Responsible Scaling Policy (RSP)

A Responsible Scaling Policy (RSP) is a formal internal framework that defines the conditions under which an AI lab may continue developing and deploying increasingly powerful models. Pioneered by Anthropic, the RSP establishes AI Safety Levels (ASL) — escalating capability tiers, each with mandatory safety requirements that must be demonstrably met before development continues. ASL-3 models require strict deployment controls; ASL-4 models may be withheld from release entirely if safety conditions cannot be satisfied. Claude Mythos Preview is a real-world example: reportedly withheld under these provisions after it autonomously discovered zero-day vulnerabilities across major operating systems. The RSP links technical research (interpretability, red-teaming, automated evaluations) with operational governance. Other leading labs — Google DeepMind, OpenAI — have developed analogous frameworks, but Anthropic is widely credited as the pioneer of the publicly documented RSP approach. For enterprises procuring AI services, a vendor's RSP is a meaningful transparency signal: it reveals how the lab handles its most capable and potentially dangerous models, and under what thresholds it will refuse to ship.