Mitigating Racial Bias in Machine Learning
Author ORCID iD
https://orcid.org/0000-0002-5718-3982
Document Type
Article
Publication Date
2022
Abstract
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.
Publication Title
Journal of Law, Medicine & Ethics
Recommended Citation
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).
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