A recent article by NPR highlights the effects of Novissi, a cash transfer program designed in partnership with the Togo Government and CEGA Faculty Director Josh Blumenstock’s team of researchers. The project used AI to target Togo’s neediest residents and offered them mobile money transfers to counteract the financial burden of COVID-19:
“In low-income countries, identifying people who have fallen on hard times due to the pandemic is no easy task. People in this economic bracket often work in the informal sector and don’t have documents to prove how much they earn. As a result, governments don’t have good data about who is poor. There are ways to find out — for example, going door-to-door and asking detailed questions about how much money a family earns — but that kind of in-person surveying is problematic in a pandemic…
So Togo turned to artificial intelligence: a computer program that dives into data to pinpoint pockets of poverty. The government partnered with researchers at the University of California, Berkeley, and the U.S. charity GiveDirectly to use satellite imagery and mobile phone data to find citizens most in need…
Blumenstock, an associate professor at the School of Information at Berkeley, has been researching new and different ways to measure poverty. His lab showed that computers can detect levels of wealth just by satellite imagery, and that the way people use their cell phones can be a pretty good indicator of how rich or poor they are.
GiveDirectly was willing to help implement this new methodology in Togo and distribute $4 million in funds from its donors in this second phase of the program, called Novissi GiveDirectly.”
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