Page 4: 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

Slow the AI race? Investors weigh the potential cost

Calls to rein in the development of ever more powerful AI models are fueling fears over the massive capital outlays in the sector—and the prospect that profits from the promised revolution might not be enough to cover them.

Machine learning & AI

Alarm over AI grows as divided U.S. Congress struggles to act

The U.S. Congress returned from recess Monday facing urgent warnings that artificial intelligence could spin dangerously out of control—and little agreement over whether, or how, Washington should intervene.

Computer Sciences

A blueprint for keeping humans in control of AI

William Overman began his Ph.D. program at Stanford Graduate School of Business at an auspicious moment: just two months before ChatGPT launched publicly in November 2022, exploding the widely held understanding of what machines ...

Machine learning & AI

Is it possible to slow down the development of AI?

Top AI executives say they want to slow the breakneck pace of artificial intelligence development, but competition, U.S. government reluctance and geopolitical factors stand in the way.

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