OpenAI Blog
Apr 13, 2022

Measuring Goodhart’s law

Goodhart’s law famously says: “When a measure becomes a target, it ceases to be a good measure. ” Although originally from economics, it’s something we have to grapple with at OpenAI when figuring out how to optimize objectives that are difficult or costly to measure.

arXiv Machine Learning
Sep 17

Making Political Text Scaling Comparable: Infrastructure and Hyperparameter Sensitivity for 17 Algorithms

The paper argues that computational text‑based ideal point estimation (CT‑IPE) methods should be viewed as configurable measurement pipelines rather than fixed estimators. It presents a large‑scale comparative experiment involving 17 CT‑IPE algorithms, 5,537 runs, and about 4.25 million left‑right position estimates, and describes shared infrastructure that enables joint execution of these heterogeneous methods. Sensitivity analyses reveal that most algorithms exhibit low hyperparameter sensitivity (ICC < .10), with any remaining sensitivity concentrated in a few key researcher choices such as the language or embedding model, seed keyword lists, and number of topics.

By Patrick Parschan