Anthropic’s Responsible Scaling Policy: Version 3.0

2026-02-23 · Source: Anthropic News · Field: Technology & Digital — Artificial Intelligence & Machine Learning, AI Safety & Governance · Depth: Intermediate, long

Summary

Anthropic has released Version 3.0 of its Responsible Scaling Policy (RSP), a voluntary framework designed to mitigate catastrophic risks from AI systems. This update refines the original September 2023 policy, which used "if-then" conditional commitments and AI Safety Levels (ASLs) to introduce safeguards as model capabilities advanced. While the previous RSP successfully incentivized stronger internal safeguards, such as input/output classifiers for ASL-3 deployment in May 2025, and encouraged similar frameworks from OpenAI and Google DeepMind, it faced challenges. Specifically, pre-set capability thresholds proved ambiguous for achieving industry consensus, and government action on AI safety has been slower than anticipated. The new RSP addresses these issues by separating Anthropic's unilateral plans from its industry recommendations, introducing a public Frontier Safety Roadmap with ambitious yet achievable goals, and implementing regular, externally reviewable Risk Reports to enhance transparency and accountability.

Key takeaway

For CTOs and VPs of Engineering evaluating AI safety frameworks, Anthropic's RSP v3.0 highlights the necessity of distinguishing internal, achievable safeguards from broader industry recommendations. Your teams should consider implementing a public roadmap with ambitious yet graded safety goals and commit to regular, transparent risk reporting, potentially with external review, to build trust and drive internal accountability, especially as AI capabilities rapidly evolve beyond current regulatory landscapes.

Key insights

Anthropic's updated Responsible Scaling Policy refines AI risk mitigation by separating internal commitments from industry recommendations and enhancing transparency.

Principles

• Conditional commitments drive safeguard development.
• Transparency fosters industry accountability.
• Unilateral action has limits for advanced AI risks.

Method

The updated RSP separates company plans from industry recommendations, introduces a public Frontier Safety Roadmap with graded goals, and mandates regular, externally reviewable Risk Reports detailing model safety profiles.

In practice

• Develop input/output classifiers for content moderation.
• Publish a Frontier Safety Roadmap for public accountability.
• Conduct regular, externally reviewed Risk Reports.

Topics

• Responsible Scaling Policy
• AI Risk Mitigation
• Frontier Safety Roadmap
• AI Policy and Governance
• Model Evaluation

Best for: CTO, VP of Engineering/Data, Executive, Policy Maker, AI Ethicist, Director of AI/ML

Related on AIssential

• Anthropic Responsible Scaling Policy v3: Dive Into The Details — Anthropic's RSP v3.0 prioritizes flexibility and trust over concrete commitments for AI safety, raising concerns about accountability.
• The Dark Side of Anthropic’s Growth — Anthropic's rapid commercial growth creates fundamental tensions with its founding AI safety and ethical commitments.
• Anthropic’s Safety Superpower — Anthropic's "safety" narrative strategically aligns with its economic and power imperatives to control frontier AI development and user data.
• Anthropic loosens safety pledge to compete with its AI peers - marketplace.org — Anthropic is relaxing its strict AI safety policy to compete in the rapidly evolving AI market.
• Anthropic confronts the RSI clock — AI systems are already significantly accelerating their own development, raising concerns about future autonomous self-improvement.
• ‘Safety first’ puts Anthropic ahead in game of AI spin — Independent validation of AI safety claims is crucial, especially when public releases are restricted.

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Editorial summary, takeaway, and curation by AIssential. Original article published by Anthropic News.