A majority of the victims are advertised online and have no input into the wording used in the advertisements posted for them by their pimp, who usually controls over 4 to 6 victims, says Reihaneh Rabbany, Assistant Professor at McGill’s School of Computer Science and Canada CIFAR AI chair. This leads to similar phrasing and duplication among listings which can be used to detect organized activity.
The proposed algorithm, called InfoShield, can put millions of advertisements together and highlight the common parts,” adds Christos Faloutsos, Fredkin Professor at CMU’s School of Computer Science, and the CMU project lead. “If the ad have a lot of things in common, it’s not guaranteed, but it’s highly likely that it is something suspicious.” This algorithm could help law enforcement direct their investigations and better identify human traffickers and their victims.
According to the International Labor Organization, an estimated 24.9 million people are trapped in forced labor. Of those, 55% are women and girls trafficked in the commercial sex industry. In the past decade, human trafficking cases have been on the rise in Canada and in response to that the Canadian government (in collaboration with RCMP) has launched a “National Strategy to Combat Human Trafficking 2019-2024”, with one of the focus areas being the need for technological advancements and research. The Infoshield algorithm is taking a step in this direction.
“Human trafficking is a dangerous societal problem which is difficult to tackle,” explains lead authors Catalina Vajiac and Meng-Chieh Lee. “By looking for small clusters of ads that contain similar phrasing rather than analyzing standalone ads, we’re finding the groups of ads that are most likely to be organized activity, which is a strong signal of (human trafficking).”