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Across a four-part virtual discussion series convened by the Harvard Global Health Institute (HGHI) in partnership with the Center for Bioethics at Harvard Medical School this spring, experts from academia, multilateral organizations, government, philanthropy and civil society examined the opportunities, challenges and key questions shaping AI’s role in global health. Together, the discussions revealed that AI’s impact will not be determined by technological capability alone, but by the interconnected systems of governance, research and implementation that shape how these tools are developed, deployed and sustained.
“We must break the cycle of a lack of accountability and find the right balance between the speed of AI adoption and the rigor needed to ensure these technologies are safe, effective, and responsive to the communities they are intended to serve,” said Louise Ivers, HGHI faculty director. Through these focused discussions on governance, partnerships, evaluation, and implementation, speakers examined what this balance requires in practice.
When governance trails technological change
AI governance is being actively negotiated through national strategies, institutional guidelines and global frameworks, reflecting the imperative for questions of accountability to evolve alongside technological development. Yet, as the discussions in this series highlighted, governance often remains reactive, attempting to establish boundaries for AI systems already being deployed rather than shaping how they are developed from the outset. The central challenge is not only defining responsible AI principles, but ensuring they translate into locally relevant approaches, strengthen countries’ capacity to govern emerging technologies, and advance equity rather than deepen existing divides.
The UNESCO Recommendation on the Ethics of Artificial Intelligence, adopted in 2021, calls for AI systems to be developed and used in ways grounded in human rights, transparency, fairness, and human oversight. But translating principles into practice requires more than shared values; it requires the institutional capacity and local expertise to shape how AI is developed and applied.
Gabriela Ramos, assistant director-general for the Social and Human Sciences Sector at UNESCO, emphasized that this means ensuring countries are not simply recipients of AI technologies, but active participants in shaping them.
“One of the things that I feel is important is getting the conversation back to the realities of the Global South, to the very specific needs of each single country, and then defining what kind of capacities they want to bring up to better understand the technologies and to shape them.”
Power, partnerships and the politics of deployment
Governments, philanthropies, academic institutions, technology companies and local actors are increasingly collaborating to deploy AI in health. Yet, as discussions throughout the series highlighted, these partnerships are far from neutral exchanges of technology; rather, they are shaped by questions of power, ownership, and decision-making. Model development remains concentrated in a small number of high-income countries, while many deployment settings risk being positioned not as co-creators, but primarily as markets for consumption and testing.
These dynamics raise fundamental questions about who defines problems, whose expertise informs design decisions, and who has influence over how AI systems are deployed, evaluated, and governed. Without deliberate attention to these power structures, AI risks reinforcing existing inequities under the guise of technological neutrality.
Emerging approaches from the Global South offer alternative models of engagement. Esther Kunda, director general of Innovation & Emerging Technologies at Rwanda’s Ministry of Information Communication Technology (ICT) and Innovation, discussed Rwanda’s approach to AI governance and partnerships, including efforts to align emerging technologies with national priorities through the country’s national AI policy. Rwanda’s experience highlights a broader shift away from viewing countries primarily as adopters of externally developed technologies and toward strengthening local capacity and agency to shape how AI is developed and deployed on their own terms.
Chinasa T. Okolo, founder and scientific director of Technecultura and an AI governance researcher, argued that optimism about AI must be grounded in realism. Local ecosystems across the Global South must be strengthened rather than made dependent on external technology providers, and investment in AI should not come at the expense of hospitals, supply chains and health workforces — the foundations of resilient health systems.
