Institute for AI Policy & Governance

Introduction

Across Africa, Artificial Intelligence (AI) is rapidly transforming governance, business, and social systems. From predictive analytics in health surveillance to chatbots in financial inclusion, algorithmic systems are increasingly mediating decisions that affect millions of citizens. Yet, despite this accelerating adoption, few governments or institutions can answer the fundamental question: what AI systems are in use, and what risks do they pose?

This absence of visibility is not merely administrative; it represents a profound gap in governance. The principle is straightforward: one cannot govern what one does not know. Without an inventory of deployed systems, oversight becomes impossible, accountability remains fragmented, and regulatory efforts largely performative. As AI becomes a critical component of Africa’s digital public infrastructure, this invisibility undermines both state capacity and public trust.

The Global Algorithmic Transparency Divide At least eleven countries, Argentina, Brazil, Canada, France, India, Mexico, the Netherlands, New Zealand, the United Kingdom, the United States, and several regional blocs including the European Union, maintain active algorithmic or AI repositories. These registries enable governments to monitor the deployment of algorithmic decision-making tools across public and private domains. In contrast, none of Africa’s fifty-four nations currently operates a public algorithmic transparency registry, although the African Union has explicitly identified this gap in its Continental AI Strategy (2024–2030.

The result is a widening algorithmic transparency divide between Africa and other regions. Transparency has become an essential component of trustworthy AI governance, yet Africa remains without the infrastructure to achieve it. This disparity also limits Africa’s influence in global governance forums that increasingly rely on demonstrable compliance with transparency and audit standards.

Notable Global Examples

• European Union: The EU AI Act mandates that all high-risk AI systems be registered in a public database prior to deployment, institutionalizing transparency as a regulatory principle.
• China: Operates a national registry that regulates algorithms driving major internet platforms, reflecting Asia’s assertive model of state-led algorithmic governance.
• City-Level Innovation: Helsinki and Amsterdam launched the first municipal AI registers in 2020, followed by similar initiatives in Barcelona, Brussels, Eindhoven, Mannheim, Rotterdam, and Sofia.
• Regional Case Studies: Chile’s Public Algorithm Repository , the EU, and the United Kingdom’s Algorithmic Transparency Records offer instructive examples of algorithmic registries implemented to enhance accountability and auditability in the public sector.

Africa’s Emerging Foundations

While no African nation currently maintains an operational registry, several developments suggest growing momentum.

• The African Union has encouraged member states to establish national AI or algorithmic transparency registers.
• The Continental AI Strategy provides a framework for harmonized governance.
• The African AI Policy Repository and the interactive Africa AI Policy tool which aggregate national policy and regulatory documents.
• The “Made in Africa” Open Code Repository promotes local innovation, albeit without serving the governance functions of a public sector algorithm register.

These efforts represent early but significant steps toward a more coherent governance framework. The challenge is to convert policy aspiration into operational capability.

The Governance Gap in AI Oversight

Most African governments have adopted or are drafting national AI strategies emphasizing fairness, privacy, and accountability. However, these frameworks largely remain declarative rather than operational. They articulate ethical principles but rarely specify how to identify, register, or monitor algorithmic systems in practice.

Procurement contracts often fail to include clauses ensuring access to model documentation, training data, or algorithmic logic. Ministries and agencies act independently, producing fragmented oversight regimes. The outcome is a patchwork of AI deployments without coordination or continuity, a situation reminiscent of earlier experiences with donor-funded ICT projects that created parallel systems rather than integrated infrastructure.

The establishment of an AI Tools and Risk Registry would help bridge this gap. Such a registry would:

1. Catalogue AI systems across sectors and jurisdictions.
2. Classify them by function, application domain, and risk level.
3. Enable regulators to prioritize oversight for high-risk uses, such as credit scoring, biometric surveillance, and predictive policing.
4. Create a baseline for accountability and evidence-based policymaking.

