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Chronicles

The story behind the story

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As bots plague everything from Tinder to Twitter, a look at how generative adversarial networks create images and videos of fake people, sold on many websites

There are now businesses that sell fake people.  On the website Generated.Photos, you can buy a “unique, worry-free” fake person for $2.99, or 1,000 people for $1,000.

New York Times

Context & Ripple Effects

The fake-person trade has a traceable lineage: in 2018, [[a:925441|Nvidia researchers showed GANs could synthesize photorealistic faces of people who don't exist]], and two years later the technique is a storefront product — Generated.Photos sells 'unique, worry-free' fake humans at $2.99 apiece or 1,000 for $1,000.

The same pipeline has an abusive twin: weeks before this piece, researchers exposed a [[a:959217|Telegram bot that generated fake nudes of real women, with 100K+ images shared publicly by July]]. The NYT story captures the moment synthetic identity went from lab demo to both a legitimate commodity and a harassment weapon, while bots built on such assets plague Tinder and Twitter.

First-order effects

  • Platforms like Tinder and Twitter absorb the direct hit: cheap, indistinguishable fake profiles degrade user experience and force moderation teams to fight adversaries whose supply cost is under three dollars per identity.

Second-order effects

  • Buyers of bulk synthetic people — marketers, stock-photo users, and fraud operators — gain pricing leverage over traditional stock photography and model licensing, while ad-fraud ecosystems like the fake online traffic business Wired documented in 2022 get a ready-made population to attach to fraudulent inventory.

Third-order effects

  • If per-dollar synthetic humans keep proliferating, platforms and regulators are pushed toward proof-of-personhood systems and likeness-governance rules, because visual authenticity alone can no longer distinguish a customer from an inventory item.

The trend: Synthetic human imagery is commoditizing along the same path as its research origins — from Nvidia's 2018 demos to dollar-priced marketplaces — collapsing the cost of fake identity faster than platforms can verify real ones.

Discussion

  • @nytimes @nytimes on x
    Artificial intelligence is responsible for these fakes. It trains on photos of real people and tries to make its own, then attempts to detect the flaws. Over time, it learns and keeps getting better. It will soon be hard to tell online who is real. https://www.nytimes.com/...
  • @kashhill Kashmir Hill on x
    The hard thing about covering tech is that it is both amazingly powerful and unexpectedly flawed at the same time. Tried to describe here, but, ironically, the incredible demo/tech does the job best: https://www.nytimes.com/...
  • @bendobrown Benjamin Strick on x
    Terrifying, yet great, piece by @nytimes on just how easy it is to create fake people and how these AI-generated disguises are being used to conceal bad actors. https://www.nytimes.com/... https://twitter.com/...
  • @panzer Matthew Panzarino on x
    Watch @CodedBias then you'll understand why the presentation of this article is so chilling. https://twitter.com/...
  • @ericajoy Erica Joy on x
    🎶do you see what i see?🎶 https://twitter.com/...