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Facial recognition Tool Wrongly Labelled 2,200 people as Criminals

Welsh police has come under fire after it emerged it used faulty face-recognition technology to spot criminals during the 2017 Champions League final. Over 2,000 people were mistakenly flagged up as criminals, The Guardian found.

Law enforcers in South Wales started trialling face-recognition tools in June 2017: the technology scanned the face of passersby and immediately compared them against a database of known offenders.

When the technology was deployed during the football event in Cardiff, it singled out 2,470 — out of a crowd of about 170,000— as potential criminals. It has now emerged that 92 percent (2,297 people) were later discovered to be “false positives.”

South Wales police, though, has defended its system,  explaining that now arrest was carried out due to a wrong match.

“Over 2,000 positive matches have been made using our ‘identify’ facial recognition technology, with over 450 arrests. Successful convictions so far include six years in prison for robbery and four-and-a-half years imprisonment for burglary. The technology has also helped identify vulnerable people in times of crisis,” a spokesman said.

“Technical issues are common to all face recognition systems, which means false positives will be an issue as the technology develops. Since initial deployments during the European Champions League final in June 2017, the accuracy of the system used by South Wales police has continued to improve.”

The force chalked up the high number of mismatches on “poor quality images” and on the fact that the Champions League final was the first major deployment of the tool. Police plans to use face-recognition tools especially during events attracting larghe crowds, which are more vulnerable to terror attacks.

 

“We need to use technology when we’ve got tens of thousands of people in those crowds to protect everybody, and we are getting some great results from that,” chief constable, Matt Jukes told the BBC.

“But we don’t take the use of it lightly and we are being really serious about making sure it is accurate.”

 

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