Toronto police have been using facial recognition technology for more than a year — a tool police say increases the speed and efficiency of criminal investigations and has led to arrests in major crimes including homicides.

But the emerging technology — which relies on artificial intelligence — has generated enough privacy and civil liberty concerns that the city of San Francisco, worried about police and state overreach, recently became the first U.S. city to ban the tool.

Toronto police say that facial recognition technology is being used to compare images of potential suspects captured on public or private cameras to its internal database of approximately 1.5 million mugshots.

According to a report submitted by Chief Mark Saunders to the Toronto police services board, the technology is generating leads in investigations, particularly as a growing number of crimes are being captured on video through surveillance cameras. Since the system was purchased in March 2018 — at a cost $451,718 plus annual maintenance and support fees — officers have conducted 2,591 facial recognition searches. The report was submitted in advance of Thursday’s board meeting.

The goal of purchasing the system was to identify suspects more efficiently and quickly, including violent offenders. It will also help police conclude major investigations with fewer resources and help tackle unsolved crimes, Saunders said. Funding for the system was provided through a provincial policing modernization grant.

But critics are wary of facial recognition technology for reasons including its potential to be misused by police or other government agencies as technological advancements outpace oversight.

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“This technology is being put in place without any legislative oversight and we need to hit the pause button,” NDP MP Charlie Angus told the Star on Monday.

The technology is “moving extremely fast,” said Angus, who is examining the ethics of artificial intelligence as part of a House of Commons Standing Committee on Access to Information, Privacy and Ethics.

In San Francisco, city officials banned the use of the technology by police and other agencies earlier this month, citing concerns about potential misuse by government authorities. The city’s police department had previously been using the tool, but stopped in 2017. One of the city legislators told reporters that the move was about having security without becoming a security state.

According to Saunders’ report, Toronto police ran 1,516 facial recognition searches between March and December last year, using approximately 5,000 still and video images. The system was able to generate potential mugshot matches for about 60 per cent of those images. About 80 per cent of those matches led to the identification of criminal offenders.

The total number of arrests the technology has generated is undetermined, the report states, because unlike fingerprint matches, the facial recognition tool only identifies potential candidates and arrests are made only after further investigation produces more evidence.

“Many investigations were successfully concluded due to the information provided to investigators, including four homicides, multiple sexual assaults, a large number of armed robberies and numerous shooting and gang related crimes,” Saunders wrote.

Other jurisdictions have come under fire for using facial recognition on crowds in real-time, such as scanning attendees at major sports events to identify the subjects of outstanding warrants and arrest them on the spot.

In emailed responses to questions by the Star, Staff Inspector Stephen Harris, Forensic Identification Services, said Toronto police have no plans to extend the use of facial recognition technology beyond comparisons to its pre-existing mugshot database. Harris and Saunders both emphasized that Toronto police does not use real-time facial recognition and has no legal authorization to do so.

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Last year, Toronto police used the technology during their investigation into serial killer Bruce McArthur. Investigators located what they believed was a post-mortem image of an unknown man on McArthur’s computer. Hoping to identify him, they used the software and found, within their police database, a mugshot image of Dean Lisowick.

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In documents filed with the courts during the McArthur probe, an investigator notes that there were “undeniable physical similarities” between the two images, including distinctive moles. A relative of Lisowick’s later confirmed the match, and police charged McArthur in Lisowick’s death three days later.

Canadians need to have a discussion about what are legitimate uses of the technology — and what aren’t, said Angus.

Police using the technology to identify someone caught committing a crime on surveillance footage is reasonable, Angus said, but measures need to be put in place to stop what is determined to be unacceptable use, such as real-time monitoring at a rally.

Research has shown that facial recognition technology has racialized false positive rates: some systems are more likely to produce an inaccurate match for Black women than white men, for example.

“This strikes me as particularly important, given all the concerns around carding and other kinds of ethnic and racialized surveillance that have taken place by TPS in the past,” said Chris Parsons, research associate at the University of Toronto’s Citizen Lab.

Asked by the Star about its false positive rate overall and for different racial and ethnic groups, Harris said that Toronto police “does not use facial recognition to make a positive ID. Suspect identifications are only made after further investigation and evidence leads us to that conclusion.”

Civil liberties advocates also appreciated that Toronto police were disclosing details about their facial recognition technology, but wondered why it took so long. The force began a year-long pilot project for the technology in September, 2014, and sent four forensic officers for training at an FBI division in West Virginia before that.

“The fact that there has been very little — virtually no — public conversation about the fact that this is happening, despite the fact that they’ve been looking into it for at least the past five years ... raises questions for me,” says Brenda McPhail, director of the privacy, technology and surveillance project at the Canadian Civil Liberties Association.

“Being open and accountable and transparent about the ways that new surveillance technologies are being integrated into municipal policing is essential to maintaining public trust, and to enable the kinds of conversations that can help Toronto police understand the concerns of city residents.”

Saunders’ report also says that the force conducted a Privacy Impact Assessment for the technology in 2017. The system is only used in criminal investigations, and the only officers with access to it are six FBI-trained personnel. No other databases besides lawfully obtained mugshots are used.

Calgary Police Service was the first Canadian force to begin using the technology. In 2014, it signed a contract for its facial recognition software and said the technology would be used as an “investigative tool” to compare photos and videos from video surveillance against the service’s roughly 300,000 mugshot images.

Asked if images captured by Toronto police’s body-worn cameras could be used with the facial recognition system, Harris said investigators could only do so if a suspect was on camera committing a criminal offence. In that case, investigators would still have to get the court’s permission to use the facial technology during the probe.

The Toronto police board is scheduled to hear discussion of Saunders’ report Thursday.

With Star files

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