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February 20, 2022

Macy’s and a dozen other large retailers are quietly using controversial facial-recognition technology to fight a rise in smash-and-grab robberies and other coordinated attacks.

It’s part of a larger push to turn retailers’ existing security cameras — those ubiquitous black gadgets that produce thousands of hours of mostly useless footage — into a more sophisticated artificial-intelligence surveillance system, capable of automatically identifying people, license plates and other information that can be used to alert store employees of unfolding threats and ultimately prosecute offenders.

The technology has new appeal at a time when theft and violence is on the rise, particularly from organized crime groups that steal millions of dollars in merchandise and then sell the products online. Organized retail crime has risen by 60% since 2015, according to the National Retail Federation, with nearly 70% of retailers reporting an increase in 2021. As much as $69 billion worth of products are stolen from the nation’s retailers each year, or 1.5% of sales, according to estimates from the Retail Industry Leaders Association and the Buy Safe America Coalition. A record 523 people were killed during robberies and other violent retail incidents in the U.S. in 2020, including 256 customers and 139 employees.

This month, the federal government charged 29 people with stealing $10 million in over-the-counter medicine and other items from Walmart, Costco, CVS, GNC and others, then reselling the products on sites like Amazon and eBay.

Facial-recognition technology is controversial because research has shown it’s often inaccurate when identifying people of color and women. The worst technology has an error rate of up to 35% when scanning darker-skinned women, but less than 1% with lighter-skinned men, according to one research report. The reason? Early versions of the algorithms were trained using images of celebrities that skewed white and male.

Companies have been working to address the racial bias, and between 2014 and 2018, facial-recognition software got 20 times better at searching a database to find a matching photograph, according to the National Institute of Standards and Technology. However, as of 2019, the government found that some software still misidentified African-American and Asian people 10 to 100 times more often than white men.

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