Dissecting racial bias in an algorithm used to manage the health of populations

Ziad Obermeyer · Brian W. Powers · et al. Vogeli C

21 citations0/0 files storedYearbook of pediatric endocrinology

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Ethics and Social Impacts of AI Artificial Intelligence in Healthcare and Education Race, Genetics, and Society

Abstract

Short summary: Dissecting racial bias in health care systems revealed that a type of software program, which determines who receives access to high-risk health care management, routinely accepts healthier whites ahead of blacks who are less healthy.

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References

2016Inherent Trade-Offs in the Fair Determination of Risk Scores 2018The Measure and Mismeasure of Fairness 2018The Frontiers of Fairness in Machine Learning 2018Does Diversity Matter for Health? Experimental Evidence from Oakland 2019Uniform Pricing in US Retail Chains

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2022Subverting machines, fluctuating identities: Re-learning human categorization 2020Colorblind Algorithms: Racism in the Era of COVID-19

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