Page 4: 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

Is recursive self‑improvement the dawning of AI superintelligence?

The US AI research company Anthropic has become known for building powerful AI models while simultaneously warning about their dangers. Most recently, its executives wrote about the threat posed by "recursive self-improvement." ...

Software

Reliably detecting and clearly explaining deepfake images

Artificial intelligence can now generate images that are virtually indistinguishable from real ones. Researchers at the Fraunhofer Institute of Optronics, System Technologies and Image Exploitation IOSB have developed RealOrRender, ...

Machine learning & AI

Top developers are pivoting from chatbots to physical AI

Computer scientist Louis Castricato was in his eighth year studying large language models—the artificial intelligence technology behind chatbots like ChatGPT and Claude—when he started to feel like he was hitting a dead end.

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