FIELD NOTES TOPIC

measurement

4 notes, newest first.

  1. Searching for "Harmful Refusal": A Psychometric Audit of an AI Safety Benchmark

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    The preprint audits whether harmful refusal is a single measurable attribute in HELM Safety. It reports saturation in three candidate datasets and uses multidimensional item-response theory plus differential item…

  2. On the estimation and validity of AI time horizons---a statistical look at the METR plot

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    The preprint recomputes METR-style 50% AI time horizons over 228 tasks and 26 AIs using splines and item-response theory. The authors report that the fitted spline is nearly flat from roughly 2–30 minutes and close to…

  3. How to connect AI usage to business value

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    OpenAI describes ChatGPT Work and Codex analytics that combine usage, spend, task insights, and outcome metrics. The post describes task classification, model/reasoning/speed breakdowns, plugin and skills views, Codex…

  4. AI Exposure Scores: what they measure, what they miss, and what comes next

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    The article discusses the limitations of a set of AI Exposure Scores introduced by Eloundou et al., which measure the share of tasks that can be assisted by large language models. The authors highlight two main gaps…