New algorithm can detect poverty- from space - Redorbit

Attempting to locate and assist people living in impoverished parts of the world could be made easier by using satellite imagery and machine learning algorithms, according to a new study led by researchers at Stanford University and published in the journal Science. Traditionally, international aid group perform door-to-door surveys to record data on local incomes in developing nations, but as study author Marshall Burke of the Stanford Institute for Economic Policy Research explained, these methods can be expensive and time consuming. They believe they've found a more efficient alternative. "If you give a computer enough data it can figure out what to look for. We trained a computer model to find things in imagery that are predictive of poverty," Burke told BBC News.