Facial recognition technology blamed for mistaken arrest in Louisiana purse snatching case

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A facial recognition error leads to the wrong man being arrested and jailed for SIX days, even though he never visited Louisiana, where the bag robbery took place and the 40-pound weight difference to the actual criminal

  • Randall Reid, 28, was wrongly jailed in November after facial recognition technology mistook him for a pickpocket in Louisiana.
  • In addition to having a mole on his face and a 40-pound weight difference from the suspect, Reid says he has never been to Louisiana.
  • Reid is black, and critics warn that facial recognition technology may lead to further misidentification of people of color.

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The use by Louisiana authorities of facial recognition technology led to the mistaken arrest of a Georgia man on a fugitive warrant, a lawyer said in a case bringing renewed attention to racial disparities in the use of the digital tool.

Randall Reid, 28, was jailed Nov. 25 in DeKalb County, Georgia, after authorities misidentified it as a bag snatcher in Jefferson Parish and Baton Rouge.

They told me he had a warrant for his arrest at Jefferson Parish. I said, “What is Jefferson Parish?” Reid said. ‘I’ve never been to Louisiana a day in my life. Then they told me it was for theft. So not only have I not been to Louisiana, but I haven’t stolen either.

He was released on December 1 when the authorities acknowledged their mistake.

Reid is black, and his arrest draws attention to the use of technology that critics say leads to a higher rate of misidentification of people of color than white people, The Times-Picayune/The New Orleans Advocate informed.

Critics warn that facial recognition technology may result in increased misidentification of people of color. In the photo: a random man

Tommy Calogero, Reid’s attorney, said he was falsely connected to the luxury handbag theft in June from a thrift store in Metairie, a New Orleans suburb in Jefferson Parish.

The thieves had stolen $10,000 worth of luxury Chanel and Louis Vuitton handbags in a span of three days.

A detective with the Baton Rouge Police Department later adopted Reid’s identification from the Jefferson Parish Sheriff’s Office to secure an arrest warrant alleging that he was among three men involved in another luxury purse heist the same week, court records show, according to the newspaper.

The differences, such as a mole on Reid’s face, prompted the Jefferson sheriff to rescind the warrant, said Calogero, who estimated a 40-pound difference between Reid and the purse snatcher on surveillance footage.

“I think they realized that they risked making an arrest based on a face,” Calogero said. NOLA.

The police department’s use of facial recognition in Reid’s arrest is unclear.

Tommy Calogero, Reid’s attorney, said he was falsely connected to the June theft of luxury handbags from a Metairie thrift store.

Reid’s case draws attention to the use of facial recognition tools in Louisiana and elsewhere.

In July, the New Orleans City Council voted to allow police to use facial recognition after several people complained about privacy concerns, NOLA reported.

Police can use facial recognition to identify violent crime suspects after all other tactics have failed.

New Orleans authorities say facial recognition can only be used to generate leads and that officers must get approval from department officials before filing a request through the Louisiana State Analytic and Fusion Exchange in Baton Rouge.

Under the latest city rules, all possible matches must undergo a review by other facial recognition researchers.

Legislation to restrict the use of facial recognition statewide died in a 2021 legislative session.

HOW DOES FACIAL RECOGNITION TECHNOLOGY WORK?

Facial recognition software works by matching images in real time with a previous photograph of a person.

Each face has approximately 80 unique nodal points in the eyes, nose, cheeks, and mouth that distinguish one person from another.

A digital video camera measures the distance between various points on the human face, such as the width of the nose, the depth of the eye sockets, the distance between the eyes, and the shape of the jaw line.

This produces a unique numeric code that can then be linked to a matching code drawn from a previous photograph.

Facial recognition systems have faced criticism because of their mass surveillance capabilities, which raise privacy concerns, and because some studies have shown that the technology is much more likely to misidentify black people and people of color than white people. , which has resulted in mistaken arrests.

The investigation comes amid the widespread deployment of facial recognition technology for law enforcement, airports, banking, retail and smartphones.

Failures could lead to ‘the wrong people being arrested’ and ‘lengthy interrogations’ according to Jay Stanley of the American Civil Liberties Union.

A 2019 National Institute of Standards and Technology (NIST) study found that two algorithms assigned black women the wrong gender 35 percent of the time.

Activists and researchers have claimed that the potential for errors is too great, and that errors could result in the imprisonment of innocent people.

They also claimed that the technology could be used to create databases that can be hacked or used inappropriately.

The NIST study found both “false positives,” where an individual is misidentified, and “false negatives,” where the algorithm fails to accurately match a face to a specific person in a database.

An expert in facial recognition software at the MIT Media Lab says this study shows that the proliferation of facial surveillance must be stopped to protect people.

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