The United Nations has taken a decisive step in global AI governance with the announcement of the Independent International Scientific Panel on Artificial Intelligence. This move marks a clear transition from years of discussion on AI ethics toward the creation of a formal, science-led oversight body, comparable in structure and intent to the Intergovernmental Panel on Climate Change.
Beyond its mandate, the composition of the Panel tells a deeper story about how global AI governance is being shaped, not only by who is included, but also by who is absent.
From Ethics Conversations to Scientific Authority
The primary role of the Panel is to bridge a widening gap between rapid technological advancement and slow-moving international policy. Its mandate is to provide independent, evidence-based assessments of the opportunities, risks, and societal impacts of AI.
These assessments are intended to serve as a shared factual foundation for the UN General Assembly as it considers future international instruments on AI, including resolutions, treaties, or global norms. Crucially, the Panel does not regulate. Instead, it defines the scientific consensus upon which regulation can be built, while ensuring alignment with human rights and the Sustainable Development Goals.
This shift reflects a growing recognition that effective AI governance must be grounded in science, not political positioning.
Representation as a Governance Strategy
The Panel brings together 40 experts from across the world, deliberately spanning multiple disciplines, regions, and professional backgrounds. Geographic diversity is a defining feature, with representation from every continent and meaningful inclusion of voices from the Global South, including Ethiopia, Senegal, Brazil, and Saint Kitts and Nevis.
Equally important is the balance between technical expertise and social impact perspectives. The Panel includes leading researchers, policy thinkers, and public intellectuals whose work intersects with democracy, human rights, and societal resilience. This design reduces the risk of AI governance being shaped solely by engineering priorities or commercial incentives.
Notable figures such as Yoshua Bengio, a Turing Award winner and prominent advocate for AI safety, Maria Ressa, a Nobel Peace Prize laureate known for her work on technology and democracy, and Bernhard Schölkopf, a global authority in machine learning and causal inference, signal the seriousness of the Panel’s ambitions.
The Countries You Might Expect, but Do Not See
Despite its diversity, the Panel’s composition reveals several notable absences that are unlikely to be accidental.
The United States and China, the two most powerful AI actors globally, are not represented. Their absence appears intentional and strategic. Including them at this stage could risk politicizing the scientific process or allowing geopolitical rivalry to overshadow evidence-based consensus. Both countries retain significant influence through industry leadership, bilateral diplomacy, and domestic regulation, even without seats on the Panel.
The absence of the United Kingdom is also striking, particularly given its strong AI research ecosystem and its leadership in recent global AI safety initiatives. Similarly, India, which positions itself as a bridge between the Global North and South and champions digital public infrastructure at scale, is missing from the list.
Advanced AI economies such as Japan and South Korea are also absent, despite their significant contributions to robotics, applied AI, and global technology supply chains.
These omissions suggest that the Panel is not designed to reflect industrial dominance. Instead, it prioritizes neutrality, legitimacy, and scientific trust over geopolitical or economic power.
Agenda Setting, Not Enforcement
The UN AI Scientific Panel should be understood as an agenda-setting body. Its influence lies in shaping how AI risks and opportunities are framed, measured, and discussed at the global level. By defining what is scientifically credible, the Panel indirectly shapes what becomes politically possible.
This approach mirrors lessons from climate governance, where scientific consensus created by the IPCC eventually translated into international agreements, national policies, and market shifts, even among states that were initially resistant.
Why This Matters for Africa
For Africa and other regions in the Global South, the structure of this Panel creates a rare strategic opening. The absence of dominant AI superpowers reduces the risk of agenda capture and allows space for contextual realities to be meaningfully considered.
Issues such as data extractivism, infrastructure constraints, labor displacement, surveillance risks, and unequal value distribution from AI systems are more likely to be taken seriously within a forum that values lived impact alongside technical innovation.
At Data Governance Africa, we view this moment as a reminder that global AI governance is being shaped now, often quietly, and largely through scientific framing rather than legislation. Participation, vigilance, and sustained engagement will determine whether Africa helps define the rules of the AI era or merely adapts to them after the fact.
The future of AI governance will belong to those who show up early, informed, and prepared to shape consensus.