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Chronicles

The story behind the story

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An NYT project using Amazon's facial recognition cloud service and New York City's cameras identified people for day without their knowledge and cost just ~$60

Most people pass through some type of public space in their daily routine — sidewalks, roads, train stations. Tweets: @nytopinion , @alexisohanian , @privacyproject , and @cwarzel Tweets: @nytopinion : We turned New York City's cameras into a facial recognition machine. The total cost: $60. For more on privacy, follow @privacyproject http://www.nytimes.com/... Alexis Ohanian Sr. / @alexisohanian : People out here distracted by “AI = Terminator” when we should be talking about how AI *right now* can power unprecedented surveillance. http://twitter.com/... @privacyproject : Most people expect that a detailed log of their location and a list of people they're with are private. Facial recognition threatens to compromise that privacy, says Sahil Chinoy. http://www.nytimes.com/... Charlie Warzel / @cwarzel : this story by my colleagues is wild and so well executed. facial recognition software can be deployed for cheap using cameras that already exist in cities. they were able to accurately pick folks out of the crowds http://twitter.com/...

New York Times Sahil Chinoy

Context & Ripple Effects

This project is the demonstration that made the surveillance debate concrete: the NYT's opinion desk wired New York City's existing camera feeds into Amazon's off-the-shelf facial recognition cloud service and identified passersby for a day without their consent, for roughly $60. The point was not technical novelty but accessibility — no custom hardware, no special access, just a credit card and public camera streams. Alexis Ohanian and Charlie Warzel amplified exactly that framing, arguing the live risk is present-day tracking rather than sci-fi scenarios.

The demo landed at the start of an arc the related coverage traces directly: months later, a new generation of UK cameras began feeding real-time facial recognition checks into public spaces, and by January 2020 Clearview AI had scraped billions of photos from social platforms for 600+ law enforcement agencies. The NYT experiment was the cheap, reproducible proof-of-concept those developments industrialized.

First-order effects

  • Every organization with a budget of tens of dollars — journalists, activists, stalkers, private firms — can now replicate the setup, because Amazon sells the recognition capability as a commodity cloud API and cities already operate the cameras.

Second-order effects

  • Law enforcement adoption accelerates along the path the coverage documents: Clearview's claimed 600+ agency customer base and the UK's real-time camera deployments show police forces reaching for the same capability without building it themselves.

Third-order effects

  • If identification in public space becomes this cheap and reproducible, anonymity in streets, stations, and sidewalks becomes the exception requiring deliberate protection — pushing the regulatory question from 'should governments do this' to 'who is allowed to identify whom, and under what notice.'

The trend: Facial recognition is collapsing from a government-scale capability into a commodity service layered on existing public cameras, moving the constraint from technology to governance.