Definition
AI Alignment is the field focused on ensuring AI systems do what humans actually want them to do.
- **Key Challenges:**
- Specification: Precisely defining goals
- Robustness: Maintaining alignment under distribution shift
- Assurance: Verifying alignment
- Scalable Oversight: Supervising superhuman AI
Current Techniques: - RLHF (Reinforcement Learning from Human Feedback) - Constitutional AI - Red teaming - Interpretability research
- **Alignment Problems:**
- Reward Hacking: Gaming the objective
- Goal Misgeneralization: Wrong goals learned
- Deceptive Alignment: Appearing aligned but not
- Mesa-Optimization: Unintended inner goals
Why It Matters: - Prevent harmful AI behavior - Build trustworthy AI systems - Ensure AI benefits humanity - Critical for advanced AI safety
Examples
Training ChatGPT to refuse harmful requests while remaining helpful.
Related Terms
Training method using human preferences to make AI more helpful and safe.
Research field focused on ensuring AI systems are beneficial and don't cause harm.
Anthropic's training approach using principles to guide AI behavior without human labeling.
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