How Russia is using facial recognition to police its coronavirus lockdown

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How Russia is using facial recognition to police its coronavirus lockdown
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When he landed in Moscow in early March from South Korea, Vladimir Bykovsky said he was ordered into self-quarantine for two weeks. Bykovsky said officers told him he had been spotted on a camera set up on the front door of his apartment building and identified through a facial recognition system, which

When he landed in Moscow in early March from South Korea, Vladimir Bykovsky said he was ordered into self-quarantine for two weeks. Under the rules, he was not permitted to leave the house. But after a few days—and showing no symptoms of novel coronavirus-- he said he stepped out of his building and threw out his trash. Then he went back inside.

Tune into ABC at 1 p.m. ET and ABC News Live at 4 p.m. ET every weekday for special coverage of the novel coronavirus with the full ABC News team, including the latest news, context and analysis. How it worksThe system allows police to search in real-time across those cameras for a person using just a single image, according to its developers.As in other countries, Moscow’s technology works through training a neural network to recognize faces by feeding it millions of images. The system can then construct a unique profile for each face it analyzes.

The company soon hopes to roll out a function analyzing silhouettes, he said, meaning it could spot large gatherings and also automatically detect when people are standing too close together. “I wouldn’t discount what they’re saying, but I would caveat it significantly in terms of their spread and abilities to do what they’re claiming,” said Magarita Konaev, a research fellow at Georgetown University’s Center for Security and Emerging Technology, who is focused on the Russian military’s use of artificial intelligence.

Patrick Grother, a scientist at the Commerce Department's National Institute of Standards and Technology and an author of the study, said whether the technology could maintain similar speeds in the real world was primarily a question of how much computing power a city was willing to purchase. “We built a super power-efficient system, so we consume very few resources,” said Alexander Khanin, founder of Vision Labs, which supplied one of the algorithms.

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