Social Thursday, 06 May 2021 10:13
(Togo First) - Geospatial and demographic data analyzed by predictive algorithms enabled the Togolese government to refine targeting and optimize the second phase of its Novissi cash transfer program, supported by the international NGO
GiveDirectly.
AI used to support Novissi
Artificial intelligence tools have been made available by the World Bank, through the International Development Association (IDA) as part of the Single Identification Program for regional integration and inclusion in West Africa.
The 100 poorest cantons in Togo were identified using geospatial and demographic data. To achieve this, World Bank technicians and experts from the American University of Berkeley and the Northwestern University established micro-estimates of wealth for areas of 2.4 km², a territorial division made by satellite imagery, by applying deep learning algorithms.
Sponsored by: Computer Science Department
Intended Audience(s): Public
Categories: Lectures & Seminars
Abstract: As Covid-19 spreads in low and middle-income countries, economic disruptions have left hundreds of millions without work or income, precipitating the first rise in global extreme poverty in over 20 years. To offset the pandemic’s most devastating effects, national policymakers and humanitarian organizations are scrambling to provide emergency humanitarian aid to those who need it most. But determining “those who need it most” is difficult in many poor and conflict-affected countries, where official government registries are often incomplete and out of date.
This talk describes ongoing work that leverages recent advances in machine learning, applied to rich data from satellites and mobile phone networks, to target and deliver emergency social assistance. The algorithms we have developed now form the basis for Covid-19 response programs in Togo and Nigeria, which a