In fact, AI watermarks and detectors may leave us worse off by creating a false sense of confidence in content marked as genuine.
“But I know a fake when I see it,” someone might say.
We’ve seen this story before. During the earliest days of the Internet, visual polish at least told you something. Major institutions had the resources needed to produce well-designed websites. Janky-looking sites, on the other hand, screamed “scam!” Information experts directed Internet users to dwell on features such as design, broken links, and typos. But when the Internet changed, the advice didn’t.
The most dangerous legacy of this aesthetic fixation is the inverse illusion: the cognitive tendency to believe that if the presence of a signal proves one thing, its absence proves the opposite. Yes, a site with misspellings that claims to show aliens still isn’t legit. But a beautiful site with a dot-org domain can also be harmful. In 2019, our research group found that nearly half of hate groups had dot-org domains. Bad actors know how to adopt the trappings of credibility.
Which brings us to AI watermarks and detectors. These approaches, based on hidden signals in content, promise that while we can’t always spot the signs, their algorithms can.
Google admits that the accuracy of detecting watermarked AI text is “greatly reduced” when users thoroughly rewrite what they generate, and that it “is not designed to directly stop motivated adversaries from causing harm.” More broadly, open-weight AI models that can run locally, outside platform terms and conditions, guarantee the spread of unmarked content.
I would argue that the biggest problem for detectors and watermarks remains the inverse illusion. Just because content lacks a watermark doesn’t mean it wasn’t produced or edited with AI. As Anthropic notes: “lack of a detected mark doesn’t mean the content wasn’t AI-generated or processed.” Deferring judgment to AI detectors leaves us vulnerable to bad actors who know how to launder content and make it pass muster.
But just because we can’t trust our eyes or place full faith in detectors doesn’t mean we can’t trust anything. Rather than hunt for visual clues or outsource judgment to detectors and watermarks, we can turn to reputation and context. It’s easy to fake content. It’s much harder to fake a good reputation that’s validated by credible sources.
In an era of dwindling trust, we should not fork over ours to cheap signals or cheap software.
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