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20232026
most citedComputing Power and the Governance of Artificial Intelligence

22 citations · 33 across the 4 of their papers we have counts for

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5 papers · 1 filter

cs.CY2026

Prioritization of Risks from Artificial Intelligence: A Delphi Study of 272 International Experts

Alexander K. Saeri, Jess Graham, Michael Noetel +185

Artificial intelligence poses many risks, ranging from familiar present-day harms to unprecedented and potentially catastrophic ones. Effective risk management requires prioritizat…

cs.CY2025

Distributed and Decentralised Training: Technical Governance Challenges in a Shifting AI Landscape

Jakub Kryś, Yashvardhan Sharma, Janet Egan

Advances in low-communication training algorithms are enabling a shift from centralised model training to compute setups that are either distributed across multiple clusters or dec…

cs.CY20244 cited

Governing Through the Cloud: The Intermediary Role of Compute Providers in AI Regulation

Lennart Heim, Tim Fist, Janet Egan +5

As jurisdictions around the world take their first steps toward regulating the most powerful AI systems, such as the EU AI Act and the US Executive Order 14110, there is a growing…

cs.CY202422 cited

Computing Power and the Governance of Artificial Intelligence

Girish Sastry, Lennart Heim, Haydn Belfield +16

Computing power, or "compute," is crucial for the development and deployment of artificial intelligence (AI) capabilities. As a result, governments and companies have started to le…

cs.CY20237 cited

Oversight for Frontier AI through a Know-Your-Customer Scheme for Compute Providers

Janet Egan, Lennart Heim

To address security and safety risks stemming from highly capable artificial intelligence (AI) models, we propose that the US government should ensure compute providers implement K…