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AI extraction agents may look more accurate than they are if evaluators count only the items they successfully find. A Towards Data Science author argues that a capture-recapture method, borrowed from ecology, can help estimate the missing items by comparing independent extraction sources.
Why it mattersThe author also recommends jackknife estimators and small manual audits. It is a useful reminder that a system’s reported recall can miss the very errors nobody caught.
Discuss: How much should AI evaluations rely on automated estimates, and when should people check the work?
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