digital exclusion, misrepresentation, and bias. Civil society and community-based organizations from under-resourced regions often lack access to technical or policy discussions, even though they provide essential insights on social, ethical, and human rights implications of AI. To include these voices, the Dialogue could: Offer targeted representation, such as reserved seats or speaking opportunities for Global South governments, youth organizations, women-led tech initiatives, and Indigenous representatives. Provide capacity-building and preparatory support, including briefings, mentorship, and resources to ensure underrepresented actors can meaningfully participate and contribute. Use multi-lingual formats and accessible platforms, enabling participation across language barriers and regions with limited connectivity. Establish structured mechanisms for ongoing engagement, such as regional consultative hubs, virtual participation channels, and community-led working groups, to ensure continuous input beyond a single event.

To foster meaningful and dynamic engagement during the AI Dialogue, a combination of interactive, multi-modal, and inclusive formats is essential. Traditional plenaries alone are insufficient for tackling complex, multi-stakeholder AI governance challenges. 1. Multi-stakeholder roundtables and breakout sessions – Organize thematic tables where participants from governments, civil society, private sector, academia, and technical communities collaboratively address specific challenges such as safe AI, transparency, or capacity-building. Structured discussions with facilitators encourage dialogue rather than one-way presentations. 2. Scenario-based simulations and policy labs – Use real-world case studies or hypothetical AI deployments to explore governance dilemmas in areas like bias, surveillance, or algorithmic accountability. This hands-on approach helps participants understand trade-offs and experiment with potential policy solutions. 3. Interactive digital platforms – Incorporate live polls, Q&A, and virtual collaboration tools to engage both in-person and remote participants. Multi-lingual online spaces allow global contributions, especially from underrepresented regions such as the Global South. 4. Hackathons and co-creation workshops – Bring together developers, policymakers, and civil society to prototype AI governance tools, guidelines, or monitoring frameworks. This encourages practical innovation and immediate knowledge sharing. 5. Youth and community voices sessions – Dedicate forums for youth, women, and Indigenous communities to share perspectives and propose solutions, ensuring their voices influence the broader dialogue. 6. Interactive exhibitions and demos – Showcase emerging AI applications, governance frameworks, and ethical toolkits. Live demonstrations make abstract concepts tangible and spark cross-sector learning. 7. Follow-up "commitment boards" and accountability dashboards – Capture participants' pledges and track implementation progress post-Dialogue, creating a living record of actions and accountability.

1. Ethical frameworks and guidelines - The UNESCO Recommendation on the Ethics of AI and the OECD AI Principles offer globally recognized standards emphasizing human rights, transparency, and accountability. These frameworks guide governments and organizations in designing responsible AI systems. 2. Multi-stakeholder platforms - The Global Partnership on AI (GPAI) brings together governments, academia, and industry to collaborate on AI research, policy guidance, and practical solutions. Similarly, regional initiatives like the African Union Continental AI Strategy promote local capacity-building, inclusivity, and innovation. 3. Regulatory sandboxes and experimentation - Countries such as Singapore and United Kingdom explainability, which strengthens accountability. 5. Data governance and privacy regulations - Policies like the European Union guidance, practical experimentation, stakeholder collaboration, and capacity-building, providing replicable models for countries like Nigeria.