Equation 9 · Part 2 · A Chatbot Confessed to Being Built by a Company That Never Trained It

Symbol m

I(m)=\frac{1}{k}\sum_{q\in Q}\mathbb{1}[r_m(q)\in\mathcal{T}]

m

What this part means

m is an argument of the function-like quantity on the left; its role is set by that function’s stated inputs.

Its job in the formula

m is an argument of the function-like quantity on the left; its role is set by that function’s stated inputs.

Full expressionSymbol mArticle meaning

The passage around this formula

Sort a population of models $\mathcal{M}$ =\{ $m_1$ , $\dots$ , $m_N$ \} into the three exposure classes just defined, $\mathcal{M}_V$ , $\mathcal{M}_H$ , and $\mathcal{M}_\varnothing$ . For each model m , define its trait incidence as I(m)= $\frac{1}{k}$ $\sum_{q\in Q}$ $\mathbb{1}$ [ $r_m(q)$ $\in$ $\mathcal{T}$ ] , where Q is the held-out probe set of size k and $r_m(q)$ is m ’s response to probe q . I(m) is a dimensionless rate between 0 and 1: the fraction of probes that elicit the trait. Average I(m) within each…

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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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See this notation across published equations →

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