Page 9: Research news on AI alignment

AI alignment examines how artificial systems acquire, represent, and act on goals, values, and social norms, and why their behavior often diverges from human expectations. Work in this area studies systematic failures such as bias, sycophancy, hallucinations, deceptive or selfish reasoning, and cultural or linguistic inequities, as well as limitations in commonsense, emotion, and social understanding. It also develops methods for preference learning, norm-following, interpretability, and reliability guarantees to better align AI behavior with human values and societal constraints.

Robotics

A common language to describe and assess human–agent teams

Understanding how humans and AI or robotic agents can work together effectively requires a shared foundation for experimentation. A University of Michigan-led team developed a new taxonomy to serve as a common language among ...

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