Constitutional AI (CAI)

advancedspreading

A training method in which a language model evaluates and corrects its own answers based on a described set of principles, the 'constitution', to learn safe behavior.

In plain terms

Constitutional AI is a method developed by Anthropic to make a language model not only smart but also well-behaved. Instead of showing the model tens of thousands of individual examples of good and bad answers, developers write down a set of principles in everyday language, and the model learns to align its behavior with them.

It is like when you do not explain a thousand specific cases to a new colleague but give them the company's code of ethics and ask them to review and correct all their work against it. After a while, they no longer need to take out the code of ethics because the mindset has become part of their work.

In traditional solutions, large groups of people evaluate model responses, which is slow, expensive, and requires evaluators to read through much offensive content. Here, the AI performs most of the evaluation based on written principles. Moreover, these principles can be public, allowing you to read what the model adheres to.

How it works

Developers write the 'constitution': a list of natural language principles stating that the model should be helpful, honest, and cause no harm.
The model answers sensitive or provocative questions, then evaluates its own answer based on principles and rewrites it for improvement.
The model is further trained on improved responses, so it now gives answers aligned with principles on the first try.
In the second round, the model compares answer pairs and decides which one better complies with the constitution. These judgments form the basis of the reward, which refines behavior using AI feedback instead of human scorers.
The result is a model where principles function not as external filters but as part of learned behavior. The company then tests where it still makes mistakes.

An everyday example

You ask a chatbot to write a humiliating message to your ex-partner. You do not get a dry error message but a polite refusal and an offer to help phrase calmly what is upsetting. This behavior does not come from a blocklist but from training the model according to written principles.

Who is affected

everyoneIf you use an AI assistant, such principles decide what it helps with, what it refuses, and what tone it uses to speak to you.

developerIf you build a product or agent on a model, you must know the built-in principles governing its behavior, as your instructions cannot fully override these. → Code

entrepreneur, executiveWhen selecting a model, it matters whether the manufacturer publicly commits to the values governing its system.

lawyer, citizenA public set of principles makes it easier to hold a private company to account for the values it builds into a technology used by the masses. → Law

A common misconception

MythConstitutional AI means that artificial intelligence complies with the country's constitution and laws.

In realityHere, the 'constitution' is not a legal text but a collection of principles written by the developer company regarding the model's behavior. It has nothing to do with state constitutions and does not guarantee legal compliance.

Limits and risks

The principles are written by a private company, so they reflect its value judgment, not a democratically accepted consensus.
The method is not a guarantee: the model can still make mistakes, and clever tricks (jailbreaks) can be used to force it to violate principles.
Principles sometimes clash, such as helpfulness with caution, so the model can be overly strict or overly permissive.
Just because the principles are public does not mean you can see how a specific answer is generated.

Similar, but not the same

system prompt – A system prompt is an instruction received during a conversation that the operator can rewrite at any time, while constitutional AI embeds principles into the model during training.
Content filter (guardrail) – The filter acts as an external gatekeeper stopping incoming requests or ready answers, whereas in constitutional AI, the model itself learns to respond differently.
reinforcement learning from human feedback (RLHF) – In RLHF, humans score the answers; in constitutional AI, the model largely does this based on written principles.

Related concepts

Broader

AI safety, AI alignment, Responsible AI, model training

Narrower

collective constitutional AI

On the edge

constitutional classifiers, reinforcement learning, fine-tuning, system prompt, guardrail, jailbreak

A brief history

The method was described by Anthropic researchers in December 2022 in the study titled "Constitutional AI: Harmlessness from AI Feedback." In 2023, the company made public the principles on which it trained its model named Claude. In January 2026, it published a much longer, explanatory constitution in place of these.

Where things stand

The method and its improved variants are still part of the training of Anthropic's Claude models. In January 2026, the company published a much more detailed, public constitution, which is no longer a short list of rules but a text explaining the model's values and their rationale. Other developers also publish similar behavioral principles (such as OpenAI's document called Model Spec), but there is no unified industry standard.

Status: 2026 November

Also known as

Constitutional AI · Constitutional AI · constitutional artificial intelligence · Constitutional AI · CAI · AI constitution · Claude's constitution · Claude's Constitution

Sources

This entry was machine-edited and has undergone machine expert review; the “In the news” section updates automatically from Agent Age stories.