Responsible Scaling Policy
Also written: RSP
A company's plan for assessing and managing risks as AI models become more powerful.
A Responsible Scaling Policy (RSP) is a company's public commitment to developing AI safely. As AI models get more capable, they can also become more dangerous if misused or if they behave in unexpected ways.
An RSP outlines how a company will watch for these risks and what steps it will take if certain danger levels are reached. For example, a company might promise to do extra safety testing or slow down development if a model shows signs of becoming too autonomous or easy to misuse for harmful purposes.
A Responsible Scaling Policy (RSP) is a documented framework by an AI developer detailing how they will assess and mitigate risks associated with increasingly capable AI systems. It typically defines thresholds for model capabilities, autonomy, and potential misuse, triggering specific safety measures, development slowdowns, or enhanced oversight when these thresholds are approached or crossed. The goal is to ensure that AI development proceeds cautiously, with safety measures scaling alongside model power.
Anthropic's recent endorsements of California legislation like SB 53 highlight the growing focus on AI safety and transparency. These actions demonstrate a proactive approach by leading AI labs to engage with policymakers on how powerful AI systems should be developed and overseen, aligning with the principles of their Responsible Scaling Policies.
- Anthropic is endorsing SB 53Anthropic · Anthropic News ·
- Anthropic’s response to Governor Newsom’s AI working group draft reportAnthropic · Anthropic News ·
- Expanding Access to Claude for GovernmentAnthropic · Anthropic News ·
- Anthropic Claude
- Anthropic has publicly detailed its Responsible Scaling Policy as a core part of its approach to developing and deploying advanced AI systems like Claude.
- AI Safety Research
- This is the broader field of study focused on ensuring AI sy
- AI Alignment
- This refers to the technical challenge of ensuring AI systems purs
- AI Ethics Guidelines
- These are general principles for responsible AI developmen
The concept of a Responsible Scaling Policy was notably introduced and detailed by Anthropic as a foundational element of their AI development philosophy, emphasizing a cautious approach to scaling AI capabilities. Source ↗
Explore Anthropic's website for their public statements on Responsible Scaling Policies. Read their detailed policy document to understand the specific risks they monitor and the safety measures they plan to implement as their AI models advance.
The Playbook: reusable how-tos, prompts, configs and tips pulled out of the news.
- PromptRole-play a student struggling with math for AI tutor simulationSimulate a student's math struggles and uncertainty for AI tutor evaluation. · 5 min
- TemplateReusable workflow templates for healthcare teamsTeams can create and share templates for common workflows like documentation or prior authorizations. · 15 min
- TemplateTemplate for building an AI tool tailored to your workA structured approach to defining and building a custom AI tool for specific business needs. · 15 min
- TemplateEvals CSV prompt list for agent skillsA CSV file template for listing prompts used in evaluating agent skills. · 20 min
- HeuristicDouble coding agent task completion with docs linksProviding coding agents with a documentation link significantly increases their task completion rate. · 2 min
Questions people ask
- What is the main goal of a Responsible Scaling Policy?
- The main goal is to ensure that as AI models become more powerful and capable, the safety measures and risk assessments also increase proportionally, preventing potential harms.
- Who creates Responsible Scaling Policies?
- These policies are typically created by leading AI development companies, like Anthropic, as a public commitment to responsible AI advancement.
First seen on Subvolts Sep 10, 2024. Updated Sep 9, 2026. Written by an AI model from the items above and reviewed against them weekly; report an error.