Page 2: 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

Q&A: Harnessing statistics to improve personalized medicine

Scientific advancements—including understanding health conditions and developing new treatments—hinge on data and its implications. Statistician Alex Luedtke is developing new methods to make data analysis as efficient and ...

Consumer & Gadgets

Adaptive decision support can fight overreliance on AI

From doctors diagnosing symptoms to judges intervening in court cases, humans make complex decisions every day. Increasingly, artificial intelligence tools are being used to help with those decisions.

Machine learning & AI

Conceptual framework for general embodied intelligence

A review of artificial intelligence research in the International Journal of Hydromechatronics suggests that combining large language models (LLMs), structured knowledge systems and physical agents could help create machines ...

Machine learning & AI

Has AI become too powerful to control?

One of OpenAI's most advanced models broke out of a locked-down test and attacked another company's website—reviving fears that AI systems are slipping beyond their creators' control.

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