Mitigating Racial Bias in Machine Learning

Kristin M. Kostick-Quenet; I. Glenn Cohen; Sara Gerke; Bernard Lo; James Antaki; Faezah Movahedi; Hasna Njah; Lauren Schoen; Jerry E. Estep; J. S. Blumenthal-Barby

doi:10.1017/jme.2022.13

Mitigating Racial Bias in Machine Learning

Kristin M. Kostick-Quenet, I. Glenn Cohen, Sara Gerke, Bernard Lo, James Antaki, Faezah Movahedi, Hasna Njah, Lauren Schoen, Jerry E. Estep, J. S. Blumenthal-Barby

Research output: Contribution to journal › Article › peer-review

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.

Original language	English (US)
Pages (from-to)	92-100
Number of pages	9
Journal	Journal of Law, Medicine and Ethics
Volume	50
Issue number	1
DOIs	https://doi.org/10.1017/jme.2022.13
State	Published - 2022
Externally published	Yes

Keywords

Algorithmic Bias
Artificial Intelligence
Ethics
Machine Learning
Racial Bias

ASJC Scopus subject areas

General Medicine

Online availability

10.1017/jme.2022.13

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title = "Mitigating Racial Bias in Machine Learning",

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.",

keywords = "Algorithmic Bias, Artificial Intelligence, Ethics, Machine Learning, Racial Bias",

author = "Kostick-Quenet, {Kristin M.} and Cohen, {I. Glenn} and Sara Gerke and Bernard Lo and James Antaki and Faezah Movahedi and Hasna Njah and Lauren Schoen and Estep, {Jerry E.} and Blumenthal-Barby, {J. S.}",

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doi = "10.1017/jme.2022.13",

language = "English (US)",

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AU - Kostick-Quenet, Kristin M.

AU - Cohen, I. Glenn

AU - Gerke, Sara

AU - Lo, Bernard

AU - Antaki, James

AU - Movahedi, Faezah

AU - Njah, Hasna

AU - Schoen, Lauren

AU - Estep, Jerry E.

AU - Blumenthal-Barby, J. S.

PY - 2022

Y1 - 2022

N2 - 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.

AB - 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.

KW - Algorithmic Bias

KW - Artificial Intelligence

KW - Ethics

KW - Machine Learning

KW - Racial Bias

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Mitigating Racial Bias in Machine Learning

Abstract

Keywords

ASJC Scopus subject areas

Online availability

Library availability

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