This paper provides a comprehensive examination of the ethical governance landscape for data science health research in Nigeria, serving as a representative case study for understanding challenges faced across the African continent.

We identified how data science methods applied to health research can exacerbate pre-existing ethical dilemmas while generating novel challenges specific to the African context. These include issues related to informed consent in pervasive data environments, the complexity of secondary data use, reidentification risks despite anonymization efforts, power imbalances between international and local researchers, algorithmic bias resulting from lack of diversity in training data, and regulatory gaps in cross-border research collaborations. It further argues that Nigeria’s experience exemplifies the broader tensions facing many African low- and middle-income countries as they attempt to balance the promotion of data science innovation with the protection of research participants and communities. Hence, there is an urgent need for novel ethical frameworks that address blurred consent boundaries, ensure equitable benefit-sharing, and prevent commercial exploitation while promoting meaningful local participation in global data science initiatives.