Guilty until proven innocent: shoppers falsely identified by facial recognition system struggle to clear their names

"Ian Clayton was stunned when approached by a staff member and asked to leave the shop due to being flagged as a shoplifter by Facewatch. He was left outside with no explanation and a QR code to scan."

"Facewatch claims a 99.98% accuracy rate and sent over 50,000 alerts to various retailers. However, those wrongly identified report a lack of support and unclear complaint processes."

"Clayton faced difficulties in addressing the false accusation, as the Facewatch contact number led to a message stating they do not take calls, forcing him to email instead."

"After submitting a subject access request, Clayton discovered he had been incorrectly linked to a previous shoplifting incident, feeling as though he was guilty until proven innocent."

Ian Clayton was falsely accused of shoplifting by Home Bargains due to a facial recognition system called Facewatch. Despite the system's claimed 99.98% accuracy, many individuals have been wrongly identified and faced no support or clear complaint processes. After being ejected from the store, Clayton struggled to find a way to address the error, ultimately needing to submit a data protection request to uncover the mistake. This experience highlights the challenges and potential injustices associated with the use of such technology in retail settings.

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