Amazon-powered AI camera used to detect emotions in unknowing UK train passengers

Network Rail did not respond to questions about the trial sent by WIRED, including questions about its use of AI, emotion detection and privacy concerns.

A Network Rail spokesperson said we take the security of our rail network very seriously and use a range of advanced technologies across our stations to protect passengers, colleagues and rail infrastructure from crime and other threats. When deploying technology, we work with police and security services to take appropriate measures and always comply with applicable laws regarding the use of surveillance technology.

It is unclear how widely emotion detection analytics have been deployed. Sometimes the documentation says use cases need to be looked at more carefully, and stations have reported that it is impossible to verify accuracy. But Gregory Butler, CEO of data analytics and computer vision company Purple Transform, which has been working with Network Rail on the trial, said the feature was broken during testing and no images were saved when enabled.

Network Rail's document on AI trials describes a number of use cases involving the potential to send automated alerts to staff when cameras detect certain behaviour. Neither system uses controversial facial recognition technology, which aims to match people's identities with those stored in a database.

Butler added that his company's analytics system, SiYtE, is being used at 18 sites, including train stations and tracksides. Butler said there have been five serious break-ins detected by the system at two sites over the past month. They include a teenager picking up a ball on a track and a man spending more than five minutes picking up a golf ball along a high-speed line. .

Leeds train station, the busiest outside London, has 350 CCTV cameras connected to the SiYtE platform, Butler says. Analytics are used to measure the flow of people and identify issues such as platform crowding and, of course, trespassing, where technology can filter out tracking workers through their PPE uniforms. AI can help operators who cannot continuously monitor all cameras quickly assess and resolve safety risks and issues.

According to a Network Rail document, cameras used at one station, Reading, allowed police to pinpoint bicycles in the footage, speeding up investigations into bicycle thefts. The analysis showed that although the theft could not be reliably detected, the person in possession of the bicycle could be detected. They also added that the new air quality sensors used in the trials will save staff time on manual checks. One AI instance uses data from sensors to detect sweaty floors that have become slippery due to condensation and alerts staff when they need cleaning.

Although the document details some elements of the trial, privacy experts say they are concerned about the overall lack of transparency and debate about the use of AI in public spaces. In a document designed to assess the system's data protection issues, Big Brother Watch's Hurfurt said there appeared to be a dismissive attitude towards people with privacy concerns. One question is: Are some people likely to find it intrusive or opposed to it? One employee wrote: Generally not. However, there is no explanation for some people.

At the same time, similar AI surveillance systems that use this technology to monitor crowds are increasingly being used around the world. During the Paris Olympics later this year, AI video surveillance will monitor thousands of people and try to spot crowd surges, use of weapons and abandoned objects.

Systems that don't identify people are better than ones that do, but I worry about a slippery slope, says Carissa Vliz, associate professor of psychology at the University of Oxford's Institute for AI Ethics. Vliz points to a similar AI experiment on the London Underground that first blurred the faces of people evading fares, and then she changed her approach, keeping the images in place longer than originally planned without blurring the photos.

There is a very instinctive drive to expand surveillance, Vliz says. Humans like to see more and farther. However, surveillance leads to control, and control leads to loss of freedom that threatens liberal democracy.

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