The Science of the Predicted Human talk series: Joshua Blumenstock

Science of the predicted human

We are delighted to host Joshua Blumenstock (UC Berkeley) for a talk in our series on The Science of the Predicted Human. His research combines econometrics, machine learning and network science to explore the application of predictive algorithms for improving social programs, the spread of information online and much more.

Please join us for this event on April 19 at 1330-1500 in Goth. Aud. 1, Gothersgade 140.

Title
Targeting Social Assistance with Machine Learning 

Abstract 
Targeting is a central challenge in the design of anti-poverty programs: given available data, how does one rapidly identify the individuals and families with the greatest need? Here we show that machine learning, applied to non-traditional data from satellites and mobile phones, can improve the targeting of anti-poverty programs. Our analysis is based on data from three field-based projects -- in Togo, Afghanistan, and Kenya -- that illustrate the promise, as well as some of the potential pitfalls, of this new approach to targeting. Collectively, the results highlight the potential for new data sources to improve humanitarian response efforts, particularly in crisis settings when traditional data are missing or out of date.

About Joshua Blumenstock
He is a Chancellor’s Associate Professor at the U.C. Berkeley School of Information and the Goldman School of Public Policy. He is the Co-director of the Global Policy Lab and the Center for Effective Global Action. Blumenstock does research at the intersection of machine learning and empirical economics, with a focus on how novel data can better address the needs of poor and marginalized people around the world. He has a Ph.D. in Information Science and a M.A. in Economics from U.C. Berkeley, and Bachelor’s degrees in Computer Science and Physics from Wesleyan University. He is a recipient of awards including the NSF CAREER award, the Intel Faculty Early Career Honor, and the U.C. Berkeley Chancellor's Award for Public Service. His work has appeared in general interest journals including Science, Nature, and PNAS, as well as top economics journals (e.g., AER) and computer science conferences (e.g., ICML, KDD, AAAI, WWW, CHI).