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.

Engineering

Generative AI: Modeling a proper cuppa from a proper pot

The Yixing Zisha teapot sits neatly at the intersection of art, engineering and heritage. As such, it makes for an intriguing test case for a technology increasingly taking on creative tasks across almost every field of human ...

Business

Will companies ever be run by an AI CEO?

OpenAI's CEO Sam Altman has speculated about how long it will take for artificial intelligence to replace senior leadership teams in organizations. "Shame on me," Altman told the Conversations with Tyler podcast in November ...

Computer Sciences

Hidden goals can undermine AI teamwork, study finds

Large language models (LLMs), the computational models that underpin conversational agents such as Gemini and ChatGPT, are now widely used by people worldwide to rapidly find information, summarize documents and generate ...

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 ...

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