Algorithmic emergence? Epistemic in/justice in AI-directed transformations of healthcare

Abstract

Moves toward integration of Artificial Intelligence (AI), particularly deep learning and generative AI-based technologies, into the domains of healthcare and public health have recently intensified, with a growing body of literature tackling the ethico-political implications of this. This paper considers the interwoven epistemic, sociopolitical and technical ramifications of healthcare-AI entanglements, examining how AI materialities shape emergence of particular modes of healthcare organization, governance and roles, and reflecting on how to embed participatory engagement within these entanglements. We discuss the implications of socio-technical entanglements between AI and Evidence-Based Medicine (EBM) for equitable development and governance of health AI. AI applications invariably center on the domains of medical knowledge and practice that are amenable to computational workings. This, in turn, intensifies the prioritization of these medical domains and furthers the assumptions which support the development of AI, a move which decontextualizes the qualitative nuances and complexities of healthcare while simultaneously advancing infrastructure to support these medical domains. We sketch the material and ideological reconfiguration of healthcare which is being shaped by the move toward embedding health AI assemblages in real-world contexts. We then consider the implications of this, how AI might be best employed in healthcare, and how to tackle the algorithmic injustices which become reproduced within health AI assemblages.