Beyond License Plates: How U.S. Surveillance Networks Are Capturing Political Affiliations and Personal Details

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Automatic License Plate Recognition Systems Are Compiling a Nationwide Database Extending Beyond Vehicle Tracking

On the morning of December 4 of the previous year, at 8:22 am, a vehicle equipped with license plate scanning technology was capturing images of other cars as it navigated through a quiet neighborhood street in Alabama. Among the collected images was one that, interestingly, did not feature a car or a license plate but instead captured a vivid red “Trump” political sign positioned in front of a house’s garage. This particular photo also included a backdrop with an Israel-related banner, a decorative Christmas wreath, and a cheerful inflatable snowman.

A separate photograph captured on another occasion by a different mode of transport depicts a placard endorsing "Steelworkers for Harris-Walz" prominently displayed on the grass outside a residence. In close proximity to another sign promoting Harris, a construction worker, whose face is clearly visible, is seen. Additional images document vehicles throughout the United States adorned with stickers showing support for or disdain towards Trump and Biden, with some explicitly bearing the phrase “Fuck Biden”. Furthermore, an image from November 2023 captures a bumper sticker partially ripped, which had shown support for the Obama-Biden ticket.

The photographs were produced by artificial intelligence-equipped cameras installed on vehicles, originally created to photograph vehicle registration plates. However, they have shifted focus and are now capturing images of political signs on residential lawns, people donning text-emblazoned T-shirts, and cars with pro-abortion messages on bumper stickers, all the while logging the exact positions of these sightings. Recent data analyzed by WIRED reveals the transformation of a device initially aimed at overseeing traffic into a mechanism that monitors expression safeguarded by the First Amendment of the US Constitution.

High-resolution images appeared in the output generated by DRN Data's search algorithms, a company specializing in license plate recognition (LPR) technology and a subsidiary of Motorola Solutions. This LPR technology finds application among private detectives, asset recovery specialists, and insurers; likewise, Vigilant, another Motorola-associated enterprise, provides law enforcement agencies with access to identical LPR information.

Nonetheless, documents provided to WIRED by artist Julia Weist, as she chronicles limited-access datasets in her projects, reveal the capability for individuals with access to the License Plate Recognition (LPR) system to conduct searches using widely recognized words or names, including those of public officials. These searches yield images where the search keywords appear, even when they are not visible on vehicle license plates.

A query for Delaware vehicle license plates featuring the word "Trump" yielded over 150 photos, capturing residential areas and vehicles' rear stickers. Every image displayed carries information on the specific date, time, and location where it was snapped.

Weist mentions, "When I looked up 'believe,' what I found was entirely composed of yard signs. It included images of things like slogans painted on roadside planters, and even a person donning a hoodie with 'Believe' emblazoned on it." He adds, "Upon searching for 'lost,' the results were predominantly missing pet posters people hang up for their lost dogs and cats."

The study underscores the extensive scope of License Plate Recognition (LPR) technology, which has amassed a vast collection of billions of license plate images. It further illustrates how individuals' political beliefs and residential locations are being cataloged into large databases that are accessible for search.

Jay Stanley, a senior policy analyst at the American Civil Liberties Union, highlights how this situation uncovers the widespread nature of surveillance throughout America's tranquil streets. He points out that the monitoring goes beyond just recording license plates, encompassing a broad range of data that could disclose significant details about individuals.

In a communication to WIRED, DRN stated it adheres to "every relevant legal and regulatory requirement."

Massive Volume of Images

Systems that recognize license plates typically start by taking a photo of a car. They then apply optical character recognition (OCR) technology to detect and pull out the license plate's text from the photo. Owned by Motorola, DRN markets several types of cameras for recognizing license plates: one is a stationary camera that can be installed beside roads to identify a car's make and model, and record images of cars moving as fast as 150 mph; another is a "quick deploy" camera that can be fixed to buildings to keep an eye on vehicles at those locations; and there are also portable cameras that can be placed on dashboards or attached to vehicles to take pictures while on the move.

For over ten years, DRN has collected over 15 billion instances of "vehicle sightings" throughout the U.S., and according to its promotional content, it continues to gather over 250 million new sightings each month. While DRN's commercial database, accessible through its Vigilant system, is made available to law enforcement agencies, the data collected by police are not contributed to the broader database.

The network operates with the help of DRN "partners" who equip their vehicles, including tow trucks, with cameras to record license plate numbers while on the move. A single vehicle may be outfitted with as many as four cameras, ensuring coverage from multiple directions. These partners are rewarded with monthly incentives and may also benefit from complimentary cameras and credits for searches.

In 2022, Weist achieved certification as a private detective in the state of New York, opening up opportunities for her to utilize the extensive surveillance tools available to private investigators. Among the tools she gained access to was the DRN's analytics platform, DRNsights, offered as part of a service package by the investigative firm IRBsearch. However, following the publication of an opinion piece by Weist outlining her activities, IRBsearch reviewed her account and subsequently terminated it. The firm remained silent when WIRED reached out for a statement.

