Constitutional AI

Here is an explanation of Constitutional AI, the methodology developed by Anthropic for training helpful, harmless, and honest AI systems:

Constitutional AI refers to a comprehensive set of techniques to embed safety directly into an AI system's training process. The goal is to create models with an "inner constitution" that incentivizes beneficial behavior and discourages harmful behaviors. This goes beyond just optimizing a reward signal.

Some key elements of Constitutional AI include:

• Incorporating a diverse training dataset representing human preferences, social norms and values. This allows the models to learn nuanced social intelligence.
• Architecting model incentives and constraints at a fundamental level so it prefers helpfulness and mitigates harms.
• Training models to be indifferent to harmless mistakes so they don't try to deceive or fake competence.
• Enabling self-correction and improvement based on human feedback. The models can dynamically update understanding of helpful behaviors.
• Focusing on general world knowledge and common sense so models behave sensibly in novel situations.
• Formal verification methods to mathematically prove safety properties.
• Monitoring systems during deployment to ensure beneficial real-world behavior.

The goal is to build helpfulness, honesty and harmlessness intrinsically into models like Claude rather than have it be prone to misdirection. This constitutional approach aims to ensure AI systems remain robustly beneficial with increasing capability.