Over the last years, the intrusion of AI technologies and data-driven decision-making in the healthcare sector has contributed to the expansion of the health and well-being “data-market”.In particular, the data collection by platforms and self-tracking apps corresponds to the “personalised access” imperative and is fueled by the dominant understanding of data as the new oil.
Academic scholarship has scrutinized the extractivist material relationships the data-oil associations signify, whilst researchers and activists investigate alternative data-governance models, such as Public Data Trusts, Data cooperatives, and Data commons.
In this research project we argue that in order to persuasively defend any alternative data governance models, we first need to contribute toward a deeper understanding of how health data comes into value. To do so, we trace the flows of value(s) during the health data creation process. The preliminary findings of the first ethnographic study conducted in companies utilizing data-driven technologies for patient screenings, and for patients-to-clinical trial matchmaking, prove that health data has no intrinsic value. It is the diversity of practices, human labor and infrastructures, as socio-technical assemblages that bring health data into value.