Responsible Tech Through an African Lens: A Conversation on AI, Ethics, and Governance in Nigeria with Bibitayo Ojo
We had the pleasure of speaking with Bibitayo Ojo, a Data Protection Officer and a qualified lawyer specialising in technology law, data protection, data privacy, and AI governance.Bibitayo is a Certified Compliance Analyst and Certified Data Protection Officer, with experience advising organisations on global privacy laws, regulatory compliance, and algorithmic risk. His work focuses on responsible AI deployment, AI governance frameworks, data protection, and balancing technological innovation with accountability.
In this conversation, we explore AI governance through a Nigerian and by extension African lens, discussing responsible technology, privacy and data protection, the evolving regulatory landscape, and what responsible AI development and deployment could look like across Africa.
*Note: transcript has been taken by AI zoom assistant and edited to highlight for readability on key topics covered in the discussion. Please
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How did you end up working at the intersection of technology and society?
Bibitayo’s career path was non-conventional. After qualifying as a barrister and solicitor of the Supreme Court of Nigeria, the COVID-19 pandemic prompted him to reconsider traditional courtroom advocacy. He recognized that emerging technologies like AI require a broader coalition of stakeholders to ensure products and services are not harmful to society. This realization drew him toward data protection, privacy, and ultimately AI governance, as these fields directly intersect with how people's data is used.
What does responsible technology mean to you?
Responsible technology means designing, deploying, and governing technology; particularly AI; in a way that is accountable, transparent, and genuinely inclusive of marginalized groups such as vulnerable populations, children, and the elderly. Bibitayo breaks it into two parts: for developers, ethics must be embedded throughout the entire product lifecycle from design to deployment; for end users, ethical and cautious use of AI tools and designing for marginalized communities are equally important.
How AI Governance Conversations Differ in Nigeria and Across Africa
Bibitayo asserted that Nigeria is actively engaged in discussions on AI Governance. While there is no single holistic AI law, Nigeria adopted a National AI Strategy in 2024, and the African Union released its Continental Strategy for Artificial Intelligence in the said year. It is expected that every member state should localize and ensure that there is a framework for AI. Moreover, he mentions that the Nigerian Data Protection Act (2023) acknowledges gaps and extends its scope to cover emerging technologies including AI. Nigeria is therefore making meaningful progress, even if a comprehensive AI-specific law is still absent.
Global Tech Regulations and Their Impact on Nigeria – Do they reflect the local realities?
These regulations have both inspired and negatively influenced Nigeria. Nigerian data protection law; including the 2019 Data Protection Regulation (now replaced by the 2023 Data Protection Act); was closely modeled on the GDPR. The major concern is that Nigeria often adopts these frameworks wholesale without adapting them to its distinct economy, cultural heritage, and social context. Bibitayo strongly advocates for localization rather than direct copy-pasting of Western legal frameworks.
Work in Ethical Design and Data Protection
In Bibitayo’s previous consultancy role, he conducted over 100 data protection audits across multiple sectors and countries, working with technical and business units to identify and ethically resolve compliance gaps. He also served as a mentor at the Code4Privacy Hackathon organized by Nigeria's Data Protection Authority, guiding young developers to build products ethically. In his personal consulting practice, he continues to advise startups on responsibly integrating AI into their platforms. In addition, he highlights the lack of awareness around emerging areas of technology and law, which has led him to write articles, engage in public speaking, and actively participate in policy advocacy and development.
Where do you think we are getting things wrong when it comes to AI or technology governance?
Bibitayo argues that one of the biggest mistakes in AI and technology governance is waiting for local infrastructure to mature before creating regulations. Using Nigeria as an example, he notes that while the country's AI and data center capacity is still limited compared to global leaders, Africans are already active consumers of AI-powered technologies developed elsewhere. Because these tools are already shaping society, governance cannot be postponed until domestic infrastructure catches up. Instead, policymakers need to proactively establish frameworks that address the impact of AI on citizens, even when the technology is primarily imported rather than locally built.
