Artificial intelligence and low-cost satellite imagery combine to spot forced labor at deforestation sites in Brazil’s Amazon rainforest.

Both legal and illegal deforestation efforts routinely rely on forced labor, and Brazilian prosecutors have been chasing down those abuses for years. But the sites are remote and transitory, often abandoned before inspectors can reach them.

The new system addresses that challenge by recognizing one of the telltale signs of an active deforestation site: large arrays of charcoal ovens that convert the fallen timber into charcoal. The tent-shaped ovens are typically about three meters (just under 10 feet) in diameter and usually arrayed in long rows.

“Forced labor is difficult to find, but satellite imagery can really help identify where it’s happening in time for inspectors to intervene more effectively,” says Victoria Ward, an assistant professor of pediatrics at Stanford Medicine. “The idea is to create transparency, so people can’t say they don’t know what’s happening.”

Ward and her colleagues at Stanford’s Human Trafficking Data Lab teamed up on the project with Brazilian labor prosecutors and nonprofit organizations.

The team began by collecting data from labor inspection reports at hundreds of charcoal-burning sites from 2018 to 2020. They then obtained satellite images for about 200 of those locations at the time of the inspections and hand-labeled their distinctive visual features.

Read the full article about AI spotting forced labor by Edmund L. Andrews at Futurity.