Free AI content detector

AI content detectors are classifiers trained on large samples of human-written and machine-generated text, and they score how closely a passage matches the patterns of each. They look at things like how predictable each word is given the words before it, how much sentence length varies, and how often certain phrasings appear. Machine text tends to be smoother and more evenly predictable than human writing, which is the signal most detectors lean on. The output is a probability, not a verdict.

Accuracy varies a lot, and no detector is reliable enough to accuse someone on its own. Published evaluations typically report 60% to 90% accuracy depending on the text, the model that wrote it, and how long the sample is. Short passages, technical writing and text by non-native English speakers are where detectors go wrong most often. Treat a high score as a reason to look more closely, never as proof.

Yes, in both directions. False positives flag genuine human writing as machine-generated, which happens most with formal, formulaic or plainly written prose, and studies have repeatedly shown non-native English writers are flagged more often. False negatives miss machine text that has been edited, paraphrased or prompted to write in an unusual voice. A detector score is evidence, not a finding, and on a single short paragraph it is weak evidence.

Often, but not dependably. Unedited ChatGPT output has recognisable habits, such as even sentence rhythm, predictable word choice and a preference for balanced structures, and detectors pick those up reasonably well on longer passages. Light editing, a paraphrasing pass or a prompt asking for a specific voice degrades detection sharply. Anyone who wants to avoid detection generally can, which is why detection alone is a weak basis for policy.

No. Google's stated position is that it rewards helpful, original content regardless of how it was produced, and penalises content made mainly to manipulate rankings. Mass-produced, low-value pages are the problem, not the tool used to write them. AI text that is accurate, useful and genuinely adds something ranks on the same terms as anything else.

There is no universal number, because it depends on whose rules you are following. Many universities and publishers ask for disclosure rather than setting a threshold, while others allow AI for drafting and research but not for final text. Where a percentage is quoted it is usually a detector score, and detector scores are too noisy to enforce a precise cut-off fairly. Check the specific policy that applies to you rather than aiming at a number.

Most combine a detector score with context: the student's previous writing, the assignment's specific requirements, version history in the document, and a conversation about how the work was produced. Detectors alone are widely considered insufficient, and several institutions have turned them off after false positives. Version history and drafts tend to be more convincing than any score. The usual practice is to treat a flag as the start of a conversation.

Yes, several, including this one, which runs a trained classifier in your browser with no account needed. Free detectors are generally as accurate as paid ones, because they use similar techniques and the limits are in the method rather than the price. Whatever you use, check more than one passage and read the writing yourself before drawing any conclusion.