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How Do We Know if an AI System Is Safe, Fair, Reliable, and Trustworthy?
One of the most consequential questions in technology governance today is also one of the most underexamined: how do we establish, and sustain, meaningful trust in automated decision-making systems, particularly when those systems affect the most fundamental aspects of people’s lives? In other words, how do we know if an AI System Is safe, fair,…
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Why High-Risk AI in Employment Demands More Than Ethics Statements
Artificial intelligence is no longer sitting at the edges of human resources as an experimental productivity tool. It is increasingly being used to influence who gets hired, who gets promoted, who is flagged as a performance concern, and in some cases, who is pushed out of the workforce. That reality is forcing regulators around the…
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From Stress Tests to Global Standards: How the Bank of England Is Shaping AI Risk Oversight Worldwide
When financial regulators begin stress-testing a technology, they are sending a signal of preparedness. That is precisely what happened when the Bank of England announced that it was running scenario simulations to assess how artificial intelligence could affect financial stability. The exercise examines a simple but consequential question: What happens when many institutions rely on…
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From Harm to Accountability: What Recent Global Litigation Reveals about Digital Safety Enforcement
Why documented harm alone does not produce accountability, and what institutions must build to translate incidents into protection for children online. Design Is Global. Liability Is Evidentiary. Social media platforms operate on largely uniform technical architectures across the world. Features such as infinite scrolling, algorithmic recommendations, and autoplay video are not localized technologies; they are…
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The Illusion of Safe EdTech: PowerSchool and the Global Risks to Student Data
As AI‑enabled tools are woven into educational systems in Africa and the broader Global South, they are plugging into environments where data protection laws may be nascent or weakly enforced, procurement rarely interrogates security design, and institutions have limited capacity to audit vendors’ technical claims. The potential harm is not hypothetical: once student data is…
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From Storms to Signals: Co-Designing AI-Powered Maritime Safety with Ghana’s Fishermen
In many coastal communities, small-scale fishing fleets operate outside major shipping and offshore networks. The Center for Law and Innovation Policy (CLIP) and the Institute for AI Policy and Governance (AIPG) have spent recent weeks in conversations with artisanal fishermen in Jamestown and Chorkor, not to pitch solutions, but to listen and gather insights for…
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Who Pays, Who Protects, Who Controls? Why AI skilling Requires More Than Access
AI skilling has become Africa’s new promise. From Nairobi to Lagos, Accra to Johannesburg, multinational technology companies are rolling out ambitious programs: free AI tools for students, cloud credits for universities, certification pathways for the workforce. The narrative is compelling, democratizing access to cutting-edge technology, but beneath the glossy presentations and partnership announcements lie questions…
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Google Withdraws Appeal in Uganda Data Protection Case — A Defining Moment for Big Tech Accountability in Africa
The Institute for AI Policy and Governance (AIPG) welcomes a major development in digital governance on the African continent. An official communication from the Republic of Uganda’s Ministry of ICT and National Guidance, dated 24 November 2025, confirms that Google LLC has formally withdrawn its appeal in the landmark matter of Ssekamwa Frank & 3…
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Knowing Before Governing: Why Africa Needs an AI Tools and Risk Registry
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,…
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AI Ethics Beyond Bias: Why Carbon Footprints Matter
The global race to develop ever-larger models is intensifying, but seldom do we ask: Who pays the price when AI’s hunger for electricity and water drains resources from citizens whose basic needs remain unmet? At AIPG, we believe that true responsibility begins with acknowledging AI’s environmental costs. The call to action is clear: Let’s bake…