One of the country's widely used facial recognition software, used by many convenience stores, has reportedly wrongly identified an innocent customer as a thief.
According to media reports and BBC’s Newsnight programme, an unidentified woman was incorrectly flagged by the Facewatch software while she was shopping at variety store chain Home Bargains.
The woman told BBC’s Newsnight programme that she had her bag searched, was walked out of the shop and told that she was banned from all stores that used the technology.
She told the BBC, “I was just crying and crying the entire journey home … I thought, ‘Oh, will my life be the same? I’m going to be looked at as a shoplifter when I’ve never stolen.’ ”
Facewatch is a facial recognition company that provides a cloud-based facial recognition security system to safeguard businesses against crime. The company later said to have wrote the woman and acknowledged it had made an error, BBC reported.
Facewatch is widely used in stores across the UK, including convenience stores such as Budgens and Costcutter.
Meanwhile, the UK police is pushing facial recognition techniques as next big thing in policing though there are fears that surveillance is more intensely focused on minorities and on those who are disadvantaged socioeconomically.
Earlier this year, a privacy rights group claimed that facial recognition cameras installed by a supermarket chain to tackle shoplifting disproportionately target people in poorer areas. Southern Co-op, which uses Facewatch live recognition cameras in 34 branches, typically has shops in richer-than-average neighbourhoods. But just five of the stores in which it uses Facewatch are in the richest third of neighbourhoods in England, while 14 are in the poorest.
Jake Hurfurt, the head of research at Big Brother Watch, alleged that AI supermarket surveillance is being directed at poorer communities, who are more likely to suffer excessive invasions of their privacy and unfair treatment as a result.
The charities also claim that facial recognition technology "notoriously misidentifies people of colour, women and LGBTQ+ people", meaning that already marginalised groups are more likely to be subject to an invasive stop by police, or at increased risk of physical surveillance, monitoring and harassment.
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