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Influences on User Trust in Healthcare Artificial Intelligence: A Systematic Review

Jermutus, Eva; Kneale, Dylan; Thomas, James; Michie, Susan; (2022) Influences on User Trust in Healthcare Artificial Intelligence: A Systematic Review. Wellcome Open Research , 7 , Article 65. 10.12688/wellcomeopenres.17550.1. Green open access

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Abstract

BACKGROUND: Artificial Intelligence (AI) is becoming increasingly prominent in domains such as healthcare. It is argued to be transformative through altering the way in which healthcare data is used. The realisation and success of AI depend heavily on people’s trust in its applications. Yet, influences on trust in healthcare AI (HAI) applications so far have been underexplored. The objective of this study was to identify aspects related to users, AI applications and the wider context influencing trust in HAI. METHODS: We performed a systematic review to map out influences on user trust in HAI. To identify relevant studies, we searched seven electronic databases in November 2019 (ACM digital library, IEEE Explore, NHS Evidence, ProQuest Dissertations & Thesis Global, PsycINFO, PubMed, Web of Science Core Collection). Searches were restricted to publications available in English and German. To be included studies had to be empirical; focus on an AI application (excluding robotics) in a health-related setting; and evaluate applications with regards to users. RESULTS: Three studies, one mixed-method and two qualitative studies in English were included. Influences on trust fell into three broad categories: human-related (knowledge, expectation, mental model, self-efficacy, type of user, age, gender), AI-related (data privacy and safety, operational safety, transparency, design, customizability, trialability, explainability, understandability, power-control-balance, benevolence) and context-related (AI company, media, users’ social network). The factors resulted in an updated logic model illustrating the relationship between these aspects. CONCLUSIONS: Trust in HAI depends on a variety of factors, both external and internal to AI applications. This study contributes to our understanding of what influences trust in HAI by highlighting key influences, as well as pointing to gaps and issues in existing research on trust and AI. In so doing, it offers a starting point for further investigation of trust environments as well as trustworthy AI applications.

Type: Article
Title: Influences on User Trust in Healthcare Artificial Intelligence: A Systematic Review
Open access status: An open access version is available from UCL Discovery
DOI: 10.12688/wellcomeopenres.17550.1
Publisher version: https://doi.org/10.12688/wellcomeopenres.17550.1
Language: English
Additional information: © 2022 Jermutus E et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Keywords: Trust, artificial intelligence, human-AI interaction, health care, healthcare AI, systematic review, MMAT, logic model
UCL classification: UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Div of Psychology and Lang Sciences > Clinical, Edu and Hlth Psychology
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Div of Psychology and Lang Sciences
UCL > Provost and Vice Provost Offices > School of Education > UCL Institute of Education
UCL > Provost and Vice Provost Offices > School of Education > UCL Institute of Education > IOE - Social Research Institute
UCL > Provost and Vice Provost Offices > School of Education
URI: https://discovery.ucl.ac.uk/id/eprint/10143985
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