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Eye for an AI: More-than-seeing, fauxtomation, and the enactment of uncertain data in digital pathology.
Carboni, Chiara; Wehrens, Rik; van der Veen, Romke; de Bont, Antoinette.
Afiliação
  • Carboni C; Erasmus University Rotterdam, Rotterdam, The Netherlands.
  • Wehrens R; Erasmus University Rotterdam, Rotterdam, The Netherlands.
  • van der Veen R; Erasmus University Rotterdam, Rotterdam, The Netherlands.
  • de Bont A; Tilburg University, Tilburg, The Netherlands.
Soc Stud Sci ; 53(5): 712-737, 2023 10.
Article em En | MEDLINE | ID: mdl-37154611
ABSTRACT
Artificial Intelligence (AI) tools are being developed to assist with increasingly complex diagnostic tasks in medicine. This produces epistemic disruption in diagnostic processes, even in the absence of AI itself, through the datafication and digitalization encouraged by the promissory discourses around AI. In this study of the digitization of an academic pathology department, we mobilize Barad's agential realist framework to examine these epistemic disruptions. Narratives and expectations around AI-assisted diagnostics-which are inextricable from material changes-enact specific types of organizational change, and produce epistemic objects that facilitate to the emergence of some epistemic practices and subjects, but hinder others. Agential realism allows us to simultaneously study epistemic, ethical, and ontological changes enacted through digitization efforts, while keeping a close eye on the attendant organizational changes. Based on ethnographic analysis of pathologists' changing work processes, we identify three different types of uncertainty produced by digitization sensorial, intra-active, and fauxtomated uncertainty. Sensorial and intra-active uncertainty stem from the ontological otherness of digital objects, materialized in their affordances, and result in digital slides' partial illegibility. Fauxtomated uncertainty stems from the quasi-automated digital slide-making, which complicates the question of responsibility for epistemic objects and related knowledge by marginalizing the human.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Inteligência Artificial / Conhecimento Tipo de estudo: Qualitative_research Limite: Humans Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Inteligência Artificial / Conhecimento Tipo de estudo: Qualitative_research Limite: Humans Idioma: En Ano de publicação: 2023 Tipo de documento: Article