More than a Dozen Wrongful Arrests Due to Police Reliance on Facial Recognition Technology
When police arrested Kimberlee Williams, a grandmother living in Oklahoma, because of a warrant from Maryland, she was shocked. She had never been to Maryland in her life.
Ms. Williams later learned that Maryland police had relied on an incorrect result from facial recognition technology that falsely flagged her as a suspect. She is the fourteenth person in the U.S. to join a growing list of people wrongfully arrested because police let flawed facial recognition technology taint their investigations.
Police use of facial recognition technology is dangerous, and stories of people wrongfully arrested because of police reliance on incorrect facial recognition results continue to surface. Today, the ACLU and ACLU of Maryland sent letters to three Maryland police departments on behalf of Ms. Williams, who was wrongfully arrested and jailed for six months because Maryland police relied on a false facial recognition result and concealed their reliance on that unreliable technology from the court when applying for an arrest warrant.
One Woman Arrested for a Crime She Didn't Commit
On June 23, 2021, Ms. Williams was accompanying one of her daughters on a DoorDash delivery to a local military base in Lawton, Oklahoma. When base security at the entry checkpoint conducted a standard identification check, they discovered outstanding Maryland arrest warrants for Ms. Williams and detained her.
These warrants sought Ms. Williams’ arrest for a series of fraudulent over-the-counter cash withdrawals in Maryland in December 2019 and January 2020. An unknown individual had entered SunTrust and Truist bank branches in three different counties, impersonated account holders, and fraudulently withdrew thousands of dollars from those individuals’ accounts.
Ms. Williams, however, was nowhere near Maryland during this time. She was a resident of Oklahoma, living with two of her daughters and their children. While someone was defrauding banks in Maryland, Ms. Williams was in Oklahoma with her family celebrating Christmas and her daughter’s birthday.
At the bank’s headquarters, a financial crimes investigator obtained images of the suspect from security camera footage and sent an image to a national listserv of police and private investigators called Crimedex. Someone on the email list ran the image through facial recognition technology and sent back Ms. Williams’ name and photo as a purported match to the suspect.
In the first county, the bank investigator informed Montgomery County police that Ms. Williams was identified “using facial recognition software” but provided no further information, such as who ran the facial recognition search or how they conducted it. To police in the other two counties, the bank investigator provided even less information, writing that the suspect was “recognized” as Ms. Williams, “a suspect in” the previous Montgomery County investigation.
The detectives made no attempt to establish whether Ms. Williams, an Oklahoma resident, could have been anywhere near Maryland during the relevant period. Her alibi evidence, including social media posts geotagged to Oklahoma, would have shown she couldn’t be the right person. The detectives also ignored other obvious leads: one of the incidents involved a fraudulent check made payable to a name not associated with the bank accounts. Yet there was no investigation of that name. Instead, the police relied only on the facial recognition lead, plus their own visual comparisons of the photos of the suspect and Ms. Williams. They thought the two looked similar.
After she was arrested, Ms. Williams spent a total of six months in jail, first in Oklahoma waiting to be extradited, and then in Montgomery and Prince George’s counties in Maryland. When the last of the charges were finally dropped, Ms. Williams was unceremoniously released onto the street in the middle of December and left to find her way home halfway across the country. She had no phone and no money. Relying on the kindness of strangers, Ms. Williams managed to borrow a phone to contact her family and stay at a nearby hotel before she could return home.
The ordeal turned her and her family’s life upside down, and she is still trying to recover five years later. She lost her job because of the arrest. She also worries that she might unknowingly catch the attention of law enforcement again for a crime she had nothing to do with, causing another ordeal like this one.
