AI Facial Recognition Technology Brings Airport-Style Security to UK Stores, Says Human Rights Group
A growing number of UK stores are implementing a facial recognition system powered by artificial intelligence (AI) to identify repeat shoplifters. This move has been criticized by a human rights group, which claims it represents the spread of airport-style security on the high street. The technology, developed by UK surveillance company Facewatch, has seen exponential demand as incidents of shoplifting and violence in stores have increased in recent years.
The system functions as follows: when a store manager discovers a stolen item, they review the footage recorded by security cameras to identify the thief. Subsequently, the manager logs into Facewatch’s system, which has captured video of all the customers who entered the store that day, to locate the suspect in their footage and record the incident. Once logged, the system sends an alert to the manager’s phone every time the same person attempts to enter the store again, allowing them to either ask the person to leave or closely monitor them.
Facewatch employs human super-recognizers to double-check if the suspect’s face matches those in the firm’s database of offenders. In cases where the suspect is a prolific offender or has stolen items worth over £100 ($131), their biometric data may be shared with neighboring stores utilizing Facewatch’s system.
Human rights groups argue that this type of technology infringes on people’s right to privacy and is prone to errors. Madeleine Stone, senior advocacy officer at Big Brother Watch, a UK civil liberties campaign group, stated that technology like Facewatch normalizes airport-style security for mundane activities such as buying groceries, likening the recording of shoppers’ biometric data to collecting their fingerprints or DNA samples just to enter a store.
Simon Gordon, founder of Facewatch, claims that the system was 99.85% accurate last month in identifying repeat offenders. However, errors occasionally occur, leading to innocent individuals being flagged as offenders. In such cases, the person can file a complaint with Facewatch, and their information will be promptly deleted from the system.
Although the system is legal in the UK, Stone argues that people should not be obligated to prove their innocence proactively. She also highlights the potential for bias in AI-powered software, which could result in individuals being wrongly placed on watchlists and encountering significant disruptions in their lives.
Gordon maintains that Facewatch’s system is unbiased and relies on human staff trained in facial recognition to support its operations. Despite concerns over AI’s impact on society, especially in terms of privacy intrusion and job displacement, Facewatch is experiencing global demand for its product and is considering expansion into the United States.
Governments worldwide are starting to regulate AI technology. Recently, the European Parliament agreed to ban the use of real-time, AI-powered facial recognition technology in public spaces. The legislation aims to establish rules governing AI usage by companies.
Shoplifting and incidents of violence in stores have risen significantly since the onset of the pandemic, taking a toll on businesses. Retailers incur substantial losses from repeat offenders, leading some to adopt facial recognition technology as a means of safeguarding their staff and protecting their revenue.
While human rights and privacy concerns persist, the effectiveness of AI facial recognition technology in combating theft and violence cannot be ignored. As the debate continues, striking a balance between security and privacy remains essential.
Overall, Facewatch’s system has elicited mixed responses, with its efficiency in tackling crime applauded by some and its potential consequences for privacy and bias decried by others. It is imperative to approach the deployment of AI technology with caution and address the complex social and ethical implications it brings.
