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SHR Neuro Cancer Cardio Lipid Metab Microb

Baumgartner, R; Arora, P; Bath, C; Burljaev, D; Ciereszko, K; Custers, B; Ding, J; Ernst, W; Fosch-Villaronga, E; Galanos, V; Gremsl, T; Hendl, T; Kropp, C; Lenk, C; Martin, P; Mbelu, S; Bruss, SMD; Napiwodzka, K; Nowak, E; Roxanne, T; Samerski, S; Schneeberger, D; Tampe-Mai, K; Vlantoni, K; Wiggert, K; Williams, R.
Fair and equitable AI in biomedical research and healthcare: Social science perspectives
ARTIF INTELL MED. 2023; 144: 102658 Doi: 10.1016/j.artmed.2023.102658
Web of Science PubMed FullText FullText_MUG

 

Co-authors Med Uni Graz
Schneeberger David Michael
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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.

Find related publications in this database (Keywords)
Inequalities
Health equity
Medicine
Discrimination
Bias
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