Trust in an autonomous agent for predictive maintenance: how agent transparency could impact compliance

Loïck Simon (), Philippe Rauffet (), Clément Guérin () and Cédric Seguin ()
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Loïck Simon: Lab-STICC_FHOOX - Equipe Human and Organizational Factors and autOmatic in compleX systems - Lab-STICC - Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance - ENIB - École Nationale d'Ingénieurs de Brest - UBS - Université de Bretagne Sud - UBO - Université de Brest - ENSTA Bretagne - École Nationale Supérieure de Techniques Avancées Bretagne - IMT - Institut Mines-Télécom [Paris] - CNRS - Centre National de la Recherche Scientifique - UBL - Université Bretagne Loire - IMT Atlantique - IMT Atlantique - IMT - Institut Mines-Télécom [Paris], UBS - Université de Bretagne Sud
Philippe Rauffet: Lab-STICC_FHOOX - Equipe Human and Organizational Factors and autOmatic in compleX systems - Lab-STICC - Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance - ENIB - École Nationale d'Ingénieurs de Brest - UBS - Université de Bretagne Sud - UBO - Université de Brest - ENSTA Bretagne - École Nationale Supérieure de Techniques Avancées Bretagne - IMT - Institut Mines-Télécom [Paris] - CNRS - Centre National de la Recherche Scientifique - UBL - Université Bretagne Loire - IMT Atlantique - IMT Atlantique - IMT - Institut Mines-Télécom [Paris]
Clément Guérin: Lab-STICC_FHOOX - Equipe Human and Organizational Factors and autOmatic in compleX systems - Lab-STICC - Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance - ENIB - École Nationale d'Ingénieurs de Brest - UBS - Université de Bretagne Sud - UBO - Université de Brest - ENSTA Bretagne - École Nationale Supérieure de Techniques Avancées Bretagne - IMT - Institut Mines-Télécom [Paris] - CNRS - Centre National de la Recherche Scientifique - UBL - Université Bretagne Loire - IMT Atlantique - IMT Atlantique - IMT - Institut Mines-Télécom [Paris]
Cédric Seguin: Lab-STICC_SHAKER - Equipe Software/HArdware and unKnown Environment inteRactions - Lab-STICC - Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance - ENIB - École Nationale d'Ingénieurs de Brest - UBS - Université de Bretagne Sud - UBO - Université de Brest - ENSTA Bretagne - École Nationale Supérieure de Techniques Avancées Bretagne - IMT - Institut Mines-Télécom [Paris] - CNRS - Centre National de la Recherche Scientifique - UBL - Université Bretagne Loire - IMT Atlantique - IMT Atlantique - IMT - Institut Mines-Télécom [Paris], UBS - Université de Bretagne Sud

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Abstract: Human-machine cooperation is more and more present in the industry. Machines will be sources of proposal by giving human propositions and advice. Humans will need to make a decision (comply, i.e., agree, or not) with those propositions. Compliance can be seen as an objective trust and experiments results unclear about the role of risk in this compliance. We wanted to understand how transparency on reliability, risk or those two in addition will impact this compliance with machine propositions. With the use of an AI for predictive maintenance, we asked participants to make a decision about a proposition of replanification. Preliminary results show that transparency on risk and total transparency are linked with less compliance with the AI. We can see that risk transparency has more effect on creating an appropriate trust than reliability transparency. As we see, and in agreement with recent studies, there is a need to understand at a finer level the impact of transparency on human-machines interaction

Keywords: Transparency; Human-machine interaction; Compliance; Trust (search for similar items in EconPapers)
Date: 2022-07-24
New Economics Papers: this item is included in nep-big and nep-exp
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Published in 13th AHFE Conference (Applied Human Factors and Ergonomics) 2022, Jul 2022, New York, United States. ⟨10.54941/ahfe1001602⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-03536524

DOI: 10.54941/ahfe1001602

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