Page 7: 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

When AI seems to know you better than you know yourself

I was at my clinic the other day and asked an AI assistant about the differential diagnosis of a rash in a child. A routine question. The response came back clear and sensible. And then it added, "Are you asking about one ...

Machine learning & AI

Mythos AI alarm bells: Fair warning or marketing hype?

Anthropic postponing the release of its new AI model Claude Mythos, said to be so skilled at coding it could be a wicked weapon for hackers, has encountered a mix of alarm and skepticism.

Consumer & Gadgets

Explainability is a must for older adults to trust AI, study shows

Voice-activated, conversational artificial intelligence (AI) agents must provide clear explanations for their suggestions, or older adults aren't likely to trust them. That's one of the main findings from a study by AI Caring ...

Computer Sciences

New AI testing method flags fairness risks in autonomous systems

Artificial intelligence is increasingly being used to help optimize decision-making in high-stakes settings. For instance, an autonomous system can identify a power distribution strategy that minimizes costs while keeping ...

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