Applications of Machine Learning to the Targeting of Humanitarian Aid

Tue 2/6/2024 • 1PM - 2:30PM PST

Charles E. Young Research Library, Main Conference Room 11360


Joshua Blumenstock, PhD, Chancellor's Associate Professor, School of Information and Goldman School of Public Policy, UC Berkeley
Targeting is a central challenge in the design of humanitarian programs: given available data, how does one identify the individuals and households with the greatest need for humanitarian aid?

In this talk, Blumenstock will show that machine learning, applied to non-traditional data from satellites and mobile phones, can improve the targeting of anti-poverty programs. His team's 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 challenges, 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sources to improve humanitarian response efforts, particularly in crisis settings when traditional data are missing or out of date.

This talk will be held in person and via Zoom.

Light refreshments will be served.

#Educational #Academic

RSVP for Event

Event Website

Add to My Calendar (ICS)