A 61 year old man, Harvey Eugene Murphy Jr is in pursuit of a $10 million lawsuit against the all famous and well-known retailers Macy’s and EssilorLuxottica, alleging that their use of facial recognition tech has resulted in his wrongful arrest and subsequent violent assault in a Houston, Texas jail.
The incident commenced from a misidentification which associated Murphy to a robbery at a Sunglass Hut, a subsidiary of EssilorLuxottica in 2022.
According to Murphy, an EssilorLuxottica employee, in partnership with Macy’s, employed facial recognition software that inaccurately identified him as one of the robbers. Despite the poor quality of the images used, he was also implicated in two additional robberies.
Murphy asserts that he was in Sacramento, California, during the Sunglass Hut incident. However, upon his return to Texas in October 2023 to renew his license, he was arrested based on the mistaken identity facilitated by facial recognition technology.
While in Harris County jail, Murphy endured a brutal attack by three men who physically assaulted and sexually abused him. Although the charges were dropped when it was confirmed he was not present at the Sunglass Hut during the robbery, the harm had already been inflicted.
Murphy’s attorney, examining police records, found that EssilorLuxottica and Macy’s had utilized facial recognition technology to connect him to the crime.
The lawsuit filed by Murphy highlights the permanent injuries resulting from the assault and attributes the entire ordeal to the defendants’ reliance on facial recognition technology known for its error-prone and faulty nature. This case represents the seventh publicly known instance in the United States where flawed facial recognition technology led to a wrongful arrest.
In a broader context, this incident contributes to a mounting body of evidence against facial recognition technology. In late 2023, the Federal Trade Commission (FTC) had previously censured Rite Aid for falsely accusing shoppers of shoplifting using facial recognition software, particularly affecting Black, Hispanic, and female customers.
These cases collectively underscore the concerns surrounding the accuracy and ethical implications of deploying facial recognition technology in both law enforcement and commercial settings.
