Does Machine Learning Automate Moral Hazard and Error?

Sendhil Mullainathan and Ziad Obermeyer

American Economic Review, 2017, vol. 107, issue 5, 476-80

Abstract: Machine learning tools are beginning to be deployed en masse in health care. While the statistical underpinnings of these techniques have been questioned with regard to causality and stability, we highlight a different concern here, relating to measurement issues. A characteristic feature of health data, unlike other applications of machine learning, is that neither y nor x is measured perfectly. Far from a minor nuance, this can undermine the power of machine learning algorithms to drive change in the health care system--and indeed, can cause them to reproduce and even magnify existing errors in human judgment.

JEL-codes: D82 I11 I18 (search for similar items in EconPapers)
Date: 2017
Note: DOI: 10.1257/aer.p20171084
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Citations: View citations in EconPapers (24)

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