Justice at the Forefront : Cultivating felt accountability towards Artificial Intelligence among healthcare professionals
Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved..
The advent of AI has ushered in a new era of patient care, but with it emerges a contentious debate surrounding accountability for algorithmic medical decisions. Within this discourse, a spectrum of views prevails, ranging from placing accountability on AI solution providers to laying it squarely on the shoulders of healthcare professionals. In response to this debate, this study, grounded in the mutualistic partner choice (MPC) model of the evolution of morality, seeks to establish a configurational framework for cultivating felt accountability towards AI among healthcare professionals. This framework underscores two pivotal conditions: AI ethics enactment and trusting belief in AI and considers the influence of organizational complexity in the implementation of this framework. Drawing on Fuzzy-set Qualitative Comparative Analysis (fsQCA) of a sample of 401 healthcare professionals, this study reveals that a) focusing justice and autonomy in AI ethics enactment along with building trusting belief in AI reliability and functionality reinforces healthcare professionals' sense of felt accountability towards AI, b) fostering felt accountability towards AI necessitates ensuring the establishment of trust in its functionality for high complexity hospitals, and c) prioritizing justice in AI ethics enactment and trust in AI reliability is essential for low complexity hospitals.
Medienart: |
E-Artikel |
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Erscheinungsjahr: |
2024 |
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Erschienen: |
2024 |
Enthalten in: |
Zur Gesamtaufnahme - volume:347 |
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Enthalten in: |
Social science & medicine (1982) - 347(2024) vom: 05. Apr., Seite 116717 |
Sprache: |
Englisch |
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Beteiligte Personen: |
Wang, Weisha [VerfasserIn] |
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Links: |
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Themen: |
Artificial Intelligence (AI) |
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Anmerkungen: |
Date Completed 22.04.2024 Date Revised 22.04.2024 published: Print-Electronic Citation Status MEDLINE |
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doi: |
10.1016/j.socscimed.2024.116717 |
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funding: |
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PPN (Katalog-ID): |
NLM370080513 |
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