Examples from Other Global Majority Countries
Bibitayo points to India and Brazil as strong examples of countries that have developed technology governance approaches tailored to their own realities rather than simply copying Western regulations. While these countries draw inspiration from global frameworks, they adapt policies to fit their unique economic, social, and developmental contexts. The key lesson for Nigeria and other African countries is that effective AI governance should be locally grounded, reflecting regional priorities and challenges. At the same time, developments such as the European Union’s AI Act demonstrate the importance of acting early rather than waiting for technology ecosystems to fully mature before creating regulatory frameworks.
African Union Continental Strategy for AI and the Nigerian Strategy
Bibitayo explains that the African Union’s Continental AI Strategy is rooted in responsible AI principles, with a strong focus on understanding and managing the risks associated with AI development and deployment. These include environmental risks; such as the land, energy, and water requirements needed to support large-scale data centers; as well as structural risks like bias and governance challenges. They note that Nigeria’s AI strategy reflects many of these same concerns, showing alignment between national and continental priorities.
Beyond risk management, the Bigitayo highlights the AU Strategy’s emphasis on practical AI adoption in key sectors, including healthcare, education, and public administration. He was particularly enthusiastic about the potential for AI in the public sector, where tools could improve transparency and efficiency. Drawing on a project he supervised during a 2024 summer school, where teams from Ghana and South Africa explored AI in public procurement as a tool to reduce corruption by minimizing human bias in contract award processes, though he acknowledged that AI bias remains a concern in such applications.
Future of Responsible and Inclusive Technology in Nigeria and Africa
Looking ahead, Bibitayo believes that the future of responsible and inclusive technology in Nigeria and across Africa depends on adopting a multidisciplinary approach to AI governance and innovation. Rather than viewing technology solely through a technical lens, he argues that policymakers, businesses, legal experts, healthcare professionals, ethicists, and other stakeholders must all have a seat at the table. Bringing together diverse perspectives will help ensure that AI systems are designed and deployed in ways that benefit society rather than serving only commercial interests.
He also emphasizes the importance of public participation in shaping the future of technology. Since it is not always practical to engage entire populations directly, civil society organizations play a critical role in representing public interests, advocating for accountability, and ensuring that citizens' voices are reflected in policy discussions. For Bibitayo, stronger collaboration across sectors and greater involvement from civil society will be key to building a more responsible, inclusive, and socially beneficial AI ecosystem over the next decade.
Technology That Excites and Technology That Worries
Bibitayo is most worried about the failure of technology platforms; including AI tools in education; to adequately consider and protect vulnerable groups, particularly children and the elderly. Many platforms prioritize profit over the safety of marginalized users. On the positive side, he is most excited about AI in healthcare. AI now enables people to access medical guidance remotely, and he cited an example of a person identifying an effective drug combination for a long-standing condition through AI prompting. He also described a Nigerian initiative combining AI and blockchain to create portable, continuous healthcare records accessible anywhere in the world.
AI in Healthcare: Adoption and Data Protection Implications
AI-driven healthcare is already happening in Nigeria. He described a specific organization that approached him to advise on a platform combining AI and blockchain to enable continuous, portable healthcare records accessible globally; a significant innovation. On the legal side, all data protection principles apply to AI and blockchain systems. Key unresolved legal questions include whether data can truly be deleted from AI systems, intellectual property rights over training data, and whether consent is required before using personal data to train AI models. Despite these gray areas, he advocates that privacy compliance remains non-negotiable in any AI or blockchain product.
Advice for AI Developers and Tech Policymakers
For developers, the advice is to build responsibly; not as a generic statement, but as a concrete commitment to embedding all responsible AI principles (as outlined by bodies such as the OECD) at every stage of development and deployment. Critically, responsibility does not end at deployment. Developers must continuously monitor and assess their systems post-launch, as AI can hallucinate or behave unexpectedly. Failure to do so risks legal liability. Ongoing monitoring, periodic assessment, and incident reporting mechanisms are essential components of responsible AI development.
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