AI detection FAQ
Can AI detectors be wrong?
Quick answer
Yes. Every AI detector can produce false positives (flagging human writing) and false negatives (missing AI writing), so results should be treated as evidence to review rather than proof.
False positives are most common with short samples, formulaic or templated assignments, polished writing, and text from non-native English writers. False negatives happen when AI output is heavily edited, paraphrased, or mixed with human writing.
Because the cost of a wrong accusation is high, responsible use means inspecting flagged passages, comparing them with drafts and sources, and involving human judgment before any decision.
DeepDetector is designed around this reality: it emphasizes explainability and confidence so reviewers can see why a passage was flagged and how certain the result is, instead of trusting a single number.
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See explainable, passage-level evidence instead of a single score.
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