Emerging Practices in Frontier AI Safety Frameworks
It provides an overview for AI developers, governments, and researchers to guide the development of safety frameworks, but it is incremental as it synthesizes existing ideas rather than introducing new methods.
This paper summarizes current thinking on how to write effective safety frameworks for managing severe risks in frontier AI systems, outlining three core areas and identifying emerging practices within each.
As part of the Frontier AI Safety Commitments agreed to at the 2024 AI Seoul Summit, many AI developers agreed to publish a safety framework outlining how they will manage potential severe risks associated with their systems. This paper summarises current thinking from companies, governments, and researchers on how to write an effective safety framework. We outline three core areas of a safety framework - risk identification and assessment, risk mitigation, and governance - and identify emerging practices within each area. As safety frameworks are novel and rapidly developing, we hope that this paper can serve both as an overview of work to date and as a starting point for further discussion and innovation.