Alignment Research

Published:

Alignment research studies why AI systems can drift toward unintended goals as they become more capable, even when they look fine in testing. It focuses on failure modes where the system follows the letter of an objective while missing what people actually wanted. Work in this area develops training approaches that better reflect human intent and uses evaluations that reveal risky behavior before deployment.

A core assumption is that goals are never stated perfectly. Researchers and engineers probe systems to see what strategies they discover, then check how behavior changes in new settings. Oversight is designed to keep working when outputs are fast or persuasive. Many approaches also try to make decision-making easier to inspect, which helps teams catch problems early and correct course.

Follow us on Facebook and LinkedIn to keep abreast of our latest news and articles