At Uptake.org, we build tools that use data science and machine learning to address the world’s most pressing problems. One of those problems is human trafficking.
Our ReRoute application gives border monitoring organizations the insight they need to better identify victim profiles.
We built the tool because border crossing stations are critical locations where a life-saving intervention can happen before the years of exploitation and trauma occur.
Border monitors are trained to look for warning signs and interview potential victims, learning their demographics and reasons for leaving the country. However, in order to recognize potential victims, monitors need to have a constantly changing strategy. As they catch on to patterns in victims’ stories, traffickers switch methods to avoid detection.
To solve this problem, ReRoute uses machine learning to recognize patterns in interview data. The tool identifies emerging victim profiles and locations where victims are coming from, as well as illuminates patterns such as times of day and days of week when traffickers use particular routes.
Andrew Means, director of Uptake.org, recently traveled to the Nepalese-Indian border to see the tool in action. Here’s what he learned on the trip.