DARPA-funded research IDs sex traffickers with machine learning

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Carnegie Mellon University is touting a new $3.6 million research grant from the Defense Advanced Research Projects Agency, or DARPA, to build machine learning algorithms that can index online sex ads in order to identify sex traffickers. The research is part of a larger DARPA program called Memex that aims to index seedy portions of the public web and deep web in order to identify any type of human trafficking on a larger scale.

One of the driving forces behind this type of effort is the simple fact that computers can analyze ads soliciting sex at a much greater scale than human investigators can. However, the press release announcing the DARPA grant noted, “In addition to analyzing obvious clues, CMU experts in computer vision, language technologies and machine learning will develop new tools for such tasks as analyzing the authors of ads or extracting subtle information from images.”

Even prior to this project, Carnegie Mellon said researchers at the university were working on the issue of sex trafficking and developed programs that law-enforcement agencies have already used to make arrests. That’s a reassuring piece of information considering that much university research, even the stuff involving serious issues, has a hard time making its way into the hands of law enforcement or others who can act on it.

Although, human trafficking for sex or otherwise does seem to be an issue that’s bringing together all sorts of organizations with unique abilities to combat it. Aside from the work at Carnegie Mellon, Google is doing a lot of work to identify victims and their traffickers, via targeted search results as well as partnerships with the Polaris Project and Palantir. There’s also Thorn, a non-profit started by Ashton Kutcher and Demi Moore that uses various technologies to identify cases of child exploitation online.

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