Alignment Research
The effort to make AI systems pursue goals that actually match what humans want.
Think of it like
Like training a dog to retrieve what you throw, not just to fetch anything it finds.
Example
Researchers study how to train models to refuse requests that violate policies without becoming so cautious they refuse everything reasonable.
How it actually works
Alignment is hard because human intent is ambiguous and contradictory. People want efficiency, but also fairness. They want personalization, but also privacy. Alignment research explores reward modeling, constitutional AI, interpretability, and evaluation methods to bridge the gap between what we say we want and what the model actually optimizes for.
For product teams
Invest in alignment work to ship products that behave as intended and earn user trust.
For engineers
Use RLHF, evals, and interpretability tools to align model behavior with stated values.
Related
- Value Alignment — Explicit value definition.
- RLHF — Training technique.
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