Wrongful Arrests Due to Facial Recognition Technology Increase
What happened to Ms. Williams is outrageous and is unfortunately a predictable consequence of police using facial recognition technology. At least thirteen other people are publicly known to have been wrongfully arrested by U.S. police because of reliance on erroneous facial recognition results:
- Nijeer Parks, arrested by police in Woodbridge, New Jersey (February 2019)
- Michael Oliver, arrested by police in Detroit, Michigan (July 2019)
- Robert Williams, arrested by police in Detroit, Michigan (January 2020)
- Christopher Gatlin, arrested by police in St. Louis, Missouri (August 2021)
- Alonzo Sawyer, arrested by Maryland transit police (March 2022)
- Randal Quran Reid, arrested by Georgia police on a warrant issued in Jefferson Parish, Louisiana (November 2022)
- Porcha Woodruff, arrested by police in Detroit, Michigan (February 2023)
- Jason Killinger, arrested by police in Reno, Nevada (September 2023)
- Robert Dillion, arrested on a warrant obtained by police in Jacksonville Beach, Florida (August 2024)
- Javier Lorenzano-Nunez, arrested by police in Phoenix, Arizona (October 2024)
- Trevis Williams, arrested by police in New York City (April 2025)
- Angela Lipps, arrested by U.S. Marshals in Tennessee on a warrant obtained by police in Fargo, North Dakota (July 2025)
- Beau Burgess, arrested by police in Orlando, Florida (August 2025)
When the ACLU sued Detroit police on behalf of Robert Williams in 2021, supporters of police using facial recognition technology characterized his wrongful arrest as an unfortunate but isolated mistake that shouldn’t undermine trust in the technology. But the wrongful arrests have kept coming. It is now impossible to ignore the dangers of facial recognition technology in policing. Indeed, police keep letting the same predictable failures happen again and again.
Facial recognition technology often produces false matches. Part of what is so dangerous about these systems is that when they get it wrong, innocent people who look similar to a suspect are often flagged. That is exactly what facial recognition is designed to do — find similar faces in a database, most or all of whom aren’t actually a match. When facial recognition technology generates false matches to innocent lookalikes, it can taint the investigation by tricking witnesses and police into mistakenly believing they’ve found the suspect.
In several cases, people have been wrongfully arrested after police moved straight from facial recognition results to photo lineups presented to witnesses. When presented with photos containing an image of a person who was chosen by facial recognition technology, surrounded by filler photos who look less like the suspect, witnesses unsurprisingly think they’ve found the culprit. That tainting of lineup identifications has led to the wrongful arrests of at least seven people.
In other cases, including Ms. Williams’, the only confirmation that police obtained was a visual comparison of the suspect photo to the facial recognition result by a law enforcement officer, who was similarly influenced by the technology into thinking they had a match.
Time and time again, police have failed to conduct reliable investigation and ignored obvious reasons to question a facial recognition lead. Many of the people wrongfully arrested had visible differencesto the suspect in the photo: Michael Oliver had full tattoo sleeves, Porcha Woodruff was eight months pregnant, and Trevis Williams was eight inches taller and seventy pounds heavier. In the case leading to Nijeer Parks’ arrest, police didn’t wait for the results of DNA and fingerprint analysis that would have pointed to someone else. And for those who were arrested for crimes far from where they lived — including Kimberlee Williams, Randal Quran Reid, Robert Dillon, and Angela Lipps — police appeared to have not investigated whether they could have even been in the right city or state at the time of the crime.
Without Protections, Facial Recognition Technology Will Keep Tainting Investigations
Despite police department policies and official disclaimers warning officers that facial recognition technology results are not sufficient grounds to arrest someone, police continue letting the technology ruin their investigations. The problems don’t stop there. Multiple studies have shown that facial recognition technology produces higher false match rates for people of color, women, younger people, and the elderly. Unsurprisingly, most of the known wrongful arrests from this technology have been of Black people. But as more stories come to light, including that of Ms. Williams and other white people subjected to false arrests, we are seeing that nobody is safe from having their lives upended by this technology.
These serious dangers call for serious solutions. More than 20 cities and other jurisdictions across the country have banned police from using facial recognition technology at all. In Detroit, under a landmark settlement in Robert Williams’ wrongful arrest case, the police department no longer permits officers to request arrest warrants based on only a photo lineup combined with a facial recognition-based lead. Indiana has enacted a similar protection into state law.
Ms. Williams will never get back the six months she spent in jail for a crime she clearly had nothing to do with. In our letters to Maryland police today, we are seeking both accountability and serious policy changes to minimize the chance of this happening to anyone in the future. One wrongful arrest from this dangerous technology is an outrage. More than a dozen, and counting, is a complete travesty that lawmakers and police must take immediate action to end.
