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Equation 4 · Part 1 · AI Governance and Regulation in Practice: An Advanced Technical Guide

Symbol hatp

p^+z0.95p^(1−p^)n≤ε\hat{p} + z_{0.95}\sqrt{\frac{\hat{p}(1-\hat{p})}{n}} \le \varepsilon
p^\hat{p}

What this part means

the observed error rate.

Its job in the formula

hatp occurs above the fraction bar. The numerator is divided by the entire denominator below it.

Where the article explains it

A deployer setting an acceptance gate on a generative system’s confabulation rate might define a simple pass condition against a sampled evaluation set of size n , tolerance ε\varepsilon , and observed error rate p^\hat{p} : p^+z0.95p^(1−p^)n≤ε\hat{p} + z_{0.95}\sqrt{\frac{\hat{p}(1-\hat{p})}{n}} \le \varepsilon.

The passage around this formula

…as fact. A deployer setting an acceptance gate on a generative system’s confabulation rate might define a simple pass condition against a sampled evaluation set of size n , tolerance ε\varepsilon , and observed error rate p^\hat{p} : p^+z0.95p^(1−p^)n≤ε\hat{p} + z_{0.95}\sqrt{\frac{\hat{p}(1-\hat{p})}{n}} \le \varepsilon. This is a standard one-sided Wald confidence bound, included here only because it exposes a real assumption practitioners often skip: a raw sampled error rate without its confidence interval says nothing about whether the true rate is actually below a threshold,…

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Learn the underlying idea

A function assigns an output to each allowed input. The expression f(x) means “apply f to x”.

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Sources cited in the article section

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