Using AI to locate victims of sex trafficking

From The Register:

A group of researchers from George Washington University, Temple University, and Adobe in the US have built a large dataset containing over a million images from 50,000 hotels across different countries. They hope their public Hotels-50K dataset will help developers train neural networks that can spot where a victim may be in seconds, judging from the background of their online ad.

A room’s decor may indicate its general vicinity, based on the hotel it is likely to be in. Curtains, wallpaper, bedspreads, and so on, can be analyzed to narrow down victims to particular chains and locations.

Very interesting work, though not something that should be undertaken without considering what some of the unintended consequences may be. Most obviously, identifying locations in this way may lead to pimps going to darker lengths to hide these women.

And this recent report should give added pause for thought:

Violent crime is way down in San Francisco, according to the latest police statistics. But one major category is bucking the trend: police recorded a 170 percent jump in reports of human trafficking in 2018.

The huge spike appears to be connected to the federal shutdown of sex-for-sale websites. The goal of shutting them down was to curb human trafficking. Instead, it seems to have had the opposite effect.

What can we learn from this? Measures to help women in the sex trade tend to be more successful when people listen to the women.