Learn More About the Issues on This Page
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Press ReleaseApr 2026
Privacy & Technology
Woman Wrongly Jailed For Months Based On Faulty Facial Recognition Technology Demands Apology From Maryland Police Departments. Explore Press Release.Woman Wrongly Jailed for Months Based on Faulty Facial Recognition Technology Demands Apology from Maryland Police Departments
MARYLAND — Today, the American Civil Liberties Union and ACLU of Maryland sent letters to three Maryland police departments on behalf of Kimberlee Williams, an Oklahoma woman who was wrongfully arrested because Maryland police relied on an incorrect result from facial recognition technology and concealed their reliance on that unreliable technology from the court when applying for arrest warrants. Ms. Williams is the fourteenth person publicly known to have been wrongfully arrested by U.S. police because of reliance on erroneous facial recognition results. “I lost six months of my life when Maryland police wrongfully imprisoned me halfway across the country from my children, my home, and my job, all because they relied on an incorrect result from faulty technology,” said Kimberlee Williams. “I had never even been to Maryland before I was flown there in handcuffs, for a crime I had nothing to do with. My family and I can’t get that time back, but I hope my experience will be a warning to police in Maryland and across the country that this technology can ruin lives. No family deserves to go through that.” On June 23, 2021, Ms. Williams was accompanying one of her daughters, a DoorDash driver, as she made a delivery to a local military base in Lawton, Oklahoma. When base security conducted a standard ID check, they discovered an outstanding Maryland arrest warrant for Ms. Williams, detained her, and called local police, who arrested her. Ms. Williams spent 23 days in an Oklahoma jail before a Maryland officer arrived to transport her to a jail in Montgomery County, Maryland, where she was imprisoned for over three months while she fought to show she couldn‘t have committed a crime in Maryland, a state she had never been to before. The police accused Ms. Williams of being a match to an unknown individual who had entered several bank branches in Maryland, impersonated account holders, and withdrawn thousands of dollars from their accounts. When the bank began investigating these incidents, a bank investigator sent an image of the unknown suspect to a national listserv of police and private investigators called Crimedex. Someone on the listserv ran the image through facial recognition technology and sent back Ms. Williams’ name and photo as a purported match to the suspect. The bank investigator sent a memo to a Montgomery County detective stating that “facial recognition software” had flagged Ms. Williams as the suspect. Without any independent investigation corroborating that erroneous match, Montgomery County police obtained a warrant for Ms. Williams’ arrest. As the letter sent today to Montgomery County police details, when applying for the arrest warrant, the detective assigned to the case concealed that the entire basis of Ms. Williams purported identification was a lead from an unknown and unreliable face recognition technology search by an unknown entity. Instead, he misleadingly claimed that Ms. Williams had been “identified” as the suspect, and that the detective had confirmed the identification by visually comparing a photo of the suspect with an older photo of Ms. Williams. Because the face recognition search had found an innocent person (Ms. Williams) who looked similar to the suspect—an inherent problem with the technology—the officers claimed verification was worthless. If Montgomery County police had accurately represented the facts to the magistrate judge or conducted an adequate investigation, Ms. Williams would not have been subject to wrongful arrest, prosecution, and prolonged detention. Montgomery County prosecutors dropped their charges against Ms. Williams in October 2021, but her ordeal did not end there. Charges were pending against her in two other Maryland counties where other bank branches had been defrauded, based on the same misidentification by face recognition technology and no independent investigation. She was transferred from Montgomery County’s jail to a jail in Prince George’s County, where she spent another two months fighting charges there and in Anne Arundel County. Those cases were finally dismissed in December 2021. All told, Ms. Williams spent six months behind bars. “No one should spend six months in jail because an algorithm got it wrong,” said Lauren Yu, a legal fellow with the ACLU’s Speech, Privacy, and Technology Project. “We now know of 14 people across the country who have been wrongfully arrested because of police reliance on dangerous face recognition technology, with no telling how many more have faced the same injustice. These Maryland police departments owe it to Ms. Williams to make amends and to take serious steps to make sure this doesn’t happen to anyone else. And police across the country are on notice: face recognition technology is hurting people, and these abuses must end.” In 2024, the ACLU reached a landmark settlement agreement with the City of Detroit following the wrongful arrest of Robert Williams due to police reliance on face recognition technology. The technology frequently gets it wrong, and testing has repeatedly shown that facial recognition systems exhibit higher rates of false matches when used on people of color, women, older people, and young people. To date, police in Maryland, Michigan, Missouri, Louisiana, Nevada, New Jersey, North Dakota, Florida, and Arizona are known to have precipitated wrongful arrests due to this technology. Ms. Williams is the second known case of such a wrongful arrest in Maryland. “The investigative failures that led to Ms. Williams’ improper