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Constitutional AI(CAI)
Training AI agents to follow constitutional principles through self-critique and improvement cycles
๐ฏ 30-Second Overview
Pattern: Train AI systems using explicitly defined principles and AI-generated feedback to achieve harmless, helpful behavior
Why: Scales oversight beyond human capacity, reduces harmful outputs, and creates transparent value-aligned AI systems
Key Insight: Constitutional principles guide AI feedback generation, creating self-supervising systems aligned with explicit values
โก Quick Implementation
๐ Do's & Don'ts
๐ฆ When to Use
Use When
- โข Building systems requiring strong ethical alignment
- โข Reducing human annotation costs for safety training
- โข Scaling oversight to complex AI behaviors
- โข Implementing transparent value-based AI systems
- โข Creating self-regulating AI with explicit principles
Avoid When
- โข Simple tasks with clear objective metrics
- โข Domains requiring strict regulatory compliance
- โข Systems needing real-time human oversight
- โข Applications with zero tolerance for errors
- โข Contexts with highly contested moral principles
๐ Key Metrics
๐ก Top Use Cases
References & Further Reading
Deepen your understanding with these curated resources
Foundational Papers
Implementation & Scaling
Scaling Laws for Reward Model Overoptimization (Gao et al., 2022)
Training language models to follow instructions with human feedback (Ouyang et al., 2022)
Teaching language models to support answers with verified quotes (Menick et al., 2022)
Constitutional AI at Scale: Implementation Lessons (Anthropic, 2023)
RLHF & Preference Learning
Contribute to this collection
Know a great resource? Submit a pull request to add it.
Constitutional AI(CAI)
Training AI agents to follow constitutional principles through self-critique and improvement cycles
๐ฏ 30-Second Overview
Pattern: Train AI systems using explicitly defined principles and AI-generated feedback to achieve harmless, helpful behavior
Why: Scales oversight beyond human capacity, reduces harmful outputs, and creates transparent value-aligned AI systems
Key Insight: Constitutional principles guide AI feedback generation, creating self-supervising systems aligned with explicit values
โก Quick Implementation
๐ Do's & Don'ts
๐ฆ When to Use
Use When
- โข Building systems requiring strong ethical alignment
- โข Reducing human annotation costs for safety training
- โข Scaling oversight to complex AI behaviors
- โข Implementing transparent value-based AI systems
- โข Creating self-regulating AI with explicit principles
Avoid When
- โข Simple tasks with clear objective metrics
- โข Domains requiring strict regulatory compliance
- โข Systems needing real-time human oversight
- โข Applications with zero tolerance for errors
- โข Contexts with highly contested moral principles
๐ Key Metrics
๐ก Top Use Cases
References & Further Reading
Deepen your understanding with these curated resources
Foundational Papers
Implementation & Scaling
Scaling Laws for Reward Model Overoptimization (Gao et al., 2022)
Training language models to follow instructions with human feedback (Ouyang et al., 2022)
Teaching language models to support answers with verified quotes (Menick et al., 2022)
Constitutional AI at Scale: Implementation Lessons (Anthropic, 2023)
RLHF & Preference Learning
Contribute to this collection
Know a great resource? Submit a pull request to add it.