At the Crossroads of Data Justice and Data Capitalism: How Generative AI in Healthcare Mobilises Its Assemblages

ABSTRACT Algorithmic technologies such as machine learning, generative artificial intelligence (GenAI) and automated decision‐making have become one of the frontiers of contemporary technoscientific innovation in healthcare. However, algorithmic technologies can never be seen in isolation from the networks in which they are embedded. Not only are they woven into situated sociotechnical assemblages of human and nonhuman entities—tools, objects and other technologies—but their entanglements also reach into regulatory institutions and markets. This paper conceptualises GenAI in healthcare ‘in the making’ at the rapidly changing intersection of three spheres: regulatory, market and healthcare delivery. Our study, conducted in conjunction with two nongovernmental social justice organisations, explores how this intersection is currently ‘motored’ by data justice concerns on the one hand and data capitalist objectives on the other. We draw health sociologists' attention to the technopolitics and market interests that lie behind AI promissories and implementations in healthcare. More importantly, we contribute to collective thinking around how we may steer this dynamic towards the empowerment of civic society, dynamic regulation and a push for public value—rather than enrichment of the few.