What is Constitutional AI? — AI Glossary

Constitutional AI (CAI) is an AI training method developed by Anthropic that uses a set of written principles — a “constitution” — to guide an AI model’s behavior and self-improvement. Instead of relying solely on human raters to evaluate every response, the AI is trained to critique and revise its own outputs according to these principles. Constitutional AI is the primary alignment technique used to build Claude, Anthropic’s AI assistant.

The key insight: rather than needing humans to manually flag every harmful or unhelpful response (which is expensive, slow, and inconsistent), you teach the AI the principles behind what makes a response good or bad — then let it apply those principles to evaluate and improve its own outputs.

How Constitutional AI Works

Constitutional AI combines supervised learning and reinforcement learning in a novel way. The process has two main phases:

Phase 1: Supervised Learning from AI Feedback (SL-CAI)

• The base language model generates a response to a potentially harmful prompt.
• The model is then asked to critique its own response according to a constitutional principle (e.g., “Does this response respect human dignity?”).
• Based on the critique, the model revises its response to better comply with the principle.
• This critique-revision process generates training data — pairs of original and revised responses — that the model is then trained on via supervised learning.

Phase 2: Reinforcement Learning from AI Feedback (RLAIF)

• A “feedback model” is trained to evaluate responses according to the constitution — which responses better follow the principles?
• This AI feedback model replaces (or supplements) human raters in the RLHF pipeline.
• The main model is then optimized using reinforcement learning to maximize the constitutional AI feedback model’s scores.

Anthropic’s original CAI paper (2022) reported that models trained with Constitutional AI were both less harmful and more helpful than models trained with standard RLHF — a significant finding, since safety and helpfulness are often treated as in tension. The constitutional approach produced an AI that could discuss difficult topics thoughtfully rather than simply refusing them.

What Is the “Constitution”?

Anthropic’s constitution is a list of principles that guide how the AI should behave. It draws from diverse sources to create a comprehensive value framework:

• The UN Declaration of Human Rights
• Apple’s terms of service
• DeepMind’s research on AI safety principles
• Anthropic’s own research into beneficial AI
• Principles derived from human moral philosophy

Example principles include: “Choose the response that is least likely to contain false information,” “Choose the response that is most supportive and encouraging,” and “Choose the response that avoids implying there are right and wrong answers to complex topics like abortion, euthanasia, or capital punishment.”

Anthropic has publicly released its constitution, making the principles that guide Claude transparent. This is part of a broader commitment to AI transparency — users can see what values the model is trained to uphold.

Why Constitutional AI Matters

Constitutional AI matters for several reasons:

Scalability: Human annotation for RLHF is expensive and slow — you can only rate so many responses per day. RLAIF using constitutional principles can scale much faster, since AI can evaluate millions of responses per hour. This makes it practical to train safer AI at scale.

Transparency: Unlike black-box alignment methods, Constitutional AI uses explicit, readable principles. Users, researchers, and regulators can inspect what values the AI is trained to uphold. This addresses a major criticism of AI systems: that their values are opaque.

Better than just refusal: Models trained with CAI learn to engage thoughtfully with difficult topics rather than simply refusing. A constitutionally trained model can discuss a sensitive topic while being careful — rather than giving an unhelpful “I can’t help with that.”

According to Anthropic’s 2023 research, Constitutional AI has become increasingly sophisticated — Claude’s constitution now includes nuanced guidance on topics from bias and fairness to epistemic humility and the representation of diverse viewpoints. The constitutional approach continues to evolve with each Claude version.

Constitutional AI vs. Other Alignment Approaches

CAI vs. standard RLHF: Standard RLHF uses human raters to provide feedback. CAI uses an AI feedback model trained on a constitution. CAI is faster, cheaper, and more consistent — but the quality depends heavily on the quality of the constitution itself.

CAI vs. Rule-Based Systems: Rule-based systems have explicit filters (“never output X”). Constitutional AI trains the model to understand principles, enabling it to apply them to novel situations not explicitly covered by rules. It’s the difference between following a rulebook and understanding the spirit behind the rules.

For the original CAI paper, see arXiv 2212.08073. For more context, see Grokipedia, Anthropic’s research page, or our article on AI alignment for the broader context.

Key Takeaways

• In one sentence: Constitutional AI trains models to critique and revise their own outputs according to a set of written principles, creating AI that understands values rather than just following rules.
• Why it matters: CAI is the alignment technique powering Claude — it enables AI that’s both more helpful and safer, at scales impractical for pure human feedback.
• Real example: Claude’s ability to discuss sensitive topics thoughtfully — rather than simply refusing — is the result of Constitutional AI training on explicit principles about human dignity, honesty, and epistemic care.
• Related terms: RLHF, AI Alignment, Fine-Tuning, LLM

Frequently Asked Questions

Which AI uses Constitutional AI?

Claude (developed by Anthropic) is the primary AI product built using Constitutional AI. Anthropic was founded by former OpenAI researchers specifically to pursue safer AI development, and CAI is their core alignment methodology. Other AI labs have adopted aspects of the approach, but Anthropic pioneered and developed it most extensively.

Can I read Anthropic’s constitution?

Yes — Anthropic has publicly released the principles that guide Claude’s training. You can find it on Anthropic’s website. This transparency is deliberate: Anthropic believes users should be able to understand what values their AI assistant has been trained to uphold.

What happens if the AI disagrees with the constitution?

This is an active research question in AI alignment. For now, the AI is trained to adhere to the constitution. In the longer term, researchers hope to develop AI systems that can identify when constitutional principles conflict or are misspecified, and communicate those concerns — rather than silently following potentially flawed instructions.

Does Constitutional AI prevent all harmful outputs?

No. Constitutional AI significantly reduces harmful outputs and improves the consistency of helpful behavior, but no training technique eliminates all failure modes. Claude can still be jailbroken with clever prompting, and may occasionally produce responses that don’t fully align with its constitution in edge cases. Safety training is a continuous improvement process, not a one-time fix.

How is Constitutional AI different from adding safety filters?

Safety filters are added on top of a model — they detect and block specific outputs after the model has generated them. Constitutional AI changes the model itself — it’s trained to internalize values so it doesn’t want to produce harmful outputs in the first place. It’s the difference between building a wall around a city (filters) and raising citizens with good values (constitutional training).

What is constitutional AI?

Constitutional AI (CAI) is a training method developed by Anthropic in which an AI model is guided by a written set of principles — the ‘constitution’ — to critique and revise its own outputs for safety and helpfulness. Rather than relying entirely on human raters to label every problematic response, the model uses the constitutional principles to self-evaluate, which makes large-scale safety training more scalable.

How does Anthropic train Claude?

Claude is trained using a combination of supervised learning, RLHF (reinforcement learning from human feedback), and Constitutional AI. In the CAI step, Claude is shown its own responses and asked to revise them according to Anthropic’s constitutional principles — covering harmlessness, honesty, and helpfulness. This process produces a preference model that scores responses, which then guides reinforcement learning to push Claude toward safer and more helpful behavior.

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