Wang, Weisha, Wang, Yichuan, Chen, Long, Ma, Rui and Zhang, Minhao (2024) Justice at the forefront: cultivating felt accountability towards Artificial Intelligence among healthcare professionals. Social Science and Medicine, 347:116717. pp. 1-11. ISSN 0277-9536 (Print), 1873-5347 (Online) (doi:https://doi.org/10.1016/j.socscimed.2024.116717)

Preview

PDF (VoR) 46500_MA_Justice_at_the_forefront_Cultivating_felt_accountability_towards_Artificial_Intelligence.pdf - Published Version Available under License Creative Commons Attribution. Download (2MB) | Preview

Abstract

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.

Item Type:	Article
Uncontrolled Keywords:	felt accountability; Artificial Intelligence (AI); ethical principles; trusting belief in AI; fsQCA; healthcare
Subjects:	B Philosophy. Psychology. Religion > BJ Ethics H Social Sciences > H Social Sciences (General) H Social Sciences > HD Industries. Land use. Labor > HD28 Management. Industrial Management
Faculty / School / Research Centre / Research Group:	Faculty of Business
Last Modified:	28 Mar 2024 09:42
URI:	http://gala.gre.ac.uk/id/eprint/46500

Actions (login required)

View Item

Downloads