Foundation for Partnership Initiatives in the Niger Delta

In my opinion and based on my expertise, a successful first Global Dialogue on AI Governance should deliver practical, context-aware outcomes that reflect the realities of deploying AI in fragile and conflict-affected settings. From my experience working on AI-enabled conflict analysis and early warning systems in the Niger Delta region of Nigeria, success would require a clear, action-oriented roadmap for global cooperation. This roadmap should move beyond high-level principles to define priority risks, coordination mechanisms, and implementation pathways, particularly for countries with limited regulatory and technical capacity, where exposure to AI risks is high but preparedness remains low. Second, the Dialogue should formally recognize AI's implications for peace, security, and democratic processes. This includes addressing emerging threats such as synthetic media, hate speech amplification, and misinformation in electoral contexts, especially risks related to false result transmission and the manipulation of digital election systems. Establishing a dedicated focus on AI and conflict prevention, alongside commitments to strengthen information integrity through transparency standards and coordinated responses to disinformation, would represent a meaningful and timely outcome. Finally, success should be measured by the extent to which the Dialogue catalyzes targeted capacity-building support for the Global South and institutionalizes inclusive, multi-stakeholder participation. This includes investing in data systems, local research ecosystems, and governance capacity, while ensuring that practitioners, researchers, and affected communities actively shape global frameworks. Ultimately, the Dialogue must advance inclusive and implementable governance approaches grounded in real-world risks and local realities.

• Safe, secure and trustworthy AI
• Transparency, accountability, and human oversight
• Protection and promotion of human rights
• Social, economic, ethical, cultural, linguistic and technical implications of AI

From a peacebuilding and governance lens shaped by experience working with AI-enabled conflict analysis and early warning systems in fragile contexts. The social, economic, ethical, cultural, linguistic, and technical implications of AI are central because these systems interact directly with existing inequalities, identities, and narratives. In contexts like the Niger Delta region of Nigeria, poorly contextualized AI can reinforce exclusion, misrepresent local languages, and amplify grievances, while well-designed systems can strengthen inclusion, improve access to information, and support community resilience. Safe, secure, and trustworthy AI is also a priority due to the increasing risks of synthetic media, misinformation, and manipulation of digital information ecosystems, particularly during elections and periods of heightened tension. Ensuring system reliability, robustness, and safeguards against misuse is critical to preventing escalation and maintaining public trust in institutions. Transparency, accountability, and human oversight are essential in governance and security applications of AI, where opaque systems can produce harmful or biased outcomes. In conflict-sensitive environments, human-in-the-loop approaches and clear accountability frameworks help ensure that AI-supported decisions remain contextually informed, traceable, and responsible. Finally, the protection and promotion of human rights underpins all other priorities. In settings with weak regulatory capacity, AI can enable surveillance, data misuse, and digital repression if not properly governed. Embedding human rights principles ensures that AI deployment supports dignity, inclusion, and trust. Collectively, these priorities are mutually reinforcing and critical for ensuring that AI contributes to peace, stability, and equitable development rather than exacerbating existing vulnerabilities across diverse and rapidly evolving contexts.

Speaking from my experience, several cross-cutting and emerging issues require more explicit attention, particularly from the perspective of fragile and conflict-affected contexts. First is the intersection of AI, conflict dynamics, and information integrity. The growing use of synthetic media, coordinated disinformation, and AI-amplified hate speech is reshaping how conflicts emerge and escalate, especially during elections and crises. This goes beyond general safety or transparency concerns and calls for dedicated frameworks linking AI governance with peacebuilding, early warning systems, and conflict prevention strategies. Second is context sensitivity and localization of AI systems. Many AI models are developed using datasets and assumptions that do not reflect local realities in regions like Africa, creating risks of bias, misinterpretation, and harmful or ineffective interventions. Another is the challenge of governance capacity asymmetry. There is a widening gap between countries developing advanced AI systems and those primarily consuming them without adequate regulatory, technical, or institutional capacity. This raises concerns around digital sovereignty, dependency, and the ability of developing countries to shape global AI norms. Finally, there is a need to better integrate AI into existing governance and peacebuilding infrastructures. This includes aligning AI tools with early warning and response systems, data governance frameworks, and community-based mechanisms to ensure coherence, trust, and sustainability. Addressing these cross-cutting issues is essential for building inclusive, context-responsive, and effective global AI governance frameworks that are grounded in real-world risks and development priorities.

In Nigeria and the broader Niger Delta region, governance gaps in AI, combined with rapid technological advances, are creating both significant risks and opportunities for peace, security, and development. One major challenge is the lack of regulatory frameworks and institutional capacity to oversee AI deployment. This exposes communities to misinformation, election-related disinformation, and AI-generated synthetic media, which can fuel tensions, undermine public trust, and exacerbate existing conflicts. Limited technical capacity among policymakers and civil society also constrains the ability to assess AI's social, ethical, and cultural impacts, increasing the likelihood of biased or harmful outcomes. Another challenge is the underrepresentation of local languages and cultural contexts in AI systems. Many deployed models are trained on global datasets that do not capture local realities, which can lead to misinterpretation, exclusion, or marginalization of certain communities. Additionally, the opacity of AI tools, without transparency, accountability, and human oversight, poses risks for governance, security, and human rights protection. However, there are opportunities to leverage AI for conflict prevention, early warning, and community engagement. With appropriate governance measures, AI can improve data-driven decision-making, enhance monitoring of local tensions, and support targeted interventions in fragile areas. Investments in capacity-building, locally relevant AI research, and multi-stakeholder collaboration can turn these emerging technologies into tools for inclusive development, resilience, and strengthened governance in the region.

