These images were generated by AI-powered cameras mounted on cars and trucks, initially designed to capture license plates, but which are now photographing political lawn signs outside private homes, individuals wearing T-shirts with text, and vehicles displaying pro-abortion bumper stickers—all while recording the precise locations of these observations. “When government or private companies promote license plate readers, they make it sound like the technology is only looking for lawbreakers or people suspected of stealing a car or involved in an amber alert, but that’s just not how the technology works,” says Dave Maass, the director of investigations at civil liberties group the Electronic Frontier Foundation. Wheeler did not respond to WIRED's questions about whether there are limits on what can be searched in license plate databases, why images of homes with lawn signs but no vehicles in sight appeared in search results, or if filters are used to reduce such images. While not linked to license plate data, one law enforcement official in Ohio recently said people should “write down” the addresses of people who display yard signs supporting Vice President Kamala Harris, the 2024 Democratic presidential nominee, exemplifying how a searchable database of citizens’ political affiliations could be abused. However, files shared with WIRED by artist Julia Weist, who is documenting restricted datasets as part of her work, show how those with access to the LPR system can search for common phrases or names, such as those of politicians, and be served with photographs where the search term is present, even if it is not displayed on license plates. Weist says the system, at the very least, should be able to filter out images that do not contain license plate data and not make mistakes. A search result for the license plates from Delaware vehicles with the text “Trump” returned more than 150 images showing people’s homes and bumper stickers. License-plate-recognition systems, broadly, work by first capturing an image of a vehicle; then they use optical character recognition (OCR) technology to identify and extract the text from the vehicle's license plate within the captured image. “License plate recognition (LPR) technology supports public safety and community services, from helping to find abducted children and stolen vehicles to automating toll collection and lowering insurance premiums by mitigating insurance fraud,” Jeremiah Wheeler, the president of DRN, says in a statement. Beyond highlighting the far-reaching nature of LPR technology, which has collected billions of images of license plates, the research also shows how people’s personal political views and their homes can be recorded into vast databases that can be queried. Weist believes that, given the relatively small number of images showing bumper stickers compared to the large number of vehicles with them, Motorola Solutions may be attempting to filter out images containing bumper stickers or other text. Motorola-owned DRN sells multiple license-plate-recognition cameras: a fixed camera that can be placed near roads, identify a vehicle’s make and model, and capture images of vehicles traveling up to 150 mph; a “quick deploy” camera that can be attached to buildings and monitor vehicles at properties; and mobile cameras that can be placed on dashboards or be mounted to vehicles and capture images when they are driven around. From Trump campaign signs to Planned Parenthood bumper stickers, license plate readers around the US are creating searchable databases that reveal Americans’ political leanings and more. While people place signs in their lawns or bumper stickers on their cars to inform people of their views and potentially to influence those around them, the ACLU’s Stanley says it is intended for “human-scale visibility,” not that of machines. “The DRNsights tool allows authorized parties to access license plate information and associated vehicle information that is captured in public locations and visible to all.
This Cyber News was published on www.wired.com. Publication date: Thu, 03 Oct 2024 11:13:05 +0000