Initial consumer resistance to autonomous medical artificial intelligence-based technologies: a health perspective

Résistance initiale du consommateur aux technologies autonomes de l’Intelligence Artificielle Médicale: une approche par les préoccupations liées à la santé

Zied Mani () and Inès Chouk ()
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Zied Mani: CEROS - Centre d'Etudes et de Recherches sur les Organisations et la Stratégie - UPN - Université Paris Nanterre, UPN - Université Paris Nanterre
Inès Chouk: CY - CY Cergy Paris Université

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Abstract: PurposeWhile the success of medical artificial intelligence (MAI) is dependent on understanding the mechanisms inhibiting its acceptability for potential users, relatively few studies have adopted a resistance-oriented perspective to understanding patient reaction to this technology. The aim of this study is to examine the impact of individual health concerns (1), healthcare technology concerns (2) and contextual factors (3) on initial consumer resistance to autonomous MAI based technologies. Methodology/approach Data were collected through an online questionnaire. A quantitative study was conducted with a representative sample of the French population (N= 245). Structural equation modeling was used for the analysis (AMOS). ResultsOur study proposed and validated a multi-level model of drivers of resistance to autonomous MAI-based technologies. The findings show that initial resistance to autonomous medical artificial intelligence is impacted by: perceived MAI health risk, perceived neglect of patient uniqueness and perceived liability issues. Moreover, our results highlight the role of structural assurances in alleviating consumer resistance to autonomous MAI based technologies. Practice implications -The development of MAI technologies should be based on a collaborative R&D model that incorporates all relevant stakeholders: medical personnel, developers, institutional actors, patients, etc.-Organizations providing AI-based technologies for consultations should display 'labels' to ensure the ethical and responsible utilization of these technologies for patients.-Manufacturers of AI-based technologies can develop offers combining MAI-based technologies with other tools collecting data on patients (AI health applications, IoT devices, etc.) OriginalityThe originality of this research is threefold:(1) Studying the initial reaction of consumers to a technological innovation in the acceptability stage.(2) Developing and testing a comprehensive multi-level model of drivers of consumer resistance from a health perspective (3) Identifying a new type of resistance factors to technological innovation: factors related to the organizational and the regulatory context.

Keywords: patient uniqueness; liability; structural assurances; medical artificial intelligence; innovation; Resistance; Resistance innovation medical artificial intelligence structural assurances patient uniqueness liability (search for similar items in EconPapers)
Date: 2023-10-01
Note: View the original document on HAL open archive server: https://hal.science/hal-05781830v1
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Published in Décisions Marketing, 2023, 112 (4), pp.7-26

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