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AI图鉴首页 › AI 资讯 › 警方正在利用人工智能拦截驾驶员的可疑行为
文章 URL:https://gizmodo.com/Police-re-using-ai-to-pull-over-drivers- for-susident-behavior-2000831220 评论 URL:https://news.ycombinator.com/items?id= 互联网档案馆的存檔,存档日期2013-12-02.
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Automated license plate readers (ALPRs) aren’t just helping police investigate crimes anymore. They’re now being used to flag drivers for supposedly “suspicious” driving patterns.
The American Civil Liberties Union (ACLU) sounded the alarm Monday in a blog post on Monday, warning that law enforcement agencies across the United States are increasingly using license plate readers and AI-powered tools to pull over drivers even if they aren’t suspected of having committed a specific crime.
The post opens with the story of Grace Knowles, a woman in her 20s from northern Virginia who took a road trip through Oregon, Texas, and Louisiana in September 2025. On her way to Florida, she was pulled over by an officer who claimed she had spent too much time driving in the left lane.
The officer questioned Knowles about her travels and asked for proof that she had been in New Orleans. He eventually identified himself as a special agent with the Federal Bureau of Investigation (FBI) that was on a project for human and drug trafficking. He told her that her license plate had been flagged for suspicious travel patterns.
After she convinced him she was just on a road trip, he offered to show her what he was looking at on a computer in his car.
“It was basically a heat map of the U.S., and I could see different circles where I’d been, and when he clicked on it, it was a photo of my license plate,” Knowles told the ACLU.
When she asked how authorities had collected images of her license plate, the officer told her the cameras were everywhere, including on top of highway signs.
The ACLU warns that encounters like Knowles’ could become more common.
“For many people, those encounters will be far more fraught, frightening and dangerous than what Knowles experienced,” wrote Jay Stanley, a senior policy analyst with the ACLU.
ALPRs facing growing pushback nationwide
The warning comes as ALPRs are already facing growing backlash.
Companies like Flock Safety and Axon have become known in recent years for selling ALPR systems to law enforcement, which scan license plates as vehicles pass, collecting vehicle information along with the time and location they were spotted. Police can then search that data during investigations.
Privacy advocates, however, warn that the cameras collect location data on millions of people who are not suspected of crimes, often without a warrant, probable cause, or reasonable suspicion. There have also been reports of the systems leading to mistakes and rampant misuse by law enforcement.
An August YouGov survey found that 46% of respondents opposed law enforcement using the technology in their communities, while 38% supported it.
Law enforcement agencies around the country, including the Los Angeles Police Department, have suspended or even ended their Flock contracts amid the growing backlash.
Knowles’ story is far from the only case raising concerns about how police are using license plate data.
In March, The Markup reported that a California grandmother was questioned by U.S. Customs and Border Protection (CPB) officers about how often she visited local casinos. In another case, a man was targeted for a traffic stop after repeatedly driving back and forth between Wisconsin and Michigan, which local police described as “a known source State for Marijuana.”
Earlier this month, a federal jury in Texas sided with a man who sued over what his attorneys described as an “unconstitutional traffic stop scheme” enabled by “AI-powered” license plate readers. According to the lawsuit, he was pulled over after his license plate was flagged for driving from Houston to Carrizo Springs, staying overnight, and returning home the following day.
Meanwhile, WIRED reported this month that Flock had developed an AI-powered investigative tool that “can identify drivers and track vehicles by their patterns of movement alone.”
Flock did not immediately respond to a request for comment.
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