An AI essay detector doesn't read your essay for meaning — it looks at statistical patterns in how the words are put together, and estimates how closely those patterns match typical AI output. That distinction matters for understanding what a score does and doesn't tell you.
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Most detectors score two related things: perplexity, roughly how 'predictable' the word choices are to a language model, and burstiness, how much sentence length and structure varies. AI-generated text tends to be more predictable and more uniform; human writing tends to be messier and more varied.
Neither of those is a direct measurement of 'was this written by AI' — they're proxies, which is exactly why detectors can be wrong in both directions.
Every major detector — including the ones built into Turnitin and standalone tools like GPTZero — publishes some acknowledgment of false positive and false negative rates. Heavily edited AI text can score as human; very formal or repetitive human writing can score as AI.
This is why checking against multiple detectors and looking for agreement across them is more informative than relying on any single score.
If your own original writing gets flagged, look at what's being highlighted — usually it's the most generic, formulaic sentences (introductions and conclusions are common culprits). Adding specific detail, personal examples, or varying sentence structure tends to lower a score meaningfully.
If you used AI as part of your drafting process, the same fix applies: the more specific and personally-voiced the final draft is, the less it will resemble the generic patterns these tools are built to catch.
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