Stratifiering, välfärd och socialpolitik-seminarium, vid Institutet för social forskning (SOFI);

Adel Daoud från Institutet för analytisk sociologi (IAS) vid Linköpings universitet presenterar "Observatory of Poverty: Combining AI and Earth Observation to Measure Health and Living Conditions in Africa"

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Abstract

About 900 million people globally—one-third in Africa and another one-third in India—live in extreme poverty. Operating on the assumption that impoverished communities are trapped in poverty, major global donors have deployed a stream of development programs to break these traps. Despite the scale of programs, scholars have little knowledge about the distribution of global poverty historically and geographically. To address these knowledge gaps, scholars must first tackle a data challenge: the lack of historical and geographical poverty data. The AI and Global Development Lab is innovating development research by combining deep-learning, satellite technologies, and knowledge on human development to overcome the data challenge. The Lab is recreating historical and geographical human-development trajectories from satellite images from 1984 to 2022. These new data will measure poverty at unprecedented temporal and spatial granularity. Among other things, these data will enable the Lab (and other scholars) to start examining—with a high precision—the causal effects of foreign aid on poor communities’ chances of breaking poverty. This talk will discuss key scientific challenges and early findings.