In effect, the registry would transform AI governance from principle to practice, shifting from reactive oversight to proactive stewardship.

Visibility as a Governance Principle

Visibility must be understood as a governance value rather than a technical outcome. A continental registry would serve multiple strategic functions:

• Transparency: Providing public visibility into how and where algorithms are deployed.
• Accountability: Allowing oversight bodies and civil society to track the use of high-risk systems.
• Policy Coordination: Enabling cross-sector and cross-border harmonization.
• Risk Management: Informing impact assessments and mitigation planning.
• Capacity Development: Training public officials to recognize and document AI deployments.

Operationally, this framework would require collaboration among the African Union, sub-regional bodies such as ECOWAS and SADC, and national digital authorities. Interoperable data standards would allow comparative analytics and benchmarking across countries.

Lessons from Digital Infrastructure Governance

Africa’s experience with digital public infrastructure provides cautionary lessons. Many e-governance systems, ranging from health information platforms to revenue collection databases, were implemented through vendor-controlled contracts that limited state access to source code and data portability. These systems became indispensable yet ungovernable, locking states into cycles of technological dependency.

A similar pattern may emerge with AI unless visibility is embedded at the outset. Registries can act as preventive infrastructure, ensuring that algorithmic systems deployed by or for the state remain auditable, replaceable, and under sovereign control.

Toward a Continental Framework

Establishing an AI Tools and Risk Registry at the continental level would provide a shared foundation for national implementation. The registry could operate as a federated system, where member states maintain their own inventories linked through a continental hub managed by the AU’s Department of Infrastructure and Energy or a new AI Governance Coordination Unit.

Such a model would allow each state to tailor its data entries and classification protocols while ensuring comparability through standardized metadata. The registry could also serve as a research resource, enabling scholars and policymakers to track trends in AI adoption, assess compliance with ethical standards, and evaluate socio-technical impacts.

Conclusion: Seeing Is Governing

Africa stands at a pivotal moment in its digital transformation. The question is no longer whether AI will shape governance and society, but how, and under whose terms. Without visibility, governance becomes reactive; without records, accountability is impossible.

A continental AI Tools and Risk Registry represents both a policy innovation and a sovereignty safeguard. It would anchor AI governance in knowledge rather than conjecture, ensuring that Africa’s digital evolution remains accountable to its people and responsive to its values.

Ultimately, the future of responsible AI governance begins with a simple truth: one cannot govern what one does not know.

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References

1. Leveraging Responsible, Explainable, and Local Artificial Intelligence Solutions for Clinical Public Health in the Global South (PMC, 2023).
2. Can Artificial Intelligence Revolutionize Healthcare in the Global South? A Scoping Review of Opportunities and Challenges (PMC, 2023).
3. Optimizing Human-Centered AI for Healthcare in the Global South (PMC, 2024).
4. A Global Perspective on Data Powering Responsible AI Solutions in Health Applications (PMC, 2024).
5. African Union Commission (2024). Continental Artificial Intelligence Strategy for Africa (2024–2030).
6. European Union (2024). Artificial Intelligence Act (EU Regulation 2024/1686).
7. https://github.com/collections/made-in-africa
8. Algorithmic Transparency in the Public Sector, Case studies of repositories of public  algorithms in Chile, the EU and the UKhttps://wp.oecd.ai/app/uploads/2024/12/15-Algorithmic-Transparency-in-the-Public-Sector-Case-studies-of-repositories-of-public-algorithms-in-Chile-the-EU-and-the-UK.pdf
9. AU Continental AI Strategy (2024–2030).
10. The African Union’s Continental AI Strategy: Data Protection and Governance Laws Set to Play a Key Role in AI Regulation, By Chuma Akana, Former FPF Global Privacy Summer Fellow and Mercy King’ori, FPF Policy Analyst, Global Privacy The African Union’s Continental AI Strategy: Data Protection and Governance Laws Set to Play a Key Role in AI Regulation – Future of Privacy Forum