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    How AI Detection Works

    Understand AI detection signals, confidence, passage-level evidence, limitations, false positives, and responsible review decisions.

    Open core guide

    Signals are evidence, not a verdict

    AI detectors estimate whether writing resembles model-generated text. The result should guide review, not replace context or human judgment.

    Interpret results with limitations in mind

    Short samples, templated writing, translation, editing, and non-native writing can affect confidence. Good workflows document uncertainty.

    FAQ

    Can AI detection prove authorship?

    No. AI detection estimates writing risk from text signals. It should be reviewed with context, drafts, citations, and policy before any high-stakes decision.

    Why do false positives happen?

    False positives can happen with short text, formulaic writing, templates, non-native writing, translation, or heavy editing. Review workflows should account for those limits.

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    How AI detection worksAI detector accuracyAI detector false positives