Does Machine Learning Automate Moral Hazard and Error?
指出，在医疗数据中因变量和自变量均存在测量误差，这可能导致机器学习算法放大人类判断中的现有错误，而非推动医疗系统改进。
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.