Measurement challenges in AI catastrophic risk governance and safety frameworks

TL;DR

This work identifies six critical measurement challenges in safety frameworks implementation and proposes three policy recommendations to improve their validity and reliability.

Abstract

Safety frameworks represent a significant development in AI governance: they are the first type of publicly shared catastrophic risk management framework developed by major AI companies and focus specifically on AI scaling decisions. I identify six critical measurement challenges in their implementation and propose three policy recommendations to improve their validity and reliability.