Page 10: 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.

Consumer & Gadgets

What does it mean to train an AI to speak like you?

Ultra-personalized artificial intelligence for assisted communication risks muting aspects of the user's identity and occasionally breaches privacy, according to a new study from a Cornell Tech doctoral student who trained ...

Consumer & Gadgets

The friendlier AI gets, the more it can backfire

Major AI platforms, including OpenAI and Anthropic, as well as social apps like Replika and Character.ai, are increasingly designing chatbots to be warm, friendly, and empathetic. However, new research from the Oxford Internet ...

Computer Sciences

Can AI quantify beauty? New study suggests it can't

Attempts to define human beauty using artificial intelligence may reveal more about bias in data than universal standards, according to a new analysis from the University of Virginia's School of Data Science. Using computer ...

Internet

How AI bias can creep into online content moderation

A University of Queensland study has shown large language models (LLMs) used in AI content moderation may be prone to subtle biases that undermine their neutrality. A team led by data scientist Professor Gianluca Demartini ...

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