Trust, mistrust, and the promise of AI in genomics for African populations.

Abstract

Artificial intelligence (AI) is rapidly reshaping genomic medicine, yet its benefits remain unevenly distributed due to the profound under-representation of African populations in genomic datasets and persistent legacies of mistrust. These structural gaps undermine model validity, amplify bias, and limit clinical utility across the world's most genetically diverse populations. Building trustworthy AI for genomics in African populations requires transparent and interpretable systems, equitable data generation led by African institutions, culturally grounded governance, and rigorous population-specific validation. Advancing these principles is essential to ensure that AI reduces, rather than reinforces, global genomic inequities.