Building on my experience in AI-enabled conflict analysis and early warning systems in the Niger Delta, the AI Dialogue can play a critical role by fostering multi-stakeholder engagement that ensures voices from underrepresented countries, local communities, and conflict-affected contexts are included in shaping global AI governance frameworks. My work has shown that without local input, AI systems risk misrepresenting realities, amplifying grievances, and undermining trust. The Dialogue can help establish norms, standards, and technical guidelines that are culturally sensitive, context-aware, and adaptable to diverse governance capacities, particularly in fragile regions where regulatory structures are still developing. Furthermore, the Dialogue can catalyze targeted capacity-building initiatives, supporting countries in strengthening institutional frameworks, technical expertise, and regulatory readiness. From my perspective, embedding AI into peacebuilding and governance infrastructures, such as early warning and response systems requires ongoing collaboration, knowledge-sharing, and ethical oversight, which the Dialogue can facilitate. It can also coordinate the development of shared mechanisms for transparency, accountability, and human oversight, mitigating risks of misinformation, hate speech, and algorithmic bias. By creating a platform for continuous learning, research collaboration, and iterative policy improvement, the AI Dialogue can help transform AI governance from fragmented national approaches into a coordinated, inclusive, and context-sensitive international framework, ultimately enabling AI to support peace, security, and sustainable development in regions like the Niger Delta and beyond.

From my perspective, the added value of the AI Dialogue lies in its ability to bridge global and regional frameworks with the realities of conflict-affected and underrepresented regions. Globally, frameworks such as the OECD AI Principles, the UN Secretary-General's Roadmap on Digital Cooperation, and the African Union's Digital Transformation Strategy provide normative guidance and best practices for responsible AI development. However, these global initiatives often remain high-level and are not fully tailored to contexts where governance, technical capacity, and institutional infrastructure are limited. In the Niger Delta, for example, AI tools have demonstrated potential to strengthen early warning and response systems, improve data-driven decision-making, and support targeted peacebuilding interventions—but this potential can only be realized if governance frameworks are context-sensitive, inclusive, and practically oriented. The AI Dialogue can facilitate structured knowledge sharing between global experts, regional policymakers, and local practitioners, enabling adaptation of AI tools to local languages, cultural contexts, and governance realities, while also integrating lessons from other regions experiencing fragility, political tensions, or post-conflict reconstruction. Moreover, the Dialogue can coordinate capacity-building initiatives for countries with limited technical and regulatory infrastructure, connecting them with global research networks, technical standards, and policy guidance. Based on my experience implementing AI-enabled conflict monitoring and early warning systems, this coordination is critical for translating international principles into operational practices that address real-world risks, including disinformation, synthetic media, and algorithmic bias. By linking global norms and standards with localized implementation, the AI Dialogue can act as a catalyst for inclusive, actionable, and context-aware AI governance, strengthening both peace and sustainable development outcomes across underrepresented and high-risk regions worldwide.

Different stakeholders can contribute to the AI Dialogue by bringing their unique expertise, perspectives, and operational experience to ensure AI governance frameworks are inclusive, context-aware, and actionable. Governments can share national strategies, regulatory experiences, and lessons learned from implementing AI policies in public institutions, including elections, security, and service delivery. Civil society organizations and community-based actors can highlight the social, cultural, and human rights implications of AI, particularly in underrepresented and conflict-affected regions, ensuring governance approaches reflect the realities of those most affected. Academia and research institutions can provide evidence-based insights, evaluations of AI risks and benefits, and context-specific research on ethics, peacebuilding, and socio-technical impacts. Private sector actors and technology developers can share technical knowledge, innovations, and operational practices that promote trustworthy AI, as well as support pilot projects and knowledge transfer. International organizations and multilateral platforms can facilitate coordination, standard-setting, and capacity-building initiatives, linking global norms with local implementation. Regarding the format, the AI Dialogue should adopt a multi-tiered, participatory approach to maximize inclusivity and practical relevance. Plenary sessions can provide space for high-level discussions on global priorities, emerging risks, and lessons learned. Thematic working groups aligned with key areas such as trustworthy AI, human rights, capacity-building, and conflict-sensitive AI deployment can enable deep technical and policy engagement. Regional and sectoral consultations would ensure that local experiences, challenges, and culturally relevant solutions are surfaced, giving voice to underrepresented and conflict-affected regions. To reinforce continuity and implementation, the Dialogue should integrate knowledge-sharing platforms and technical workshops to support capacity-building, exchange of best practices, and co-development of operational guidelines. Follow-up mechanisms, including annual reports, collaborative monitoring, and implementation trackers, would help maintain accountability and facilitate iterative improvement. By combining high-level coordination with localized, evidence-driven input, the AI Dialogue can produce practically relevant, inclusive, and actionable outcomes that guide responsible AI governance globally while addressing the needs of vulnerable and high-risk contexts.

