Renate Baumgartner, Payal Arora, Corinna Bath, Darja Burljaev, Kinga Ciereszko, Bart Custers, Jin Ding, Waltraud Ernst, Eduard Fosch-Villaronga, Vassilis Galanos, Thomas Gremsl, Tereza Hendl, Cordula Kropp, Christian Lenk, Paul Martin, Somto Mbelu, Sara Morais dos Santos Bruss, Karolina Napiwodzka, Ewa Nowak, Tiara Roxanne, Silja Samerski, David Schneeberger, Karolin Tampe-Mai, Katerina Vlantoni, Kevin Wiggert, Robin Williams
- 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 developArtificial 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.…
