The Metropolitan Police is using facial recognition technology to identify London’s most prolific shoplifters as retail crime soars.
The initiative was announced as data released by the Office for National Statistics showed shoplifting offences recorded by police forces in England and Wales rose by 25 percent in the past year.
The ONS said 365,164 shoplifting offences were recorded in the year to June 2023, up a quarter on the previous 12 months.
On Thursday—24 hours after meeting with retail leaders to discuss how to tackle the problem—the commissioner of the Metropolitan Police, Sir Mark Rowley, announced detectives had been using facial recognition software to identify the capital’s most prolific shoplifters.
At the end of September the Met wrote to 12 leading retailers asking them to send CCTV images of their 30 most prolific but unidentified offenders.
A specialist team has begun using facial recognition technology to match facial features from the stores’ CCTV footage against photographs in the force’s custody image database.
149 Suspects Identified
The Met said: “Within a matter of days, 149 suspects had been identified from 302 CCTV stills. Some are wanted for more than one offence. Local officers will now work with the stores to build a case and track the suspects down.”Retail crime is responsible for an estimated £1.9 billion loss of revenue in London each year and there were more than 1,000 cases of abuse and violence against staff reported annually in the capital.
She said there were also an increasing number of TikTok videos which encouraged mass theft and even handed out shoplifting tips.
In response to political and commercial pressure, the Met appears to be upping its game.
‘Results so far are Game-Changing’
“The results we’ve seen so far are game-changing. The use of facial recognition in this way could revolutionise how we investigate and solve crime.”“What’s most powerful is what we’ve learned about those involved in this offending so far. It’s clear the majority are career criminals involved in serious crime. This data and information helps us focus our efforts in an even more precise way than we originally anticipated,” he added.
The chief executive of the Association of Convenience Stores, James Lowman, welcomed the use of facial recognition but said there were still delays in getting offenders off the streets.
Mr. Lowman said: “Using artificial intelligence to identify prolific offenders can be an effective way of drastically reducing the amount of police time it takes to make links between crimes committed against different businesses locally.”
“Whether its artificial intelligence or local intelligence that leads to criminals being identified, the real challenge remains apprehending these offenders and getting them off the streets,” he added.
But Emmanuelle Andrews, from human rights charity Liberty, was adamantly opposed to the idea.
She said: “Facial recognition has no place on our streets, in our shops, or in any other areas of our lives. This technology threatens our privacy and stifles free speech, and we should all be worried about moves to expand its reach.”
Ms. Andrews said: “We’re also concerned about the creep of facial recognition technology into other areas of policing. Let’s be clear: we cannot rely on tech to solve deep societal problems, this is an unjustified expansion of state surveillance and there are numerous alternatives.”
