How a new type of AI is helping police skirt facial recognition bans

“The whole vision behind Track in the first place,” says Veritone CEO Ryan Steelberg, was “if we’re not allowed to track people’s faces, how do we assist in trying to potentially identify criminals or malicious behavior or activity?” In addition to tracking individuals where facial recognition isn’t legally allowed, Steelberg says, it allows for tracking when faces are obscured or not visible. 

The product has drawn criticism from the American Civil Liberties Union, which—after learning of the tool through MIT Technology Review—said it was the first instance they’d seen of a nonbiometric tracking system used at scale in the US. They warned that it raises many of the same privacy concerns as facial recognition but also introduces new ones at a time when the Trump administration is pushing federal agencies to ramp up monitoring of protesters, immigrants, and students.

Veritone gave us a demonstration of Track in which it analyzed people in footage from different environments, ranging from the January 6 riots to subway stations. You can use it to find people by specifying body size, gender, hair color and style, shoes, clothing, and various accessories. The tool can then assemble timelines, tracking a person across different locations and video feeds. It can be accessed through Amazon and Microsoft cloud platforms.

In an interview, Steelberg said that the number of attributes Track uses to identify people will continue to grow. When asked if Track differentiates on the basis of skin tone, a company spokesperson said it’s one of the attributes the algorithm uses to tell people apart but that the software does not currently allow users to search for people by skin color. Track currently operates only on recorded video, but Steelberg claims the company is less than a year from being able to run it on live video feeds.

Agencies using Track can add footage from police body cameras, drones, public videos on YouTube, or so-called citizen upload footage (from Ring cameras or cell phones, for example) in response to police requests.

“We like to call this our Jason Bourne app,” Steelberg says. He expects the technology to come under scrutiny in court cases but says, “I hope we’re exonerating people as much as we’re helping police find the bad guys.” The public sector currently accounts for only 6% of Veritone’s business (most of its clients are media and entertainment companies), but the company says that’s its fastest-growing market, with clients in places including California, Washington, Colorado, New Jersey, and Illinois. 

That rapid expansion has started to cause alarm in certain quarters. Jay Stanley, a senior policy analyst at the ACLU, wrote in 2019 that artificial intelligence would someday expedite the tedious task of combing through surveillance footage, enabling automated analysis regardless of whether a crime has occurred. Since then, lots of police-tech companies have been building video analytics systems that can, for example, detect when a person enters a certain area. However, Stanley says, Track is the first product he’s seen make broad tracking of particular people technologically feasible at scale.