A false positive is when a moderation system incorrectly flags or removes content that doesn't actually violate any policy, treating legitimate content as if it were a violation. The system says there's a problem, but there isn't one.

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‍Why it matters

False positives carry a different cost than false negatives. They don't cause direct harm the way a missed violation does, but they erode trust and cause real frustration, especially when a legitimate creator, business, or user gets penalized for something they didn't do. At scale, a high false positive rate can drive away the users a platform most wants to keep. It's also a tradeoff with false negatives, since tightening detection to catch more real violations almost always increases false positives too, so platforms have to decide where that balance sits for each policy area.

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‍How teams manage it

‍Teams build an appeals process because some false positives are expected, and they track the rate by category instead of overall, to find which rule is producing the most wrong flags. One overly aggressive rule can account for a disproportionate share of complaints, and reviewing that rule is usually faster than retraining everyone.