Targeting is a core element of anti-poverty program design, with benefits typically targeted to those most "deprived" in some sense (e.g., consumption, wealth). A large literature in economics examines how to best identify these households feasibly at scale, usually via proxy means tests (PMTs)....

Algorithms (in some form) are already widely used in the criminal justice system. We draw lessons from this experience for what is to come for the rest of society as machine learning diffuses. We find economists and other social scientists have a key role to play in shaping the impact of...

Algorithms (in some form) are already widely used in the criminal justice system. We draw lessons from this experience for what is to come for the rest of society as machine learning diffuses. We find economists and other social scientists have a key role to play in shaping the impact of...

We use machine learning to better characterize low-value health care and the decisions that produce it. We focus on costly tests, specifically for heart attack (acute coronary syndromes). A test is only useful if it yields new information, so efficient testing is grounded in accurate prediction...