Sendhil Mullainathan: Machine Intelligence and Public Policy

Powered by large amounts of data, algorithms today can do pretty amazing things; from recognizing faces to understanding language. Remarkably, the engine underneath these feats is a statistical one – combining large amounts of data to produce fundamental statistical insights. If viewed from the correct light, could this same engine be used to transform public policy? Could we leverage approaches designed for facial recognition to shape the way we think about the social sciences? How would these algorithms perform in these alternative settings?

Sendhil Mullainathan, Robert C. Waggoner Professor of Economics in the Faculty of Arts and Sciences at Harvard University

Photo credits

Frisbee photo: (Rommi Saar) [CC BY-SA 3.0 (http://creativecommons.org/licenses/b…)], via Wikimedia Commons

Motorcross photo: Graeme Main/MOD [OGL (http://www.nationalarchives.gov.uk/do…)], via Wikimedia Commons