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False Positive AI Detection
False positives happen when AI detection tools flag original, human-written work as AI-generated. This is one of the most frustrating issues students face with current AI detection systems. Reports suggest false positive rates range from 2% to over 15% depending on the tool, the subject matter, and the writer's style. Non-native English speakers and technical writers are disproportionately affected.
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What Students Are Asking
Why do AI detectors flag original writing as AI?
AI detectors look for patterns like low perplexity (predictable word choices) and low burstiness (uniform sentence length). Technical writing, formulaic academic prose, and writing by non-native speakers naturally exhibits these patterns, triggering false positives.
How do you appeal a false positive AI flag?
Gather evidence: Google Docs version history, research notes, browser history showing sources visited, earlier drafts, and writing process screenshots. Present these to your professor or academic integrity office with a calm, factual explanation.