Joshua Blumenstock was always interested in being of service to others. "Ever since high school, I've been interested in working in low income settings to help improve living standards and create opportunities," he says. "But my strengths as a scholar were on the technical side - computer science, artificial intelligence, quantitative analysis."
At first, Blumenstock didn't see a straight line between his skillset and those kinds of global development issues, but during his time as a graduate student at UC Berkeley, a path began to emerge. "I started to see angles where the tools that I was good at might provide a different perspective on some of the questions that people had been studying for a long time," he says.
One of those questions is: What would it cost to end extreme global poverty? Blumenstock unpacks it in this video, part of our ongoing 101 in 101 series in which scholars explain part of their work in just 101 seconds.
Blumenstock is now a professor at Berkeley's School of Information and Goldman School of Public Policy, director of the Global Opportunity Lab and a faculty co-director of the Center for Effective Global Action. His work has taken him to Afghanistan, Togo, Rwanda and beyond, using machine learning and AI to better solve problems like identifying the neediest households for humanitarian aid, enabling access to financial services and responding to climate shocks and other crises.
Watch more 101 in 101 videos featuring UC Berkeley faculty and experts here.
Video edited by Chris Chang
