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.

Machine learning & AI

New framework could standardize high-stakes AI in toxicology

A perspective in Frontiers in Artificial Intelligence titled "Evidence-based AI: from trailblazer to trustblazer?" introduces a formal discipline called Evidence-based AI that applies the rigorous standards of medicine and ...

Consumer & Gadgets

How AI can become more transparent and reliable

When artificial intelligence is used to support or make important decisions in areas such as health care and public administration, it becomes crucial to understand how these systems arrive at their conclusions. A new doctoral ...

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