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π=0.0005\pi = 0.0005

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where TPR\mathrm{TPR} and FPR\mathrm{FPR} are the true- and false-positive rates and π\pi is the base rate. Plugging in TPR\mathrm{TPR} = 0.98 , FPR\mathrm{FPR} = 0.01 and π\pi = 0.0005 gives a precision of roughly 4.7%: more than nineteen out of twenty flagged requests are false alarms, even though the classifier’s headline accuracy sounds close to perfect. This is not a defect specific to content classifiers — it is the same base-rate arithmetic that governs any low-prevalence screening problem — but it is routinely missed by teams who read a classifier’s reported accuracy as the whole story and are then surprised when a human review queue fills up almost entirely with benign traffic. The practical…

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π=0.0005\pi = 0.0005

Equation 7 · AI Safety

Building a Deployment Safety System That Actually Holds

This equation states an equality: the expressions on both sides have the same value under the article’s assumptions.

where TPR\mathrm{TPR} and FPR\mathrm{FPR} are the true- and false-positive rates and π\pi is the base rate. Plugging in TPR\mathrm{TPR} = 0.98 , FPR\mathrm{FPR} = 0.01 and π\pi = 0.0005 gives a precision of roughly 4.7%: more than nineteen out of twenty flagged requests are false alarms, even though the classifier’s headline accuracy sounds close to perfect. This is not a defect specific to content classifiers — it is the same base-rate arithmetic that governs any low-prevalence screening problem — but it is routinely missed by teams who read a classifier’s reported accuracy as the whole story and are then surprised when a human review queue fills up almost entirely with benign traffic. The practical…

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