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Cashierless Tech Could Detect Shoplifting, but Bias Concerns Abound

As the pandemic continues to rage around the world, it’s becoming clear that COVID-19 will endure longer than some health experts initially predicted. Owing in part to slow vaccine rollouts, rapidly spreading new strains, and politically charged rhetoric around social distancing, the novel coronavirus is likely to become endemic, necessitating changes in the ways we live our lives.

Some of those changes might occur in brick-and-mortar retail stores, where touch surfaces like countertops, cash, credit cards, and bags are potential viral spread vectors. The pandemic appears to have renewed interest in cashierless technology like Amazon Go, Amazon’s chain of stores that allow shoppers to pick up and purchase items without interacting with a store clerk. Indeed, Walmart, 7-Eleven, and cashierless startups including AiFi, Standard, and Grabango have expanded their presence over the past year.

But as cashierless technology becomes normalized, there’s a risk it could be used for purposes beyond payment, particularly shoplifting detection. While shoplifting detection isn’t problematic on its face, case studies illustrate that it’s susceptible to bias and other flaws that could, at worst, result in false positives…   Venture Beat

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