Explicabilité et conditions d’appropriation de l’intelligence artificielle: une ressource au service du management ?

Yann Ferguson (), David Rodriguez (), Didier Chabanet () and Damien Richard ()
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Yann Ferguson: Mission IA - Inria Siège - Inria - Institut National de Recherche en Informatique et en Automatique, CERTOP - Centre d'Etude et de Recherche Travail Organisation Pouvoir - UT2J - Université Toulouse - Jean Jaurès - UT - Université de Toulouse - UT3 - Université Toulouse III - Paul Sabatier - UT - Université de Toulouse - CNRS - Centre National de la Recherche Scientifique
David Rodriguez: Institut Catholique d'Arts et Métiers (ICAM), CERTOP - Centre d'Etude et de Recherche Travail Organisation Pouvoir - UT2J - Université Toulouse - Jean Jaurès - UT - Université de Toulouse - UT3 - Université Toulouse III - Paul Sabatier - UT - Université de Toulouse - CNRS - Centre National de la Recherche Scientifique
Didier Chabanet: IDRAC Business school Lyon - Institut pour le Développement et la Recherche d'Action Commerciale - Université de Lyon, TRIANGLE - Triangle : action, discours, pensée politique et économique - ENS de Lyon - École normale supérieure de Lyon - Université de Lyon - UL2 - Université Lumière - Lyon 2 - IEP Lyon - Sciences Po Lyon - Institut d'études politiques de Lyon - Université de Lyon - UJM - Université Jean Monnet - Saint-Étienne - CNRS - Centre National de la Recherche Scientifique
Damien Richard: INSEEC - Institut des hautes études économiques et commerciales | School of Business and Economics

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Abstract: How can we explain and therefore encourage the appropriation of Artificial Intelligence (AI) in the workplace? This article sheds light on this question, based on the study of three use cases (process industry, banking industry and food industry), investigated via an AI at work observation platform, set up in 2020 as part of the Global Partnership on AI. The results show the importance of involving field workers and work collectives at all stages of project design, so that operators are never subservient to either the machine or the experts. The discussion highlights the importance of "situated explicability", discussion spaces and the decisive role of local managers in the construction of meaning so that AI is constantly anchored in real work.

Keywords: Artificial intelligence; machine learning; explicability; management; intelligence artificielle; explicabilité (search for similar items in EconPapers)
Date: 2024-07-03
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Published in Question(s) de Management, 2024, 2024/2 (49), pp.131-141. ⟨10.3917/qdm.229.0131⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-04650734

DOI: 10.3917/qdm.229.0131

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