2024-02-15 07:00:00
Thousands of people using the London Underground saw their movements, behavior and body language monitored by artificial intelligence surveillance software designed to see if they were committing crimes or in unsafe situations, new documents obtained by WIRED reveal. From the report:Machine learning software was combined with live CCTV footage to try to detect aggressive behavior and brandished weapons or knives, as well as look for people falling onto subway tracks or dodging fares. From October 2022 to the end of September 2023, Transport for London (TfL), which operates the city’s tube and bus network, tested 11 algorithms to monitor people passing through Willesden Green tube station, in the northwest of the city. The proof of concept is the first time the transport agency has combined artificial intelligence and live video footage to generate alerts that are sent to frontline staff. More than 44,000 alerts were issued during the test, of which 19,000 were delivered to station staff in real time.
Documents sent to WIRED in response to a Freedom of Information Act request detail how TfL used a wide range of computer vision algorithms to track people’s behavior while they were at the station. It is the first time that full details of the trial have been reported, and comes after TfL said in December that it will expand its use of AI to detect fare evasion to more stations across the British capital. In the trial at Willesden Green, a station that had 25,000 visitors a day before the Covid-19 pandemic, the AI system was set up to detect potential safety incidents and allow staff to help people in need, but also targeted to criminals and antisocial behavior. Three documents provided to WIRED detail how AI models were used to detect wheelchairs, strollers, vapers, people entering unauthorized areas or putting themselves in danger by approaching the edge of train platforms.
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