constitutional ai

**Constitutional AI** **What is Constitutional AI?** Constitutional AI (CAI) is an alignment approach by Anthropic that uses a set of principles to guide AI behavior, reducing reliance on human feedback for every scenario. **Core Concept** Instead of collecting human feedback for every case, define principles (a "constitution") that the model uses for self-improvement. **The CAI Process** **Stage 1: Supervised Learning with Self-Critique** ``` 1. Generate initial response 2. Critique response against principles 3. Revise response based on critique 4. Fine-tune on revised responses ``` **Stage 2: RLHF with AI Feedback (RLAIF)** ``` 1. Generate response pairs 2. AI evaluates which is better (using principles) 3. Train reward model on AI preferences 4. RLHF as usual ``` **Example Constitution Principles** ``` - Be helpful, harmless, and honest - Refuse to help with illegal activities - Correct mistakes when pointed out - Express uncertainty when appropriate - Avoid stereotypes and bias - Protect user privacy - Do not pretend to be human ``` **Self-Critique Example** ``` [Original response]: [potentially harmful content] [Critique]: This response violates the principle of being harmless because it provides information that could be used to harm others. [Revised response]: I cannot provide that information because it could be used to cause harm. Instead, let me suggest... ``` **Benefits** | Benefit | Description | |---------|-------------| | Scalable | Less human annotation needed | | Transparent | Principles are explicit | | Consistent | Same principles applied everywhere | | Maintainable | Update principles as needed | **Implementation Approach** ```python def constitutional_revision(response: str, principles: list) -> str: # Self-critique critique = llm.generate(f""" Given these principles: {principles} Critique this response: {response} Identify any violations of the principles. """) # Revision revised = llm.generate(f""" Original response: {response} Critique: {critique} Generate a revised response that addresses the critique while remaining helpful. """) return revised ``` **Comparison to RLHF** | Aspect | RLHF | CAI | |--------|------|-----| | Human involvement | Every preference | Define principles once | | Scalability | Limited by humans | Highly scalable | | Transparency | Implicit in data | Explicit principles | | Consistency | Varies with annotators | Consistent | Constitutional AI is foundational to Anthropic Claude models.

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