Constitutional AI
/ˌkɒnstɪˈtjuːʃənəl eɪˈaɪ/
What is Constitutional AI?
Constitutional AI (CAI) is an alignment technique developed by Anthropic where an AI model is trained to follow a set of written principles — a "constitution" — rather than relying entirely on human feedback for every decision. The model uses these principles to critique and revise its own outputs, then is trained on the improved responses.
The approach builds on Reinforcement Learning from Human Feedback (RLHF) but adds a key innovation: instead of needing a human labeler to judge every response, the model itself can evaluate responses against the constitution. This makes the process more scalable and more transparent — anyone can read the principles and understand what the model is optimizing for.
Key Characteristics
- Principle-based: Behavior guided by explicit, readable rules rather than implicit patterns in human feedback data
- Self-supervised critique: The model evaluates its own outputs against the constitution
- Transparent: The principles are published, making alignment decisions auditable
- Scalable: Reduces dependency on large human labeling teams
- Iterative: The constitution can be updated as understanding of alignment improves
Why Constitutional AI Matters
For organizations building with AI, Constitutional AI matters because it makes alignment legible. When a model's behavior is governed by a readable set of principles, it's much easier to audit, explain, and customize than a model trained on opaque human preference data.
This has practical implications: enterprises can understand why a model refuses certain requests, and researchers can study how different constitutional principles affect model behavior. It also enables customization — in theory, different deployments could use different constitutions tuned to specific use cases.
Historical Context
Anthropic published the Constitutional AI paper in 2022, introducing the concept alongside Claude's first release. The name deliberately evokes the US Constitution — a set of foundational principles that guide decision-making. The co-founders describe the process of writing the constitution as extensive and collaborative, going through many drafts to reach consensus on principles that are both specific enough to be useful and general enough to cover edge cases.
Related Reading
- Responsible Scaling Policy - Anthropic's broader safety framework
- Reinforcement Learning - The training paradigm CAI builds on
- Dario Amodei - Anthropic CEO
Mentioned In
Anthropic Co-founders at 00:00:00
"Constitutional AI started as a consensus-building exercise where the team wrote down a set of principles — like a constitution — that guides model behavior, rather than relying solely on human labelers."