False positives: what to do when your own writing is flagged

It's a horrible feeling: you wrote it, and a detector says a machine did. Here's why it happens and what actually helps.

Why real writing gets flagged

Detectors estimate how predictable and uniform text is, not who wrote it. Writing that is short, formulaic, highly polished, or produced by a non-native English speaker tends to be more predictable, and gets flagged at higher rates. Grammar tools that smooth your prose can push it further toward 'machine-like'. None of that means you did anything wrong; it means the tool is measuring a proxy, and the proxy is imperfect.

Detector vendors know this. The responsible ones tell institutions in writing not to use a score alone to make a decision about a person.

If you're accused

Keep evidence of your process: version history in your document, drafts, notes, browser research. Being able to show how a piece evolved is the strongest response to a flag, and it's a good habit regardless. Ask what the score actually was and how the tool defines its threshold. A '40% AI' document-level score is not a finding that 40% of your sentences are fabricated. Request a human review, and point to the vendor's own guidance that scores are not proof.

If your institution has an AI policy, follow it and document your compliance. Most disputes are resolved by showing your work, not by arguing about the number.

How to lower a false positive

The same edits that make writing better make it read as more human: vary your sentence length, prefer concrete examples over abstractions, and let your own voice through. You can use antigpt to check how a passage reads to a classifier and to rework the parts that read as uniform (as feedback, not as a way to 'beat' anything). The goal is writing you'd defend, that also happens to read as yours.