From my observation in fragile communities in the Niger Delta, several voices and perspectives remain underrepresented in global discussions on AI governance. Local communities, who are directly affected by AI-driven misinformation, synthetic media, and digital surveillance, rarely have access to international policy platforms. Their experiences, particularly around conflict dynamics, election integrity, and social cohesion, are often overlooked in favor of perspectives from high-income countries and large technology companies. Similarly, civil society organizations, grassroots practitioners, and community-based monitors—who engage directly in peacebuilding, human rights protection, and inclusive development—have limited opportunities to influence international AI policy and standards. Women, youth, and linguistically or culturally marginalized groups are also frequently excluded from shaping AI governance frameworks. AI systems that do not account for local languages, cultural norms, or gendered vulnerabilities risk reinforcing inequality and social exclusion. Smaller research institutions and academic voices from the Global South, which often produce context-specific AI research, are also underrepresented, limiting the diversity of evidence and insights informing global governance standards. To address these gaps, the AI Dialogue should actively incorporate regional consultations and localized engagement mechanisms. This could include dedicated sessions for conflict-affected and underrepresented regions, structured input from community organizations, and translation of technical materials into local languages. Capacity-building and mentorship programs can support smaller institutions and grassroots stakeholders to contribute meaningfully, while multi-stakeholder advisory panels including practitioners from fragile contexts, youth networks, and civil society actors can ensure that AI governance frameworks are informed by lived realities, culturally relevant, and inclusive. This approach would make global AI governance more equitable, context-sensitive, and actionable for vulnerable communities.

Based on my experience working in conflict-affected regions such as the Niger Delta, meaningful engagement in AI governance requires formats that are interactive, inclusive, and context-sensitive, moving beyond traditional plenary sessions. One effective approach would be thematic working groups or "policy labs" that bring together governments, civil society, local practitioners, researchers, and private sector actors around specific challenges, such as trustworthy AI, conflict-sensitive deployment, and human rights protection. These labs would enable participants to co-design solutions, test policy scenarios, and develop actionable recommendations in real time, ensuring that discussions move from theory to practice. Regional and sectoral consultations are also critical to surface local experiences, particularly from underrepresented and fragile contexts. These could take the form of virtual or in-person community roundtables, allowing grassroots practitioners, youth, and marginalized groups to directly contribute perspectives on AI risks and opportunities in their communities. Integrating digital collaboration platforms can extend participation, enabling real-time input, multilingual engagement, and asynchronous contributions from stakeholders who cannot attend physically. Finally, interactive demonstration sessions and scenario-based exercises can help illustrate AI's real-world implications, including both opportunities and risks in governance, peacebuilding, and electoral processes. By combining structured presentations with participatory simulations, these sessions can promote dialogue, enhance mutual understanding, and strengthen the practical relevance of policy discussions. Coupled with follow-up mechanisms—such as knowledge repositories, collaborative monitoring dashboards, and iterative feedback loops—these formats can ensure that the AI Dialogue remains dynamic, inclusive, and actionable, bridging global principles with local realities and fostering sustained international cooperation.

In my experience working at the intersection of AI, conflict monitoring, and peacebuilding in the Niger Delta, several global policies, practices, and platforms provide practical models for effective AI governance and addressing emerging risks. The OECD AI Principles offer a foundation for trustworthy AI, emphasizing transparency, accountability, human oversight, fairness, and robustness, and have influenced national strategies in countries such as Canada, France, and Singapore. The UN Secretary-General's Roadmap on Digital Cooperation promotes inclusive, multi-stakeholder collaboration and capacity-building, which is particularly critical for underrepresented regions with limited technical and institutional infrastructure. At the regional level, the African Union's Digital Transformation Strategy and its work on AI ethics and data governance illustrate how continent-specific standards can address linguistic, cultural, and socio-economic diversity, ensuring that AI deployment is context-sensitive and ethically grounded. Practical applications also offer concrete examples of operationalizing governance principles. Early warning and response systems (EWER) enhanced with AI-driven analytics demonstrate how transparency, accountability, and human oversight can be embedded in real-world systems, as seen in the Niger Delta's community-based conflict monitoring initiatives. Platforms such as the Global Partnership on AI (GPAI) and Partnership on AI facilitate multi-stakeholder collaboration, enabling research, knowledge exchange, and capacity-building. Emerging approaches, including synthetic media detection tools, algorithmic auditing frameworks, and open-source AI models, help mitigate risks related to misinformation, bias, and misuse. Together, these policies, practices, and platforms provide actionable pathways for implementing responsible AI governance that safeguards human rights, promotes inclusion, and strengthens institutional and societal resilience in both global and localized contexts.