待翻译：Flock Has a Powerful New AI Tool for Police. We Got Its Code

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Drawing on a network of cameras that logs the movements of drivers in more than 6,000 communities, the tool can pick out potential witnesses by how often their cars pass through a neighborhood, or surface a driver’s “associates” from the cameras they pass together. Because the system also reaches police case files, 911 dispatch logs, and commercial identity records, those plates can be turned into names, home addresses, and relatives. It can search for people in an area drawn on a map based on nothing more than a physical description. The software, originally called Nightshift and more recently renamed OS Investigate, ships with 69 prewritten prompts that officers can select, review, or edit, and then submit to the AI. Officers can also input prompts of their own. The suggested prompts sit in a cache of more than 450 files that WIRED found on Flock’s own website, served by its login pages to anyone who loaded them. The code describes 45 tools at the AI’s disposal, giving it access to plate scans and camera metadata, arrest records, case files, dispatch logs, ballistics results, and commercial databases that contain Social Security numbers, dates of birth, phone numbers, email addresses, relatives and associates. Flock says it is testing the product with a small group of law enforcement partners and describes it as still in development, with capabilities that may not reflect what it eventually sells. It arrives as the company faces bipartisan political pressure, a growing record of officers caught misusing its platform, and a wave of vandalism that has left cameras sawed off and lenses painted over in cities across the country. Privacy and legal experts say Flock’s tools already raise serious constitutional concerns by giving police broad, often warrantless access to a vast record of people’s movement. But the prompts WIRED examined go further, turning a tool for finding a known vehicle into one that casts suspicion on drivers based on where and how often they drive, regardless of whether they are wanted for a crime. Flock built its business on a simple transaction: A camera photographs a passing car, converts the plate to text, and checks it against a list of vehicles police are looking for. (Cars that are not on the list are recorded and otherwise ignored.) OS Investigate’s preloaded prompts describe an inversion of that arrangement. An officer no longer needs a plate, a name, or a crime to begin: They supply a place, a stretch of time, and a pattern of behavior, and the system is designed to hand back the people who fit. All 69 of the prompts are offered to officers as a menu of canned searches. Selecting one pastes it into a chat box, where the officer can review or edit it before clicking again to submit. One prompt Flock preloaded into the system reads: “Find me witnesses based on vehicles most seen in [neighborhood] during [last 14 days] during [daily timeframe] *(will not include whitelisted vehicles).” An officer would fill in the blanks and submit it. The output is a list of plates, which other tools in the product then convert into names and home addresses. Another prompt instructs the system to list everyone arrested more than twice in two years for “any offense,” exempting only narcotics arrests, and then says to map where those people live, retrieve the calls for service at their homes, and “do a workup on the top three individuals.” The prompt begins with everyone in the area who has an arrest record and ends with dossiers on three of them, chosen by the software. A “workup,” in Flock’s terminology, is a one-command background check. It starts with a name and a date of birth and returns what the department’s records and commercial data hold: vehicles, prior listings as a suspect, and, on a second screen, relatives, phone numbers, and online accounts. 19 of the prompts describe hunting for patterns rather than looking up a record. 14 call for no plate, no name, and no description. The officer simply supplies a location, a window of time, and a behavior. One group of requests asks for vehicles that visited three or more retail locations in a city in three days, or multiple banks in a week, or multiple gas stations between midnight and 5 am. None of the five names a target or an incident. The tool behind those searches carries a filter that strips out buses, semi trucks, work vans, and trailers, so a delivery driver visiting five shops would come off the list, while an ordinary driver making the same rounds remains. The same type of search also applies to travel between cities: vehicles that left one city for another and returned within a week, made repeat roundtrips over 14 days, or passed through three areas in sequence. Flock did not respond to a list of questions about the product and did not dispute the capabilities described in our reporting. Instead, in a statement, spokesperson Paris Lewbel characterized OS Investigate as a separate product from Flock’s license-plate-reader technology, designed to help investigators work across information their agencies already have access to. He said the tool’s capabilities and workflows may change significantly before a broader release. Amid mounting controversy over how police use and abuse its cameras, Flock’s long-held position has been that its technology records plates and not the drivers behind them. Its own public trust pages tell customers that its technology is built for specific, case-based investigations and “not for watching people.” Experts who reviewed the AI tool for WIRED say those assurances are hard to square with what they found in the code. “I think that most people imagine that license-plate readers are checking license plates and they’re looking if a vehicle is wanted. And if it’s not wanted, the police will move along,” says Jay Stanley, a senior policy analyst with the ACLU’s Speech, Privacy, and Technology Project. “But we’re increasingly seeing