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Anthropic: Announcing our updated Responsible Scaling Policy
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High(4)High quality. Established institution or organization with editorial oversight and accountability.
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Anthropic's RSP is a landmark industry governance document; this update is significant for AI safety practitioners tracking how frontier labs operationalize safety commitments and capability-gated deployment policies.
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Importance: 78/100policy briefprimary source
Summary
Anthropic announces an updated version of its Responsible Scaling Policy (RSP), a framework that ties AI development and deployment decisions to specific capability thresholds called 'AI Safety Levels' (ASLs). The policy outlines concrete commitments around evaluations, safeguards, and conditions under which more powerful models can be trained or deployed.
Key Points
- •Introduces updated AI Safety Levels (ASL-1 through ASL-4+) as thresholds that trigger specific safety requirements before further scaling or deployment.
- •Commits Anthropic to mandatory capability evaluations before and after training new models to assess whether ASL thresholds have been crossed.
- •Specifies concrete technical and operational safeguards required at each ASL, particularly around CBRN (chemical, biological, radiological, nuclear) risks and autonomy.
- •Represents one of the first operationalized 'if-then' safety commitments from a frontier AI lab, making safety requirements contingent on measured capabilities.
- •Updated policy reflects lessons from deploying Claude models and aims to provide more specificity and accountability than the original 2023 RSP.
Cited by 5 pages
| Page | Type | Quality |
|---|---|---|
| Should We Pause AI Development? | Crux | 47.0 |
| Why Alignment Might Be Easy | Argument | 53.0 |
| Alignment Robustness Trajectory Model | Analysis | 64.0 |
| AI Lab Safety Culture | Approach | 62.0 |
| Voluntary AI Safety Commitments | Policy | 91.0 |
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Announcements
# Announcing our updated Responsible Scaling Policy
Oct 15, 2024
[Read the Responsible Scaling Policy](http://anthropic.com/rsp)
**Today we are publishing a significant update to our Responsible Scaling Policy (RSP), the risk governance framework we use to mitigate potential catastrophic risks from frontier AI systems.** This update introduces a more flexible and nuanced approach to assessing and managing AI risks while maintaining our commitment not to train or deploy models unless we have implemented adequate safeguards. Key improvements include new capability thresholds to indicate when we will upgrade our safeguards, refined processes for evaluating model capabilities and the adequacy of our safeguards (inspired by [safety case methodologies](https://arxiv.org/abs/2403.10462)), and new measures for internal governance and external input. By learning from our implementation experiences and drawing on risk management practices used in other high-consequence industries, we aim to better prepare for the rapid pace of AI advancement.
## The promise and challenge of advanced AI
As frontier AI models advance, they have the potential to bring about transformative benefits for our society and economy. AI could accelerate scientific discoveries, revolutionize healthcare, enhance our education system, and create entirely new domains for human creativity and innovation. However, frontier AI systems also present new challenges and risks that warrant careful study and effective safeguards.
In September 2023, we [released](https://www.anthropic.com/news/anthropics-responsible-scaling-policy) our Responsible Scaling Policy, a framework for managing risks from increasingly capable AI systems. After a year of implementation and learning, we are now sharing a significantly updated version that reflects practical insights and accounts for advancing technological capabilities.
Although this policy focuses on catastrophic risks like the categories listed below, they are not the only risks that we monitor and prepare for. Our [Usage Policy](https://www.anthropic.com/legal/aup) sets forth our standards for the use of our products, including rules that prohibit using our models to spread misinformation, incite violence or hateful behavior, or engage in fraudulent or abusive practices. We continually refine our technical measures for enforcing our trust and safety standards at scale. Further, we conduct research to understand the broader [societal impacts](https://www.anthropic.com/research#societal-impacts) of our models. Our Responsible Scaling Policy complements our work in these areas, contributing to our understanding of current and potential risks.
## A framework for proportional safeguards
As before, we maintain our core commitment: we will not train or deploy models unless we have implemented safety and security measures that keep risks below acceptable levels. Our RSP is based on the principle of proportional protection: safeguards tha
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