SAN FRANCISCO — Last week, at an event on artificial intelligence for economic development, Josh Blumenstock, an assistant professor from the University of California, Berkeley, gave a talk entitled “Fighting Poverty with Data.”
Blumenstock talked about his work gathering mobile phone data from the cell phones of users in Rwanda and then turning that information, such as the number of calls made per day, SMS volume, and international contacts, into interpretable metrics. His research is at the intersection of machine learning and international development, the focus of the event organized by the Center for Effective Global Action and the World Bank at Google’s headquarters in San Francisco. He highlighted how mobile phone metadata can predict poverty, and the implications of that in terms of targeting aid, crisis response, and impact evaluation.
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