RESOLVING THE LEDGER
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Hello and welcome to Eye on AI. Beatrice Nolan here, filling in for Jeremy. In this edition:
AI-generated content might soon get easier to spot.
OpenAI’s Brad Lightcap is leaving
Nvidia and Wall Street’s biggest names team up on a $500 billion AI financing push.
House Democrats want AI CEOs to testify on hacking incidents.
Scientists used AI to invent a virus.
And AI may be able to help us answer some of our unsolvable questions—with a little encouragement.
Anthropic is planning to introduce a subtle watermark that can be used to identify AI-generated text.
Starting with models released on or after August 2, Anthropic says it’s weaving an imperceptible, machine-readable signal directly into Claude-generated text. People won’t be able to see it, and the company says it won’t affect quality or readability. But it’s designed to travel with the text when you copy and paste, and it may survive some editing too. (A heavy rewrite or a translation may knock it out, though.)
Because the watermark sits at the model level, it follows Claude’s output everywhere and will appear when users engage with Claude through the chatbot, the API, and even through tools like Claude Code. Images will also get a watermark which shows Claude processed the file and flags if someone has tampered with it since.
The move is partly an attempt to align with the new EU AI Act’s transparency rules that kicked in on August 2. Those rules require generative AI providers to make synthetic output machine-readable and detectable.
While other AI companies have attempted this kind of watermarking before, it’s been mostly aimed at images. Text has traditionally been more difficult to identify in this way because it gets copied, paraphrased, translated, chopped up and folded into someone else’s writing all the time. Anthropic itself says the new detection mark only shows Claude had a hand in something, not that a Claude model generated the entire thing. Even asking the model to proofread or translate a paragraph could leave a trace. (If you’re using an older Claude model, none of this applies yet, but Anthropic says it’s still working on extending the marking.)
A wider push to police AI slop
While the move by Anthropic has likely been sparked by the EU act, it’s also landed amid a bigger backlash against AI “slop” clogging up social feeds.
Several other companies and platforms have tried to soothe creator anger over having to compete not only with opaque algorithms but with a rising tide of low-quality AI-generated content. Substack, for example, has rolled out a reader-triggered AI scanner , so readers can get an estimate of how much of a post or even a comment was human versus AI-written. Writers can also add a “How I make this” disclosure to explain their process.
YouTube has also made strides to combat AI-generated content. Last month, the platform clarified its “inauthentic content” policy to further crack down on AI slop running wild on the platform. YouTube already barred repetitive or mass-produced videos from monetization. But it clarified that channels leaning on generic, templated output, including AI personas dishing out health, legal, financial, or political advice, can lose their revenue. AI-assisted work is still fine, so creators can keep using AI for scripts or editing. This is one of the more concrete steps, as it could end up with some heavy AI users losing out on financial gains.
Watermarking alone isn’t going to clean up the internet. Anyone determined to disguise AI output has plenty of ways to degrade or erase a statistical text watermark. Many of the previous marks have also been easy to remove.
But Anthropic’s newest attempt to separate AI content from human content speaks to a bigger push coming from consumers and publishers for simple ways to distinguish between AI and human content. Users appear to be fed up with feeling like the burden of that distinction should come from them when AI companies are playing such a vital role in pumping out low quality work en masse.
However, as some have noted online, such a flat “AI” label risks treating someone generating a thousand fake news videos the same as a writer using Claude to clean up a paragraph, or a journalist using it to translate an interview transcript.
In a world that is increasingly hostile to anything that is related to AI, it could prove to be a hard line to walk.
And with that, here’s the rest of the AI news.
Beatrice Nolan [email protected] @beafreyanolan
Before we get to the news, just a reminder to check out our new vodcast, Fortune AI Weekly. This week, Emily Forlini and I discuss Washington’s new AI framework and Google DeepMind’s big restructure. You can check out the vod here on YouTube.
This story was originally featured on Fortune.com
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