Machine Learning and the Future of Poverty Prediction
STORY HIGHLIGHTS
- Poverty measurement relies on collecting detailed household survey data, which is often expensive and time-consuming.
- Researchers at the World Bank are experimenting with the latest machine learning tools to expand the use and value of these datasets.
- Data scientists need to commit to openness around data, software, and methods to make machine learning an effective tool for tracking poverty.
