AI Surveillance Company Pitches Law Enforcement on Adding Facial Recognition to Flock Cameras

As Flock continues to be the center of a nationwide conversation about automatic license plate reading cameras, the company has said that it doesn’t, and won’t, do facial recognition: “We will not add facial recognition to our devices,” Flock CEO Garrett Langley said in a recent video. But other, third-party companies are telling cops that they are willing to add facial recognition to data gathered by Flock cameras in order to “close that gap.” 

A company called VIDIZMO is advertising the capability to export footage from FlockOS to its own platforms that do facial recognition, behavior prediction, and racial and gender analysis on live camera feeds. VIDIZMO is a several decades-old video analysis and database company that has started offering facial recognition technology to cops within the last six months. In a May email to Johnson City, Tennessee, deputy police chief Michael Adams, a salesperson from VIDIZMO wrote that the company’s product could do facial recognition on both Flock and Axon data in “one searchable platform.”

“Flock Safety generates plate reads and clips continuously. Your investigators use that data on active cases. But that Flock data does not connect automatically to your Axon evidence system,” the salesperson wrote. “VIDIZMO Intelligence Hub closes that gap. It brings Flock Safety data, Axon body worn camera footage, and any other evidence source into one searchable platform. Investigators search across all of it simultaneously —  by face, vehicle, or object in seconds.” The email was obtained using a public records request by DeFlock Johnson City and was shared with 404 Media. The Johnson City PD told 404 Media in a statement that it did not take a call with the company.

VIDIZMO’s CEO, Nadeem Khan, told 404 Media on a video call that the company has not yet started running facial recognition tech on footage from Flock cameras, and that it has not actually built the specific tool that would export data from Flock’s system to its own platform (though the company advertises this capability online, and the company already sells other facial recognition products). But Khan said VIDIZMO “would love to do the integration,” and that he believes facial recognition “is the way the world is going, the way the world will have to be,” and that he thinks Flock should offer the capability itself in a way that “balances privacy, security, and the freedom that we enjoy in this country.” 

“It is completely in line with what we want to do,” Khan said. “All of these technologies are already implemented [in the real world]. I think Flock is trying to get out of the way rather than trying to implement the technology right [correctly] by saying they will not do recognition. But this is the way the world is going, it is the way the world will have to be, but with the right sort of technologies where privacy and security are balanced.”

BREAKING: The Detroit police department has wrongly arrested another person based on a faulty facial recognition match — this time an 8-month pregnant Black woman.

This is the third known wrongful arrest from this department for a false facial recognition match in three years.

— ACLU (@ACLU) August 6, 2023

Khan said in an email that a law enforcement agency using the technology “can import plate reads or clips that it has exported under its own authorized access” and stressed that “Flock has not been involved in or informed of this.”

Indeed, Flock Safety has shied away from expanding its tech beyond reading license plates and identifying the makes and models of vehicles the cameras are used to surveil.

To be clear, there is no evidence that any law enforcement agency has yet bought into VIDIZMO’s technology. But given how many are already using Flock’s license plate readers, the temptation to enhance its ability to track people during its daily travel could prove impossible to resist.

This could lead to a slew of problems and constitutional abuses. Facial recognition has shown myriad flaws, chief among them misidentification. Several algorithms produced false matches for Asian and black American faces 10 to 100 times more often than for white faces in one-to-one tests, according to a National Institute of Standards and Technology study.

The errors worsen when officers feed blurry store-camera photos into the software instead of clearer images. There have been several instances of innocent people being arrested after being falsely identified by the technology.