"...When people become richer, you see that they make longer phone calls. And so that allows you to infer poverty at this incredibly high grain level..."
On Tuesday, January 16, 2018, Economist Sendhil Mullainathan spoke about the potential for machine learning technology to inform poverty alleviation policies.
Citing examples that ranged from using cell phone data to predict evolving poverty maps and rainfall to algorithms that could inform incarceration policies, Mullainathan examined the possibility of using newly accessible data in ways that could have real world impact on work in global development. The conversation was moderated by David Lobell, Professor of Earth System Science, and a King Center Faculty Affiliate.
The Stanford King Center on Global Development Speaker Series features talks by distinguished scholars and policymakers to foster discussions about successes and challenges in the field of poverty alleviation and development.
Please note that prior to May 2019, the Stanford King Center on Global Development was known as the Stanford Center on Global Poverty and Development. For more information, please visit [ Ссылка ]
