Mitigating Racial Bias in Machine Learning. Issue 1 (2022)

• Record Type: Journal Article
• Authors: Kostick-Quenet, Kristin M.; Cohen, I. Glenn; Gerke, Sara; Lo, Bernard; Antaki, James; Movahedi, Faezah; Njah, Hasna; Schoen, Lauren; Estep, Jerry E.; Blumenthal-Barby, J.S.
• Editors: Goodwin, Michele; Lynch, Holly Fernandez
• Is Part Of: Journal of law, medicine & ethics. Volume 50:Issue 1(2022)
• Page Start: 92
• Page End: 100
• Publication Date: 2022
• Subjects: Algorithmic Bias -- Racial Bias -- Machine Learning -- Artificial Intelligence -- Ethics; Medical laws and legislation -- United States -- Periodicals; Medical care -- Law and legislation -- United States -- Periodicals; Medical ethics -- Periodicals; Jurisprudence -- Periodicals; Legislation, Medical -- Periodicals; Legislation, Nursing -- Periodicals; Ethics -- Periodicals; Forensic Medicine -- Periodicals; Nursing -- Periodicals; Medicine -- Periodicals; Societies -- Periodicals; Medical care -- Law and legislation; Medical ethics; Medical laws and legislation; United States; Periodicals; 344.73041
• DOI: 10.1017/jme.2022.13
• Languages: English
• ISSNs: 1073-1105

Abstract

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.