Mitigating Racial Bias in Machine Learning
Author ORCID iD
When applied in the health sector, AI-based applications raise not only ethical but legal and safety concerns, where algorithms trained on data from majority populations can generate less accurate or reliable results for minorities and other disadvantaged groups.
Journal of Law, Medicine & Ethics
Kristin M. Kostick-Quenet, I. Glenn Cohen, Sara Gerke, Bernard Lo, James Antaki, Faezah Movahedi, Hasna Njah, Lauren Schoen, Jerry E. Estep, and J. S. Blumenthal-Barby, Mitigating Racial Bias in Machine Learning, 50 Journal of Law, Medicine & Ethics 92 (2022).