“Fighting Poverty with Data: Research at the Intersection of Machine Learning and Development Economics” with Joshua Blumenstock ’03


Friday, April 15th at 12pm in Downey House 113.

In wealthy nations, novel sources of “big data” from the internet and social media are creating new opportunities for commercial profit, enabling new approaches to social science research, and inspiring new perspectives on public policy. In developing economies, however, fewer sources of robust data exist, and it remains unclear if and how the world’s poor will benefit from the ongoing “data revolution.” In this talk, I will discuss a series of studies that combine insights from machine learning with traditional methods in empirical economics to better understand economic development and vulnerability. The talk will focus on recent results from Afghanistan, Ghana, and Rwanda, which show how terabyte-scale data from mobile phone networks can be combined with field-based experiments and on-the-ground interviews to construct accurate estimates of the distribution of poverty and wealth. In resource-constrained environments where censuses and household surveys are rare, this creates options for gathering localized and timely information at a fraction of the cost of traditional methods.

Joshua Blumenstock graduated from Wesleyan University in 2003 with Degrees in Computer Science and Physics. After Wesleyan, he did a Watson Fellowship, spent a few years in internet startups, and then went back to grad school at U.C. Berkeley, where he received a Ph.D. in Information Science and a M.A. in Economics. Currently, Joshua is an Assistant Professor the University of Washington, with faculty appointments in the Information School and the Department of Computer Science and Engineering. He is also the founder and co-Director of the Data Science and Analytics Lab, where he develops new methods for the analysis of large-scale behavioral data, with a focus on how such data can be used to better understand poverty and economic development. Recent projects combine field experiments with terabyte-scale spatiotemporal network data to model decision-making in poor and conflict-affected regions of the world. He is a recipient of the Intel Faculty Early Career Honor, a Gates Millenium Grand Challenge award, a Google Faculty Research Award.

This event is sponsored by DaCKI