Are AI detectors accurate?
They produce a likelihood, not a verdict — and they are wrong in both directions.
What AI detectors actually measure
A detector does not read your mind and does not hold a copy of everything ever written. It scores statistical properties of a passage and reports a likelihood. Two properties come up constantly.
Perplexity
How predictable each word is, given the words before it.
A model picks likely words, so its output tends to score as unsurprising almost everywhere. Writing that makes a specific, unexpected point does not.
Burstiness
How much sentence length and complexity vary across a passage.
Human drafts lurch — a long qualified sentence, then a short one. Generated text tends to hold an even width from start to finish.
The AI detectors you are most likely to meet
What each one looks at, where it turns up, and what its output actually is.
| Detector | Scores independently | Sells a humanizer too | What it measures | Where you meet it | What it reports |
|---|---|---|---|---|---|
| GPTZero | Own model | No | Predictability of each word, and how much sentence length varies | Schools and universities, individual checks | A likelihood, per document and per passage |
| Turnitin | Own model | No | Text patterns, alongside its long-standing similarity checking | Coursework submitted through a university system | A percentage estimate shown to the instructor, not the student |
| Originality.ai | Own model | No | Text patterns, alongside plagiarism matching | Publishers and content agencies checking freelance work | A confidence score per scan |
| Copyleaks | Own model | No | Text patterns across several languages | Enterprise and education platforms, often via integration | A per-section classification |
| Winston AI | Own model | No | Text patterns, with per-sentence highlighting | Educators and content teams | A score plus the passages that drove it |
| ZeroGPT | Own model | No | Text patterns, in a free web tool | Quick self-checks before submitting | A percentage estimate |
| Pangram | Own model | No | Text patterns, using a model trained on paired human and AI writing | Universities and publishers, and a free web check | A likelihood, with the passages that drove it |
| Undetectable.ai | Polls other tools | Yes | Text patterns, aggregated from several other detectors' verdicts | A free web check, alongside the same company's humanizer | A combined estimate plus each underlying detector's reading |
Compiled from each tool's public information, reviewed August 2026. Detectors update continuously and none publishes a stable specification, so treat this as orientation. It does not rate them for accuracy — we do not measure that, and a company selling a humanizer would be the wrong source for it. Nothing here describes how any particular piece of writing will score.
To be clear about our own position: ReverseGPT sells a humanizer. That is exactly why this page has no detector of its own in the table, rates nothing for accuracy, and makes no claim about how any text will score. Explaining how these tools work and letting you judge the scores yourself is the only honest thing we are in a position to do.
Why careful human writing gets flagged
Clarity and predictability look similar from the outside. Prose edited hard for concision, technical documentation, and measured writing by a non-native speaker all produce an even texture — which is the same signal a classifier reads as machine-generated.
That is the honest limit, and it cuts both ways: a low score is not proof of authorship either. Use a score as a prompt to reread your draft, never as a verdict on who wrote it. If your work is ever questioned, a version history showing how it developed is far stronger evidence than any score is against it.
Frequently asked questions
- Are AI detectors accurate?
- They report a likelihood, not a fact, and they are wrong in both directions. No detector has access to how a document was written — it scores statistical properties of the text and estimates.
- Why does my own writing get flagged as AI?
- Because clarity and predictability look similar statistically. Prose edited hard for concision, technical documentation and measured writing by non-native speakers all tend to score as even-textured, which is the same signal a classifier reads.
- What do AI detectors actually measure?
- Mostly two things: how predictable each word is given the words before it, and how much sentence length and complexity vary across a passage. Neither says anything about who wrote the text.
- Can any tool guarantee a particular detector score?
- No. Detectors change their models continuously, so no tool can promise a result — and any that does is describing something it cannot control.
- Can AI detectors tell which model wrote something?
- No. A detector scores statistical properties of the text and reports a likelihood that it was machine-generated; it has no way to attribute a passage to a particular model. Claims that a score identifies the tool behind a draft are reading more into the number than it contains.
- What should I do if my work is flagged?
- Keep your drafts and notes. A version history showing how a piece developed is far stronger evidence of your process than any score is against it.
Write it so it reads like you
A score is a prompt to reread your draft, not a verdict on it. ReverseGPT gives you the editor, the grammar and style assistant and the sources to do that rereading properly. Free to start.