Can State-of-the-Art Machine Learning Tools Give New Life to Household Survey Data?

In 2014 the UN called for a data revolution to put the best available tools and methods to work in service of achieving the Sustainable Development Goals. Researchers at the World Bank have responded to that call by scouring the globe for the latest machine learning tools to transform our approach to tracking progress in the fight against poverty. "Collecting household survey data on poverty is expensive and time-consuming, which means that policy makers are often making decisions based on old data," said Asli Demirguc-Kunt, Director of Research at the World Bank. "Machine learning could drastically change the game, making poverty measurement cheaper and much closer to real-time." Machine learning is a field of computer science that allows computers to examine large bodies of data to identify patterns that data scientists would never find on their own.