Dear colleagues, The Flashlab seminar’s quarterly cycle "Contemporary Challenges of Artificial Intelligence" third and final session will take place on* Monday, June 2 (4pm-5:30pm CET),* online and at Sciences Po Paris (1 place St-Thomas d'Aquin, Paris). We are pleased to welcome *Dieuwertje Luitse*, PhD student at the University of Amsterdam and co-organizer of the "*Critical AI Seminar* <https://www.create.humanities.uva.nl/seminar-series/the-critical-ai-seminar-series-returns/>", for a presentation entitled: *Rethinking Data Bodies: On the Technopolitical Production of ‘Otherness’ through ML Modelling and Evaluation in Medicine * *Abstract: *Following the rapid development of AI technologies in the medical domain, the amplification of bias and the potential reproduction of existing social or health inequities have become a central object of concern in the field (Seyyed-Kalantari et al., 2021; Lee et al., 2023). To mitigate these issues, critical work on the ethics and politics of medical AI has primarily focused on scrutinising the construction of (very) large datasets used to train and evaluate machine-learning systems for medical AI research and development or clinical deployment. Even though this type of critical work in AI ethics is vital, I stress that this particular focus on data and data practices risks obscuring the many additional factors at play here. Instead, AI-inscribed bias and health inequalities may emerge through ‘small differences’ in a series of entangled processes that underpin medical AI decision-making: machine-learning modelling and specific modes of evaluation. It is critical to further investigate these processes, and the underlying practices that feed into them, as they allow to better understand and deepen the ethico-political scrutiny of technical operations by machine-learning systems beyond just data production. Following these observations, this talk takes a combined Critical AI and STS research approach to demonstrate how data, machine-learning modelling and evaluation processes are continuously composing and recomposing categories of ‘others’ on which AI-based medical decisions can be made—including those that may lead to the (re)productions of social biases and health inequities. To do so, I propose to conceptually rethink the construction of ‘data bodies’ as technopolitical enactments of constituted medical datasets, machine-learning models and their underlying infrastructures for AI-based medical decision-making. Drawing on the notion of the ‘body multiple’ (Mol, 2002) data bodies are constituted and always ‘oscillate between multiplicity and singularity’ (Bucher, 2018). Exploring their enactment, I address the configurations of the lines between self and various others from within the entangled technical arrangements and sociotechnical practices underlying machine-learning operations in the medical realm and consider their implications for decision-making in practice. *Bio: **Dieuwertje Luitse is PhD Candidate in the Department of Media Studies at the University of Amsterdam (UvA). Her research explores the ethics, politics and power of data, artificial intelligence (AI) system and application development in healthcare. This project is part of the UvA’s interdisciplinary research priority area on AI for Health decision-making <https://www.uva.nl/en/shared-content/zwaartepunten/en/artificial-intelligence-for-health-decision-making/artificial-intelligence-for-health-decision-making.html> that brings together researchers from Computer Science, Medicine, Law and the Humanities. In addition, her research interest focuses on the study of computational infrastructures and the (historical) development of AI systems in relation to their socio-economic and political implications.In line with her research activities, Dieuwertje is the co-organiser of the Critical AI Seminar Series <https://www.create.humanities.uva.nl/seminar-series/the-critical-ai-seminar-series-returns/> hosted by the Critical Data and AI research group at UvA’s Faculty of Humanities and one of the co-editors of the topical collection on the Politics of Machine Learning Evaluation <https://link.springer.com/collections/bbbehaibcj> in *Digital Society. --- To get this session’s link, please sign up at this link <https://framalistes.org/sympa/subscribe/flashlab> or get in touch via email. The full program is available on the seminar’s *site* <https://flashlabinfo.wordpress.com/>. --- For those interested, a session of the medialab seminar will also be held on the following day, *Tuesday 3 June* *(2-4pm)* – during which* Dieuwertje Luitse *et *Anna Schjøtt Hansen *will introduce a special issue they co-edited for *Digital Society* on the *"Politics of Machine Learning Evaluation"*, with a collective discussion with some of the contributors. All information is available on the* medialab * <https://medialab.sciencespo.fr/en/news/the-politics-of-machine-learning-evaluation-from-present-to-future/> website. Kind wishes, Valentin Goujon & Assia Wirth ----------- *Assia Wirth* PhD candidate - ENS Paris Saclay (IDHES)