the aggressive deployment of AI by Flock—and in some ways, like China, very little space between what can be done and what is being done.” One example, for instance, takes a single plate and asks the system to plot the journeys of that car and its “top three associates.” The code describes explicitly how the ranking works: It counts how often other plates appear at the same cameras within a two-minute window of the target by default, and reports back any car that shows up next to it three or more times within a “confidence threshold” defaulting to 0.75. An officer supplies one vehicle and the software finds up to 20. Got a Tip? Are you a current or former police officer, government official, or Flock Safety employee who wants to talk about the company? We’d like to hear from you. Using a nonwork phone or computer, contact the reporters securely on Signal at dmehro.89 and dell.3030. “I don’t know how else to say this, but this sounds completely insane,” says Noel Pichardo, who was briefed on Flock’s technology during a pilot program while serving as a Pawtucket, Rhode Island, police officer and who reviewed the prompts for WIRED. “I don’t know how anyone can argue against the idea that Flock literally tracks people.” Pichardo spoke out against the technology before Rhode Island state lawmakers in 2024, weeks after he served a 30-day suspension for criticizing Flock and department leadership in a local newspaper. The state police chiefs’ association publicly rebuked him days later. Investigations and discipline followed, which he believes were retaliatory, and he resigned as the department moved to fire him. A detective at a California law enforcement agency, granted anonymity because he was not authorized to speak publicly, sees in OS Investigate a tool his department would use. Flock has closed many vehicle theft cases for them, he says, and officers have worked with similar technology for years. “I was not aware of this AI product, but it doesn’t change the way I think about it,” he says. “We’ll use whatever tool is available to solve crime. It isn’t controversial.” The detective said the witness-finding prompts made him slightly uncomfortable, but added, “As law enforcement, we need to use every tool available, in spite of what the ‘defund’ people say.” WIRED analyzed the software by examining code Flock served from its own login portals. Loading those pages returned a user interface for screens that would ordinarily appear only after a police user signed in, letting reporters reconstruct portions of the authenticated applications, their prompts, search fields, tools, and controls, without actual access. The files appeared to contain everything needed to reconstruct the interface from scratch. Before an officer runs a search, the software can ask for a justification. The code shows that by default an officer has to type a reason for the search; however, the form appears to place no requirements on what that reason says or how long it must be. If a department also requires a case number, the form checks only that it contains at least three characters. WIRED could not determine whether Flock applies additional checks on its servers after the information is submitted. WIRED shared its findings with Buchodi, a pseudonymous independent security and privacy researcher who has spent more than a decade reverse engineering consumer software and surveillance technologies. Buchodi examined Flock’s code separately and reproduced key parts of the analysis. References to the tools Flock offers, the data they can apparently reach, and the suggested prompts Flock authored for police are fixed in the code WIRED reviewed. What that code cannot show is how the system behaves in use. It contains no instructions given to the model itself, and it does not reveal what Flock’s servers do with a request once submitted, what they send back, or whether they refuse any command. Flock has said little about the tool in public, but Garrett Langley, its chief executive, once likened it to a crime analyst who is, in his words, “always awake, always watching out for you.” At a demonstration for police chiefs in Denver last year, Langley described the ability to search every camera in a city for cars tailing an armored truck, pulling up the registered owners of those vehicles and checking their arrest records, in under a minute. Investigators who try it, he said, get “addicted.” The company Langley started in Atlanta, where his first camera was a phone in a waterproof box, now logs 20 billion plate scans a month. Andreessen Horowitz, Founders Fund, and other venture firms have poured money into the business, which was valued at $7.5 billion in its most recent funding round. The company’s original tagline was “the first public safety operating system that eliminates crime”—and Langley recently told Vanity Fair that Flock would have solved the disappearance of Nancy Guthrie, Savannah Guthrie’s mother, had its cameras been deployed where she vanished. Flock counts roughly 140,000 monthly active users. At the company’s new Atlanta headquarters, a gold-painted camera covered in signatures commemorates an earlier ritual: marking each additional $1 million in revenue with a new camera. “Now we do more like a million a day,” Langley recently told Vanity Fair. Andrew Guthrie Ferguson, a law professor at George Washington University, says a system like this one was inevitable. “To use all the data collected, you need to build in the ability to query it,” he says. “To make things easier for police officers who are not going to create their own agentic tools, you must preprogram the system with some natural language prompts and automated workflows.” The choice of prompts is what strikes him. “It is not rocket science to figure out [that] police will want to find certain objects or patterns, but it is interesting to see what they preprogrammed,” he says. “There are a lot of innocent activities that could be flagged, even if it also might be quite useful for i [truncated for AI cost control]