Toronto police should stop using facial recognition technology or face the prospect of class-action lawsuits, says the head of the Canadian Civil Liberties Association.

Michael Bryant on Thursday called on the Toronto Police Services Board to place a moratorium on the use of the technology, “because it renders all of us walking ID cards.”

He called the use of the technology “carding by algorithm, and notoriously unreliable,” and, in a written statement, likened it to police “fingerprinting and DNA swabbing everybody at Yonge and Bloor during rush hour” and running the results through databases.

Continued use of the technology leaves the board open to lawsuits and, at the very least, requires formal oversight, Bryant said.

Toronto police Deputy Chief James Ramer told the board the use of the technology is nothing like the controversial practice of carding. “It’s not indiscriminate, it’s not random,” he said. “It’s very specific.”

The technology saves victims of crimes from having to go through police mugshot databases, Ramer said.

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On Thursday, the police board passed a motion to receive Chief Mark Saunders’ report on the use of the technology and the deputations from Bryant and others.

As reported earlier this week by the Star, Toronto police have been using facial recognition technology driven by artificial intelligence for more than a year. Police say it’s an efficient tool that has led to arrests in major crimes, including homicides.

But it also comes with criticisms that the technology is an invasion of privacy and overreach by police and state. San Francisco, a tech-centric city, recently banned the tool.

A London, U.K., policing ethics panel this month concluded that the technology should not be used if police can’t prove it works equally well with people of all ethnic and racial backgrounds and women.

The panel, set up to advise London city hall, noted there are “important ethical issues to be addressed” but concluded that does not mean the technology should not be used at all, reported The Guardian.

Research has shown that differences in race and gender can lead the technology to return false positives. Some systems kick out higher false-positive rates for Black women, compared to white men.

Toronto police ran 1,516 facial recognition searches using about 5,000 still and video images between March and December of last year, according to Saunders’ report to the board.

They were cross-checked against the service’s mugshot database of 1.5 million individuals, resulting in matches in about 60 per cent of the searches. Of those, 80 per cent of the matches resulted in identifying criminal offenders.

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There is no count available for how many led to arrests, since the technology identifies potential matches that must be further investigated further using other police methods.

Toronto police said they have no plans to extend matches beyond the mugshot database, and that real-time facial recognition, such as searching faces in crowds, is not being used.

The technology was used in the investigation into the Gay Village serial murders to help determine the identity of one of the victims.

With files by Kate Allen

Wendy Gillis is a Toronto-based reporter covering crime and policing. Reach her by email at wgillis@thestar.ca or follow her on Twitter: @wendygillis

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