BU Cyber Alliance hosts 2/20 Seminar, Featuring Sendhil Mullainathan

1:00 PM – 2:00 PM on Tuesday, February 20, 2018
BU Law, 15th Floor Faculty Lounge

Using Machine Learning to Improve Policy Problems; An Econometric Perspective
Sendhil Mullainathan
Professor, Harvard University

Abstract: Can machine learning improve policy outcomes? Can it to do so even if the algorithms do not draw causal conclusions? How do we manage the possibility that algorithms will might magnify racial and other biases? To examine these questions, Harvard University Economics Professor Sendhil Mullainathan will talk through one end-to-end example: pretrial detention decisions.

Using a large historical data set, he and his colleagues build and evaluate the potential for a purely predictive algorithm to improve on judges’ decisions making. On the one hand, their results suggest room for optimism–we can reduce, crime, incarceration rates and simultaneously reduce racial biases. At the same time, there is room for caution. Their application highlights the dangers of ‘naive’ applications. In particular, Professor Mullainathan highlights two central and thorny econometric problems — selective labels and omitted payoff biases – that are often ignored. Along the way he will present a simple econometric framework that lays out these problems but also provides a way to understand the role of prediction in policy as well racial (or other) biases in machine learning.

Bio: Sendhil Mullainathan is the Robert C. Waggoner Professor of Economics in the Faculty of Arts and Sciences at Harvard University. He has worked on poverty, behavioral economics and a wide variety of topics such as: the impact of poverty on mental bandwidth; whether CEO pay is excessive; using fictitious resumes to measure discrimination; showing that higher cigarette taxes makes smokers happier; modeling how competition affects media bias; and a model of coarse thinking. His latest research focuses on using machine learning to better understand human behavior.

He enjoys writing, having recently co-authored Scarcity: Why Having too Little Means so Much and writes regularly for the New York Times.

He helped co-found a non-profit to apply behavioral science (ideas42), co-founded a center to promote the use of randomized control trials in development (the Abdul Latif Jameel Poverty Action Lab), serves on the board of the MacArthur Foundation, has worked in government in various roles, is affiliated with the NBER, BREAD, and a member of the American Academy of Arts and Sciences.

He is a recipient of the MacArthur “genius” Award, has been designated a “Young Global Leader” by the World Economic Forum, labeled a “Top 100 Thinker” by Foreign Policy Magazine, and named to the “Smart List: 50 people who will change the world” by Wired Magazine (UK). His hobbies include basketball, board games, googling and fixing-up classic espresso machines.