Weist highlights a distinction between publicly available resources such as Google Street View and searchable content. In her research, Weist executed numerous searches using words and well-known phrases, uncovering information that extended well beyond vehicle registration numbers. The data she provided to WIRED showed that a query for “Planned Parenthood” produced images of stickers related to the reproductive health services provider, found on cars, bumpers, and windows, displaying both support and opposition. Advocates for civil liberties have expressed worries about the potential misuse of data from license plate readers against individuals pursuing abortion services.

Weist expresses worry over the potential misuse of search technologies amidst a rise in societal political unrest and division. Although it doesn't involve license plate information, a law enforcement officer in Ohio was reported suggesting that individuals note the home addresses of those who have yard signs for Vice President Kamala Harris, who is the Democratic nominee for the 2024 presidential election. This illustrates the dangers of having a database that allows for the search of citizens' political leanings.

In 2016, an investigation by the Associated Press uncovered extensive abuse of secret police databases by officers across the country. Then, in 2022, WIRED reported that numerous employees and contractors of US Immigration and Customs Enforcement were probed for misusing various databases, such as License Plate Reader systems. The accusations detailed in these investigations varied from surveillance and harassment to the distribution of information to lawbreakers.

People often display signs on their lawns or stickers on their vehicles to share their opinions and possibly sway the beliefs of others. Stanley from the ACLU points out that this is done for visibility among individuals, not for recognition by technology. "They might aim to communicate their thoughts within their local area, to the people nearby, rather than being recorded in a vast national database open to law enforcement," Stanley explains.

Weist argues that the system should, at a minimum, be capable of excluding images that lack license plate information, without errors. "It's unacceptable for it to happen even once, particularly when it's misidentifying things such as individuals' clothing or signs on their lawns," Weist states.

"Jeremiah Wheeler, president of DRN, states that technology for recognizing license plates aids in enhancing public safety and community services. This includes locating kidnapped children and retrieving stolen cars, as well as facilitating toll payments and reducing insurance costs by preventing insurance scams."

Weist is of the opinion that due to the low occurrence of images featuring bumper stickers in contrast to the high prevalence of vehicles sporting them, it's possible that Motorola Solutions is trying to exclude images that display bumper stickers or any other form of text.

Wheeler did not reply to inquiries from WIRED regarding the existence of search restrictions within license plate databases, the rationale behind the appearance of homes featuring yard signs without any visible cars in the search outcomes, or the employment of any mechanisms to minimize such instances.

"Wheeler states that DRNsights adheres to all relevant legal requirements and standards. He explains that the DRNsights platform grants access to license plate data and related vehicle details which are collected in public areas and openly visible. However, this access is limited to clients who have legally permissible reasons, and any violators will lose their access privileges."

Ubiquitous AI

In recent times, the use of systems capable of recognizing license plates has seen a significant increase, driven by advancements in camera technology and the enhancement of machine-learning algorithms. Examples of such systems include DRN and its competitor Flock, illustrating a shift in surveillance methods employed across urban and suburban areas.

More and more, AI technology is being integrated into security cameras to track individuals' activities and potentially identify their feelings. These advanced systems could notify authorities, who might not have the capacity to watch surveillance video non-stop, about significant occurrences. Nonetheless, the effectiveness of using number plate recognition in curbing criminal activities remains debatable.

Dave Maass, the director of investigations at the Electronic Frontier Foundation, a civil liberties organization, comments that the presentation of license plate reader technology by governmental bodies or private entities tends to be misleading. They suggest that its use is limited to tracking down criminals, car thieves, or individuals linked to amber alerts. However, Maass clarifies that this description doesn't accurately reflect the technology's operation. Instead, it gathers and retains data from all individuals, frequently for extended durations.

As technology advances, its capabilities could expand significantly. Maass, an expert in license-plate-recognition technologies, mentions that firms are exploring "vehicle fingerprinting." This innovative approach aims to identify a vehicle's make, model, and manufacturing year through its design, as well as to detect any existing damage. According to DRN's promotional materials, a future enhancement is expected to enable insurance providers to ascertain whether a vehicle is being utilized for ride-sharing services.

"The design of the nation's framework aims to shield the populace from excessive governmental interference. However, there seems to be insufficient measures to safeguard individuals against private entities focused on profit-making," stated Nicole McConlogue, an associate professor of law at the Mitchell Hamline School of Law, who has conducted studies on license-plate-surveillance systems and their likelihood to foster discrimination.

McConlogue highlights the scale at which vehicles traverse streets to gather images as particularly concerning. He points out that this practice not only reflects the goals of those who are compiling the information but also perpetuates the historical consequences of segregation and redlining in the U.S., which have significantly shaped neighborhood demographics.

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