arrest are a predictable result of the State’s unwillingness to specify what further investigation should be required following a facial recognition match,” said David Rocah, senior staff attorney at the ACLU of Maryland. “We told the General Assembly additional guidance was necessary when they passed legislation governing this technology in 2024, and we told the Maryland State Police this was necessary when they were writing model policies for police departments to use.” On behalf of Ms. Williams, the ACLU is demanding that police departments in Montgomery County, Prince George’s County, and Anne Arundel County investigate the failures that led to her wrongful arrest and imprisonment and publicly apologize for this devastating error. Ms. Williams is also seeking policy changes to help prevent this from happening again. Reforms must include prohibiting police from relying on facial recognition technology searches conducted by outside entities, as well as banning police from making arrests based only on face recognition results followed by human identifications, which are tainted when face recognition technology makes a false match to an innocent person who looks similar to the suspect. -
MarylandApr 2026
Privacy & Technology
Kimberlee Williams Wrongful Arrest. Explore Case.Kimberlee Williams Wrongful Arrest
Three administrative complaints seek to hold police departments in Maryland accountable for the wrongful arrest of a woman based on an , erroneous search result from facial recognition technology. -
News & CommentaryApr 2026
Privacy & Technology
Aclu Leads Fight To Limit Overbroad Digital Search Warrants. Explore News & Commentary.ACLU Leads Fight to Limit Overbroad Digital Search Warrants
ACLU litigation is leading courts to rethink warrants seizing our digital devices, social media accounts and other data to reinforce our Fourth Amendment protections. -
Press ReleaseApr 2026
Privacy & Technology
Aclu And 75 Organizations Sound Alarm On Meta’s Plan To Add Facial Recognition Technology To Ray-ban And Oakley Eyeglasses. Explore Press Release.ACLU and 75 Organizations Sound Alarm on Meta’s Plan to Add Facial Recognition Technology to Ray-Ban and Oakley Eyeglasses
Meta’s reported plan to equip its artificial intelligence (AI) eyeglasses with facial recognition technology poses an unacceptable threat to privacy and liberty and is “a red line society must not cross,” a broad coalition of organizations led by the American Civil Liberties Union, the ACLU of Massachusetts, and the New York Civil Liberties Union (NYCLU) warned today in a letter to Meta CEO Mark Zuckerberg. The letter was signed by 75 local, state, and national organizations that advocate for domestic violence survivors, worker rights, bodily autonomy, consumer privacy, civil rights, and civil liberties. They called on Meta to immediately halt and publicly disavow plans to equip its Ray-Ban and Oakley glasses with facial recognition. Glasses equipped with facial recognition technology would allow anyone wearing them to identify by name any strangers in their vicinity — including at protests, medical clinics, and businesses. They could then link that name to digital databases containing a wealth of sensitive information on the target’s job, habits, health, and relationships. “The American people have not consented to this massive invasion of privacy,” said Kade Crockford, director of technology and justice programs at the ACLU of Massachusetts. “Stalkers and scammers would have a field day with this technology. Federal agents could use it to harass and intimidate their critics. It’s dangerous and dystopian, and Meta must disavow it.” The open letter raises serious concerns about the technology’s impact on vulnerable populations, including people of color, women, children, immigrants, religious minorities, and members of the LGBTQ+ community. Anti-industry activists could use Meta’s glasses to identify and harass corporate executives. Public employees could be identified and harmed because of who they work for, or the political positions taken by their bosses. By eliminating the expectation of privacy or anonymity in public, Meta’s glasses would chill free expression for everyone. “Preventing this outcome is not just a privacy preference. It is a prerequisite for a free and safe society,” the letter states. “The principle here is quite simple: Your glasses should not know my name,” said Cody Venzke, senior staff attorney working on surveillance, privacy, and technology issues for the ACLU. “This is an inherently invasive and unethical technology. The dangers are not hypothetical — they are very real, as we have seen from the deployment of facial recognition in other contexts. Embedding this technology in consumer eyewear would vastly increase the risk of harm to individuals, families, and our democracy itself.” The coalition letter comes after internal Meta planning documents suggested that the company wanted to launch the glasses during a “dynamic political environment” because civil society groups would be too busy to protest. “That is frankly shameful,” the letter says. The groups go on to outline their deep concerns about Meta’s ability to safeguard privacy and protect the public from risks introduced by its technologies. In recent years, the company has paid more than $7 billion in settlements and fines for privacy violations. “Nobody wants to live in a world where strangers can secretly identify them, learn about their activities and interests, record their interactions, and track who they meet or how they exercise their free speech rights,” said Daniel Schwarz, senior privacy and technology strategist at the NYCLU. “Equipping these glasses with facial recognition trained on billions of unsuspecting social media users is not just unconscionable but highly dangerous.”In parallel with the open letter, the ACLU is urging consumers to write to Meta to express their concern about the technology.