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Constitutional AI(CAI)
Using an explicit set of principles to guide self-critique, revision, and AI-generated preference feedback during training
Complexity: highLearning and Adaptation
In 30 seconds
- What
- Model learns to critique and revise its own outputs against explicit principles, then ranks responses using principle-aligned feedback without human labeling.
- When to use
- Training systems where you have clear behavioral principles but limited human feedback capacity, and need interpretable alignment during learning.
- Watch out
- Principles that conflict or are vague produce inconsistent training signals; model may learn to game principle-checking rather than internalize values.
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Constitutional AI: Overview
Using an explicit set of principles to guide self-critique, revision, and AI-generated preference feedback during training
- Explicit constitutional principles
- Self-critique and revision data
- Principle-conditioned preference judgments
- Supervised and reinforcement learning stages
- Conflict and ambiguity testing
- Human governance of the constitution
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References
The papers, specifications, and repositories this pattern is based on.
- Constitutional AI: Harmlessness from AI Feedback (2022)arXiv:2212.08073