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

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.

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Publication Details

Journal
Sociology of Health & Illness
Published
2026-01-29
DOI
https://doi.org/10.1111/1467-9566.70150
Primary Topic
Ethics and Social Impacts of AI
Type
article
Field-Weighted Citation Impact
0.00

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article

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

Susi. Geiger, Nicole Gross
Sociology of Health & Illness
Ethics and Social Impacts of AI
article

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

Susi. Geiger, Nicole Gross
article en

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.

Sociology of Health & IllnessVol. 48(2)
University College Dublin (IE), National College of Ireland (IE)
Irish Research Council
Openalex Percentile: Top 74%
Ethics and Social Impacts of AI
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