AI Safety Levels
Also written: ASLs, ASL, AI Safety Level-3, ASL-3, AI Safety Level 2, ASL-2
AI Safety Levels (ASLs) are categories that set safety rules for AI models based on their capabilities, similar to biosafety levels.
AI Safety Levels (ASLs) are like different security clearances for AI systems. The more powerful an AI is, the higher its safety level, and the more precautions are needed to use it safely.
Think of it like handling dangerous chemicals. A mild cleaner might have few rules, but a highly toxic substance requires a special lab and trained personnel. ASLs work similarly, assigning stricter safety protocols to more advanced AI models to prevent potential harm.
AI Safety Levels (ASLs) are a tiered framework, modeled after biological safety levels, used by some AI labs to categorize AI systems based on their capabilities and associated risks. Higher levels correspond to more advanced capabilities and necessitate more stringent safety and security measures during development, testing, and deployment.
This approach aims to manage catastrophic risks by ensuring that the controls applied to an AI system scale with its potential impact. The specific capabilities that trigger advancement to higher ASLs are defined by the developing organization, often involving benchmarks for reasoning, planning, and other cognitive abilities.
Anthropic recently announced its Responsible Scaling Policy, which introduces AI Safety Levels (ASLs) to manage risks from increasingly capable AI systems. This policy highlights the growing industry focus on proactively addressing potential dangers as AI models become more powerful.
- Introducing Claude Haiku 4.5Anthropic · Anthropic News ·
- Announcing Anthropic's Responsible Scaling PolicyAnthropic · Anthropic News ·
- Activating AI Safety Level 3 protectionsAnthropic · Anthropic News ·
- Testing our safety defenses with a new bug bounty programAnthropic · Anthropic News ·
- A new initiative for developing third-party model evaluationsAnthropic · Anthropic News ·
- Reflections on our Responsible Scaling PolicyAnthropic · Anthropic News ·
- Expanding Access to Claude for GovernmentAnthropic · Anthropic News ·
- Anthropic Claude
- Anthropic's Responsible Scaling Policy defines AI Safety Levels (ASLs) to manage risks associated with advanced AI capabilities.
- Biosafety Levels (BSLs)
- BSLs are used in biology to classify infectious agents
- Security Levels
- General security levels often refer to data access or system pr
The concept of AI Safety Levels was introduced by Anthropic as part of their Responsible Scaling Policy, drawing an analogy to established biosafety levels used in laboratories. Source ↗
You can observe differences in safety measures by interacting with different versions of an AI model. For example, try asking Claude 3 Opus (a more capable model) to perform a complex task that might be restricted or handled differently compared to an earlier, less capable model. Note any refusals or changes in its response style.
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Questions people ask
- What is the purpose of AI Safety Levels?
- AI Safety Levels are designed to ensure that the safety and security measures for an AI system match its capabilities and potential risks, especially for advanced models.
- How are AI Safety Levels determined?
- They are typically determined by an organization's internal assessment of an AI model's capabilities, such as its reasoning, planning, and problem-solving abilities, and the potential risks associated with those capabilities.
First seen on Subvolts Sep 10, 2024. Updated Oct 5, 2026. Written by an AI model from the items above and reviewed against them weekly; report an error.