Network Rail did not respond to questions about the trials from WIRED, including questions about the current state of operate of artificial intelligence, emotion detection and privacy concerns.
“We take the security of the rail network very seriously and use a range of advanced technologies at our stations to protect passengers, our colleagues and rail infrastructure from crime and other threats,” says a Network Rail spokesman. “When deploying technology, we work with police and security services to ensure we take proportionate action and always comply with relevant laws regarding the use of surveillance technology.”
It’s unclear how widely emotion detection analysis has been used, with documents sometimes stating that the operate case “should be approached with greater caution” and station reports saying that “accuracy cannot be verified.” However, Gregory Butler, chief executive of data analytics and computer vision company Purple Transform, which worked with Network Rail on the trials, says the feature was disabled during testing and that no images were saved while it was dynamic.
Network Rail’s AI trials documents describe a number of operate cases where it is possible for cameras to send automatic alerts to staff when certain behavior is detected. None of the systems operate the controversial facial recognition technology, which aims to match people’s identities to those stored in databases.
“The main benefit is faster detection of intrusion incidents,” Butler says, adding that his company’s SiYtE analytics system is used in 18 locations, including train stations and along tracks. Butler says five stern incidents of trespassing were discovered at two locations last month, including a teenager picking up a ball from the tracks and a man who “spent more than five minutes picking up golf balls on a high-speed rail track.” line.”
At Leeds railway station, one of busiest outside London350 CCTV cameras are connected to the SiYtE platform, says Butler. “Analytics are used to measure people flow and identify issues such as platform congestion and, of course, trespassing, where technology can filter out track workers through their PPE uniforms,” he says. “Artificial intelligence helps operators who cannot constantly monitor all cameras to quickly assess and respond to security threats and issues.”
Network Rail documents show that cameras used at one station, Reading, have allowed police to speed up bicycle theft investigations by being able to locate bikes in the footage. “It was determined that while the analytics cannot detect theft with certainty, it is capable of detecting a person on a bicycle,” the filing reads. They also add that the new air quality sensors used in the trials could save staff time in carrying out manual inspections. One instance of artificial intelligence uses sensor data to detect “sweating” floors that have become slippery due to condensation and alert staff when they need to be cleaned.
While the documents detail some elements of the trials, privacy experts have raised concerns about a general lack of transparency and debate about the use of artificial intelligence in public spaces. In one of the documents produced to assess data protection issues in Hurfurt’s systems, Big Brother Watch states that there appears to be a “dismissive attitude” towards people who may have privacy concerns. One asks a question: “Could some people object or find it intrusive?” The employee writes, “Usually no, but for some people there is no accounting.”
At the same time, similar AI surveillance systems that use this technology to monitor crowds are increasingly being deployed around the world. During the Olympic Games in Paris, France later this year, AI video surveillance will watch and try to do just that with thousands of people Capture crowd waves, weapon operate, and abandoned items.
“Systems that don’t identify people are better than those that do, but I worry about a slippery slope,” says Carissa Véliz, associate professor of psychology at the Institute for Ethics in Artificial Intelligence at the University of Oxford. Véliz points to similar AI attempts on the London Underground, which initially blurred the faces of people who might have avoided tickets, but then changed their approach, removing the blurred photos and storing them longer than initially planned.
“There is a very instinctive need to expand surveillance,” says Véliz. “People like to see more and see further. But surveillance leads to control, and control leads to a loss of freedom that threatens liberal democracies.”