Page 35: 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.

Software

AI threats in software development revealed in new study

UTSA researchers recently completed one of the most comprehensive studies to date on the risks of using AI models to develop software. In a new paper, they demonstrate how a specific type of error could pose a serious threat ...

Machine learning & AI

Why AI can't take over creative writing

In 1948, the founder of information theory, Claude Shannon, proposed modeling language in terms of the probability of the next word in a sentence given the previous words. These types of probabilistic language models were ...

Robotics

That 'uhh... let me think' face you make? Androids need it too

Ever asked a question and been met with a blank stare? It's awkward enough with a person—but on a humanoid robot, it can be downright unsettling. Now, an international team co-led by Hiroshima University and RIKEN has found ...

Machine learning & AI

Firms and researchers at odds over superhuman AI

Hype is growing from leaders of major AI companies that "strong" computer intelligence will imminently outstrip humans, but many researchers in the field see the claims as marketing spin.

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