AI holds great promise to transform healthcare, especially for currently underserved people. But a substantial barrier to this opportunity is a disconnect between AI developers and clinical realities: To deploy successfully, AI development must be shaped at every stage by the specifics of the local deployment context. However, because this complex shaping task sits outside the traditional algorithm-centric focus of AI, it is poorly understood. This paper describes little-discussed but crucial aspects of an algorithm’s path to deployment, each directly relevant to AI researchers and illustrated by concrete examples drawn from our experiences in the African healthcare context.

A local copy is here.