AI Alignment
Making AI act in accordance with human intent and values
AI Alignment is a research field focused on aligning AI system goals and behaviors with human intent, values, and ethics. It starts from the recognition that powerful AI misaligned with human intent could pose serious risks. Anthropic's "Helpful, Harmless, Honest (HHH)" framework is representative. Technically implemented through RLHF, Constitutional AI, DPO, etc., with research topics including Reward Hacking, Goal Misgeneralization, and Deceptive Alignment. Short-term goals include preventing harmful outputs; long-term goals include safe operation of superhuman AI.
Key Concepts
Define human values/intent โ establish principles like "Helpful, Harmless, Honest"
Learn basic instruction following through SFT
Align to human preferences via RLHF/DPO/Constitutional AI
Red Teaming โ discover vulnerabilities through adversarial testing
Implement safeguards โ refuse harmful requests, express uncertainty, etc.
Continuous monitoring โ discover and fix issues from real-world usage after deployment
Pros
- ✓ Reduced harmful outputs
- ✓ Improved user trust
- ✓ Regulatory compliance
- ✓ Long-term AI safety assurance
Cons
- ✗ Definition of "alignment" is subjective
- ✗ Excessive safety filters reduce usefulness (over-refusal)
- ✗ Alignment Tax โ performance degradation
- ✗ Difficulty detecting deceptive alignment