AI Text Detector

AI-generated text has subtle patterns — predictable sentence structures, overuse of certain phrases, uniform tone, and distinctive vocabulary choices. Our AI analyzes these signals to assess whether a text is likely AI-generated.

While no detector is 100% accurate, this tool provides a valuable, evidence-based assessment to inform your decision.

Under the hood, detection rests on measurable properties: perplexity (how predictable each next word is), burstiness (how much sentence length and structure vary), and the frequency of signature phrases that language models overuse. Human writing tends to be messier on all three axes — and that messiness is exactly what the statistics pick up.

Take this paragraph, generated by a chatbot and left untouched: 'Time management is crucial in today's fast-paced world. By prioritizing tasks effectively, individuals can enhance their productivity. Moreover, setting clear goals is essential for success. In conclusion, mastering time management unlocks one's full potential.' A detector flags it with high confidence: every sentence follows the same rhythm, transitions like 'Moreover' and 'In conclusion' arrive on schedule, and there isn't a single concrete detail.

Now a human-edited version of the same idea: 'I used to answer email for two hours before touching real work. Blocking 9 to 11 a.m. for my hardest task — phone in a drawer — doubled my output within a month. Not a system, just one boring rule that held.' First person, an actual number, uneven sentence lengths, a small confession. Detectors read this as human because it carries the fingerprints of lived experience.

The gap between the two shows what detection actually measures: predictability, not truth.

A score means little on its own — the same passage can rate differently on different tools, or on the same tool a week apart. These habits make results meaningful:

No AI detector — ours included — is reliable enough to serve as proof. False positives are well documented, and they fall hardest on certain writers: non-native English speakers and people with a naturally plain, structured style are regularly misclassified as machines. Formulaic genres like lab reports trigger flags almost by design.

For teachers and editors, the responsible workflow is clear: never sanction a student or reject a writer on a score alone. Treat the result as a reason to open a conversation — ask the author to walk through their drafts or defend their argument, which someone who wrote the text can do easily. And keep in mind the reverse: determined users can rewrite AI text until it slips past any detector, so the absence of a flag proves nothing either.