The Institute for Data, Systems, and Society invites you to its first seminar in the fall 2015 IDSS Distinguished Seminar Series on Tuesday, Sept. 15, from 4 to 5 p.m. in the MIT Stata Center (32-141). Professor Sendhil Mullainathan from Harvard University will present "Making Good Policies with Bad Causal Inference: The Role of Prediction and Machine Learning." A reception will follow.
In the last few decades, we have learned to be careful about causation, and have developed powerful tools for making causal inferences from data. Applying these tools has generated both policy impact and conceptual insights. In his talk, Mullainathan will argue that there are significant problems where causal inference is largely unnecessary — and, instead, prediction is the central challenge. These problems are ideally suited for machine learning and high dimensional data-analysis tools. Mullainathan aims to delineate the difference between problems that require causation and problems that require prediction; describe results from solving one such prediction problem in detail; highlight the set of new statistical issues these problems raise; and argue that solving these problems can also generate both policy impact and conceptual insights.