Six months ago I attended the largest gathering of chiefs of police in the US to see how they’re using AI. I found some big developments, like officers getting AI to write their police reports. Today, I published a new story that shows just how far AI for police has developed since then. 

It’s about a new method police departments and federal agencies have found to track people: an AI tool that uses attributes like body size, gender, hair color and style, clothing, and accessories instead of faces. It offers a way around laws curbing the use of facial recognition, which are on the rise. 

Advocates from the ACLU, after learning of the tool through MIT Technology Review, said it was the first instance they’d seen of such a tracking system used at scale in the US, and they say it has a high potential for abuse by federal agencies. They say the prospect that AI will enable more powerful surveillance is especially alarming at a time when the Trump administration is pushing for more monitoring of protesters, immigrants, and students. 

I hope you read the full story for the details, and to watch a demo video of how the system works. But first, let’s talk for a moment about what this tells us about the development of police tech and what rules, if any, these departments are subject to in the age of AI.

As I pointed out in my story six months ago, police departments in the US have extraordinary independence. There are more than 18,000 departments in the country, and they generally have lots of discretion over what technology they spend their budgets on. In recent years, that technology has increasingly become AI-centric. 

Companies like Flock and Axon sell suites of sensors—cameras, license plate readers, gunshot detectors, drones—and then offer AI tools to make sense of that ocean of data (at last year’s conference I saw schmoozing between countless AI-for-police startups and the chiefs they sell to on the expo floor). Departments say these technologies save time, ease officer shortages, and help cut down on response times. 

Those sound like fine goals, but this pace of adoption raises an obvious question: Who makes the rules here? When does the use of AI cross over from efficiency into surveillance, and what type of transparency is owed to the public?

In some cases, AI-powered police tech is already driving a wedge between departments and the communities they serve. When the police in Chula Vista, California, were the first in the country to get special waivers from the Federal Aviation Administration to fly their drones farther than normal, they said the drones would be deployed to solve crimes and get people help sooner in emergencies. They’ve had some successes. 

But the department has also been sued by a local media outlet alleging it has reneged on its promise to make drone footage public, and residents have said the drones buzzing overhead feel like an invasion of privacy. An investigation found that these drones were deployed more often in poor neighborhoods, and for minor issues like loud music. 

Jay Stanley, a senior policy analyst at the ACLU, says there’s no overarching federal law that governs how local police departments adopt technologies like the tracking software I wrote about. Departments usually have the leeway to try it first, and see how their communities react after the fact. (Veritone, which makes the tool I wrote about, said they couldn’t name or connect me with departments using it so the details of how it’s being deployed by police are not yet clear). 

Sometimes communities take a firm stand; local laws against police use of facial recognition have been passed around the country. But departments—or the police tech companies they buy from—can find workarounds. Stanley says the new tracking software I wrote about poses lots of the same issues as facial recognition while escaping scrutiny because it doesn’t technically use biometric data.

“The community should be very skeptical of this kind of tech and, at a minimum, ask a lot of questions,” he says. He laid out a road map of what police departments should do before they adopt AI technologies: have hearings with the public, get community permission, and make promises about how the systems will and will not be used. He added that the companies making this tech should also allow it to be tested by independent parties. 

“This is all coming down the pike,” he says—and so quickly that policymakers and the public have little time to keep up. He adds, “Are these powers we want the police—the authorities that serve us—to have, and if so, under what conditions?”

This story originally appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first, sign up here.