AnthropicAnnouncement
Announcing Anthropic's Responsible Scaling Policy
Summary
Anthropic announces its Responsible Scaling Policy (RSP), a set of technical and organizational protocols for managing catastrophic risks from increasingly capable AI systems, including deliberate misuse and autonomous behavior contrary to designers’ intent. The policy introduces AI Safety Levels (ASL), loosely modeled on biosafety levels, with requirements for safety, security, and operations increasing alongside a model’s potential for catastrophic risk; current LLMs, including Claude, are described as ASL-2. ASL-3 would require unusually strong security and no deployment when adversarial testing by world-class red-teamers finds meaningful catastrophic misuse risk, while ASL-4 measures remain unwritten and may depend on unresolved interpretability research. Approved by Anthropic’s board, the RSP is presented as an initial, revisable framework that may temporarily pause scaling when safety procedures cannot keep pace, while incentivizing solutions needed for further development and leaving current Claude uses and product availability unchanged.
Context
Increasingly capable AI systems may create major economic and social value while also presenting more severe catastrophic risks, including deliberate misuse and autonomous behavior contrary to designers’ intent.
Approach / What changed
The RSP establishes AI Safety Levels modeled loosely on biosafety levels, assigning progressively stricter safety, security, and operational requirements according to a model’s potential for catastrophic risk. It includes adversarial testing requirements, board oversight, procedural safeguards, and commitments to develop higher-level measures before they are needed.
Takeaways
Current LLMs, including Claude, are classified in the announcement as ASL-2 because they show early dangerous capabilities but are not yet reliably useful for catastrophic misuse.
ASL-3 measures include unusually strong security requirements and a commitment not to deploy models that show meaningful catastrophic misuse risk under adversarial testing by world-class red-teamers.
The policy may require temporarily pausing training when AI scaling outpaces the ability to meet safety procedures, while using prior-level models to help develop safety features for the next level.
Source and freshness
- Source
- anthropic.com
- Published
- Added to Yomu
Summaries are generated from the original by a language model. Check the original before relying on it.
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