How to End an Epidemic: Harnessing AI to Prevent Human Trafficking

The World Economic Forum Annual Meeting in Davos-Klosters is the foremost creative force for engaging the world's top leaders in collaborative activities to shape the global, regional and industry agendas at the beginning of each year. In this regard, the Forum's mission – improving the state of the world – guides the design and development of the Annual Meeting objectives.

Human trafficking is an epidemic social injustice, with an estimated 71% of the approximate 25 million victims represented by women and girls. The “industry” brings in $150 million in profits annually – much of which funnels through our global financial system. Banks are trying to prevent this – but until recently were under-equipped using traditional detection methods. 

In a panel discussion at the Annual Meeting, our Ellen Zimiles and Tim Mueller discussed how banks can use cutting-edge AI technologies to better detect and ultimately prevent human trafficking. Ellen Zimiles explains that two real challenges are that “there is a lot of cross-border activity. It doesn’t all stay in one country. Not every country shares information because of data privacy and data protection laws. It’s actually hard to share certain information across borders.” Our Tim Mueller added that "human trafficking has been one of those areas that's very difficult through the traditional techniques to identify. I think we're finally starting to find ways to use machine learning, and network and behavioral analytics to identify them, so we're really excited about that possibility." This discussion was complemented by our published article "4 Ways to Unleash Machine Intelligence - And Take On the Criminal World".

Watch the full panel presentation on The Female Quotient Facebook feed here: