Baumgartner, R., Arora, P., Bath, C. et al. (23 more authors) (2023) Fair and equitable AI in biomedical research and healthcare: social science perspectives. Artificial Intelligence in Medicine, 144. 102658. ISSN 0933-3657
Abstract
Artificial intelligence (AI) offers opportunities but also challenges for biomedical research and healthcare. This position paper shares the results of the international conference “Fair medicine and AI” (online 3–5 March 2021). Scholars from science and technology studies (STS), gender studies, and ethics of science and technology formulated opportunities, challenges, and research and development desiderata for AI in healthcare. AI systems and solutions, which are being rapidly developed and applied, may have undesirable and unintended consequences including the risk of perpetuating health inequalities for marginalized groups. Socially robust development and implications of AI in healthcare require urgent investigation. There is a particular dearth of studies in human-AI interaction and how this may best be configured to dependably deliver safe, effective and equitable healthcare. To address these challenges, we need to establish diverse and interdisciplinary teams equipped to develop and apply medical AI in a fair, accountable and transparent manner. We formulate the importance of including social science perspectives in the development of intersectionally beneficent and equitable AI for biomedical research and healthcare, in part by strengthening AI health evaluation.
Metadata
Item Type: | Article |
---|---|
Authors/Creators: |
|
Copyright, Publisher and Additional Information: | © 2023 The Authors. Published by Elsevier B.V. This is an Open Access article distributed under the terms of the Creative Commons Attribution Licence (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
Keywords: | Bias; Discrimination; Health equity; Inequalities; Medicine; Humans; Artificial Intelligence; Delivery of Health Care; Biomedical Research; Social Sciences; Medicine |
Dates: |
|
Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Social Sciences (Sheffield) > Faculty of Social Sciences Research Institute The University of Sheffield > Faculty of Social Sciences (Sheffield) > Department of Sociological Studies (Sheffield) |
Funding Information: | Funder Grant number WELLCOME TRUST (THE) 219875/Z/19/Z |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 07 Oct 2024 09:25 |
Last Modified: | 07 Oct 2024 09:25 |
Published Version: | http://dx.doi.org/10.1016/j.artmed.2023.102658 |
Status: | Published |
Publisher: | Elsevier BV |
Refereed: | Yes |
Identification Number: | 10.1016/j.artmed.2023.102658 |
Related URLs: | |
Sustainable Development Goals: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:217942 |