How do the uses of Artificial Intelligence tools increase the radiologists’ abilities?

Comment les usages des outils d’Intelligence Artificielle augmentent-ils la capacité d’agir des radiologues ?

Joël Perez-Torrents () and E. Minvielle ()
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Joël Perez-Torrents: CRG I3 - Centre de recherche en gestion I3 - X - École polytechnique - IP Paris - Institut Polytechnique de Paris - I3 - Institut interdisciplinaire de l’innovation - CNRS - Centre National de la Recherche Scientifique
E. Minvielle: CRG I3 - Centre de recherche en gestion I3 - X - École polytechnique - IP Paris - Institut Polytechnique de Paris - I3 - Institut interdisciplinaire de l’innovation - CNRS - Centre National de la Recherche Scientifique

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Abstract: The increasing use of Artificial Intelligence (AI) tools in healthcare, especially in radiology, raises pivotal questions about enhancing the skills of highly specialized professionals. Our study delves into two theoretical frameworks: "interrogation practices" and the conformation/exploration model. Drawing from 81 hours of observation (utilizing the shadowing method) and 9 interviews conducted in two healthcare facilities using AI tools for breast cancer diagnosis, we find that the collaboration between radiologists and AI tools primarily reinforces their existing capabilities (conformation) rather than fostering new ones (exploration). These findings underscore the necessity for an enhanced dialogue between AI tool designers and domain experts to promote exploration-oriented interrogation practices, thereby increasing professional capabilities.

Keywords: radiology; diagnostic assistance; artificial intelligence; human-machine collaboration; managing AI opacity; interrogation practices; conformation and exploration; skill augmentation; radiologie; aide au diagnostic; intelligence artificielle; collaboration homme-machine; gestion de l'opacité de l'IA; pratiques interrogatives; conformation et exploration; augmentation des capacités (search for similar items in EconPapers)
Date: 2023
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Published in Journal de gestion et d'économie de la santé, 2023, 3 (3), pp.185-203. ⟨10.54695/jdds.041.3.0185⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-04527369

DOI: 10.54695/jdds.041.3.0185

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