How AI detectors work (simplified)
AI detectors try to estimate the probability that a text was generated by a large language model. They do this by looking at statistical patterns: how predictable the word choices are, how uniform the sentence structures are, and how closely the text matches the distribution of AI-generated training data.
The key insight for writers: AI detectors are not measuring whether a tool touched the text. They are measuring whether the text "looks like" AI output. A passage that was heavily rewritten by an AI tool will look more like AI output than a passage where a tool only fixed a typo.
Why rewriting triggers detectors more than proofreading
Rewriting replaces your word choices, sentence structures, and rhythms with the AI's preferred patterns. The more text the tool replaces, the more the statistical fingerprint shifts toward the AI's training distribution.
Proofreading — in the narrow sense of fixing spelling, punctuation, and clear grammar errors — changes very little text. A typo correction does not alter the sentence structure or word choice. A punctuation fix does not change the rhythm. The statistical fingerprint stays overwhelmingly human.
This is why the distinction between "proofreading" and "editing" matters to AI detectors. A tool that paraphrases your sentences is doing something fundamentally different from a tool that fixes your comma placement.
The honest limitations
AI detectors are unreliable. They produce false positives on human-written text and false negatives on AI-generated text. Academic studies have shown high error rates across all commercial detectors.
No proofreading tool can guarantee a specific AI detection score because the detectors themselves are inconsistent and frequently updated. What a tool can control is how much text it changes and whether those changes introduce AI-pattern markers.
What fiction writers should actually worry about
For self-publishing authors, AI detection is mainly a concern with publishing platforms that scan submissions and with readers who might run passages through detectors.
For traditionally-publishing authors, the concern is agent and editor trust. If your submission triggers a detector, it creates a conversation you do not want to have — even if the trigger is a false positive.
In both cases, the practical advice is the same: use tools that make narrow, visible changes rather than broad, invisible rewrites. If you can point to exactly what the tool changed and explain why each change was a factual correction rather than a style rewrite, you are in a defensible position.