Does Machine Learning Automate Moral Hazard and Error?
American Economic Review
vol. 107,
no. 5, May 2017
(pp. 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.Citation
Mullainathan, Sendhil, and Ziad Obermeyer. 2017. "Does Machine Learning Automate Moral Hazard and Error?" American Economic Review, 107 (5): 476-80. DOI: 10.1257/aer.p20171084Additional Materials
JEL Classification
- D82 Asymmetric and Private Information; Mechanism Design
- I11 Analysis of Health Care Markets
- I18 Health: Government Policy; Regulation; Public Health