The economic effects of COVID-19 have drastically driven up the world’s extreme poverty level. The World Bank estimates that the number of people living on less than $1.90 per day will reach 150 million by 2021. GiveDirectly, a charity that has focused for just under a decade on direct cash transfers to people in poverty around the world, particularly in Africa, has been escalating its pandemic relief efforts—and continually innovating with partners to find groundbreaking ways to target the most in need of money. The charity’s latest innovation is harnessing an algorithm, designed by UC Berkeley, that uses artificial intelligence to identify the poorest individuals in the poorest areas, and transfer cash relief directly to them.
Typically, in order to evaluate whom to send money to, GiveDirectly will use poverty data from national surveys, and enroll all the households in a particular area. If it needs to target more narrowly, it will depend on lists from governments, NGOs, and local organizations; use points-based poverty indexes; or rely on subjective assessments. This new initiative allows the targeting to be faster and more accurate, completely contactless (which is vital during the pandemic), and naturally adapting and evolving as data changes over time.
The algorithm works in two stages, using two distinct data sources. First, it finds the poorest neighborhoods or villages in a certain region, by analyzing high-resolution satellite imagery. The tool identifies those areas from hundreds of poverty markers that distinguish poorer from wealthier places, such as roof material, building density, sizes of farm plots, and paved or unpaved roads.