AI Alignment

When an AI system follows the letter of an instruction but misses its intent, the problem is one of AI alignment. Alignment aims to keep model behavior consistent with human goals, safety constraints, and acceptable social values, including in unfamiliar situations. The challenge is that people express preferences imperfectly, measurable objectives can reward shortcuts, and values may conflict across users or contexts. Researchers and product teams address this gap through preference training, behavioral policies, red-team evaluations, access controls, uncertainty handling, and human review. Alignment is therefore not a single training technique; it is an ongoing process that combines model design, governance, testing, and operational oversight.