The anti-trafficking technological innovation competition format created by Pasos Libres was successfully implemented in the first nation-wide technological innovation competition to combat human trafficking in Canada: the DataJam Against Exploitation.

The competition funded by the Government of Canada and organized by the United Nations Office on Drugs and Crime, Fundación Pasos Libres, IBM, and the International Centre for the Prevention of Crime (ICPC), brought together 16 teams and 75 participants from Toronto, Vancouver, Victoria, Ottawa, Oshawa, Montreal, Hamilton, and Thunder Bay. The event, which took place online from May 7 to May 17 of  2021, aimed to increase public awareness of human trafficking and enhance collaboration among interdisciplinary sectors in Canada.

The participants assumed the challenge to design solutions to protect vulnerable communities from human trafficking; identity, prevent and prosecute youth and child exploitation online; and explore the relationship between human trafficking and socioeconomic factors. During the 11 day datajam and with the support of 49 mentors and experts, the participants developed 15 innovative solutions that can be rapidly deployed to fight this crime. Judges from Pasos Libres, IBM, Traffik Analysis Hub, ICPC, and UNODC selected 3 winning and 3 outstanding teams based on their solution’s potential to tackle the datajam’s challenges and positively impact the counter-trafficking field.

First place: Buyer Resist

Representing Vancouver, Buyer Resist is a multidisciplinary team of young professionals passionate about combatting human trafficking and that believes we should use technology to get ahead of traffickers and stop them in their tracks. The team created a tool to scrape, track and analyze escort listings to make them available to law enforcement through a web app. The team scraped advertisements on three large escort websites in Canada and the United States to fetch the data. Each scraper fetches as much information as is available on each page and is adaptable to support ads that contain different information. Buyer Resist processed over 70.000 escort advertisements across Canada and analyzed the data to find similar advertisements and identify connections among them.

 

Second place: Scotiabank AMA

From Toronto, Scotiabank AMA is a team of data scientists who work developing machine learning solutions for various anti-money laundering (AML) use cases, such as transaction monitoring and client risk rating. The team assembled three text clustering models to classify list ads from the same person or group for further investigation. Incorporating location information and identifying traveling patterns, the solution helps detect potential sex trafficking ads, set alerts, and advise potential victims.  During the competition, the team scraped 20k+ ads from 4 major Canadian cities (Toronto, Calgary, Vancouver, and Ottawa), identifying 15 suspicious clusters and 373 potential sex trafficking ads.

Third place: CDL Team

Representing the City of Montreal, CDL team members are affiliated with the Montreal Institute of Learning Algorithms and experienced in diverse areas, including machine learning, network analysis, text and image processing, and criminology. The team developed Red-light, a 6-module A.I. tool that includes a web crawler, image processing module, entity extractor, graph builder, M.O. detector, and spam filter, ultimately presenting groups of related ads ranked order of suspicion.

Interested in learning more about the teams or supporting them? Contact tech@fundacionpasoslibres.org for more information.