Beds. Dressers. Clothing.
All items that raised the suspicions of a state health inspector that “business as usual” at the Orchids of Asia Day Spa in Jupiter, Fla., was anything but.
The observation that employees might be living in the spa—a red flag for human trafficking—helped launch a large-scale criminal investigation into the massage parlor and others like it across the state.
Although prosecutors ultimately did not file human trafficking charges, the media attention surrounding this high-profile case cast the issue of modern-day slavery into the spotlight. At the same time, it called attention to the challenges of using a low-tech, see-something-say-something approach to identify these types of abuses.
It’s a reality apparent to Dan Lopresti, a professor of computer science and engineering, who says the time is ripe to move beyond our reliance on good—but fortuitous—observations to uncover crimes of human trafficking.
With the United Nations calling upon states, through Target 8.7 of its Sustainable Development Goals, to end forced labor, modern slavery and human trafficking by 2030 (and the worst forms of child labor by 2025), it’s time, he says, to leverage technology to support trained law enforcement in tackling this complex issue.
Lopresti, who directs Lehigh’s interdisciplinary Data X Initiative, is at the forefront of a growing movement within the computer science community to help achieve that ambitious goal through the power of artificial intelligence and advanced computing.