Artificial intelligence for Africa: bridge or barrier for infectious disease control?

Abstract

•The promise of artificial intelligence (AI) for global health risks becoming a structural barrier in Africa if linguistic and cultural exclusions persist.•Dominant AI systems, trained on non-African languages, perform poorly in many local languages, widening health inequalities in infectious disease surveillance and control.•Locally developed, language-specific AI tools demonstrate superior performance in health communication compared with imported, non-contextualized models.•Creating effective AI for health in Africa requires investment in local data ecosystems, digital infrastructure, and participatory, epistemically just design.•Africa's linguistic diversity represents a strategic opportunity for innovation in cross-border disease surveillance and South-South technological collaboration.

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