Can detectors still catch AI text rewritten to sound like a specific human writer, or do the tells run deeper than style?

This explores whether AI-generated text can still be caught once it has been rewritten to sound like a particular human writer. The corpus's short answer: it depends on which layer the detector reads. Restyling changes the surface of a text, while the strongest evidence here says AI leaves marks deeper than surface style. One thing the corpus doesn't have yet is a direct test of style-matched rewrites against AI detectors.

Start with the surface layer, because that is what rewriting targets. AI text is measurably different from human text on lexical diversity (how varied the vocabulary is and how often words repeat), and newer models drift further from human norms even as they become harder for people to spot Can humans detect AI text if machines can measure it?. Cheap, readable linguistic features caught LLM-written Reddit arguments with 99% accuracy, partly because models give themselves away by closely following the prompt and writing in a polished 'textbook' argument style Can simple linguistic features detect AI-written arguments?. These are exactly the kinds of signals a style-matching rewrite tries to smooth over. Humans are no fallback: across 30 studies, people spot AI content at roughly chance level Can people reliably spot content made by AI?.

The more surprising finding is that some signals sit below style. In fiction, a detector that ignored writing style altogether still separated AI stories from human ones with 93% accuracy. It looked only at narrative choices, such as how much agency characters have and whether events are told in chronological order. Stripping out style cost it almost nothing, because changing those choices means rewriting the story, not polishing sentences Can AI stories be detected without analyzing writing style?. If that holds outside fiction, a detector built on structure should be much harder to fool with style mimicry than one built on word choice.

Rewriting also works in the other direction. Heavy AI rewriting erases the clues that identify a human author, and the damage varies by genre. Attribution accuracy fell 66.5 points on blogs but only 10 points on news, because the topic-driven structure of news preserves authorship clues that personal writing doesn't How much does AI rewriting erase distinctive author voice?. Some researchers suggest this produces a 'double erasure', where rewritten text hides both who wrote it and the fact that an AI was involved. But the source only tested author attribution. It never ran an AI detector, so that half of the claim is unproven Do rewrites that hide authorship also fool AI detectors?.

So, putting it together: detectors that read word choice are probably vulnerable to style-matched rewrites, and detectors that read structure probably aren't. But nobody in this collection has tested that head-on. There's also a practical point. Most AI text never gets disguised at all, because writers edit AI paragraphs only 23% of the time, and their edits leave about 96% of the original intact Do writers actually edit AI-generated text before publishing?. For now, the hard case of carefully rewritten text is rarer in practice than the easy case of untouched AI output.