Page 2: Research news on AI governance

AI governance addresses the design, implementation, and evaluation of legal, institutional, and procedural mechanisms that guide the development and deployment of artificial intelligence systems. It encompasses national and international regulatory frameworks, management-based regulation, and dynamic governance models aimed at mitigating societal and existential risks. The domain integrates AI ethics, safety standards, red-teaming, and accountability tools, and involves multistakeholder participation in setting global norms, establishing red lines, and aligning AI infrastructure and literacy initiatives with evidence-based public policy.

Machine learning & AI

Germany to create AI safety agency

The German government has announced it is setting up an institute for artificial intelligence safety designed to analyze the performance and risks of AI models.

Machine learning & AI

Anthropic calls for pause of global AI development

Artificial intelligence company Anthropic suggested Thursday a global pause on building the most powerful AI systems as the latest models are beginning to show signs they could escape human control.

Machine learning & AI

New framework could standardize high-stakes AI in toxicology

A perspective in Frontiers in Artificial Intelligence titled "Evidence-based AI: from trailblazer to trustblazer?" introduces a formal discipline called Evidence-based AI that applies the rigorous standards of medicine and ...

Machine learning & AI

The race to regulate AI systems has lawyers getting creative

Can an artificial intelligence tool, such as a chatbot, be held responsible if people committed crimes based on information they got from the tool? Should chatbots, which are programmed to closely mimic human thought patterns ...

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