Open Problems in Frontier AI Risk Management
Marta Ziosi, Miro Plueckebaum, Stephen Casper, Henry Papadatos, Ze Shen Chin, Peter Slattery, James Gealy, Tim G. J. Rudner, Brian Tse, Ariel Gil, Patricia Paskov, Maximilian Negele, Rokas Gipi\v{s}kis, Nada Madkour, Vera Lummis, Rupal Jain, Luise Eder, Kristina Fort

TL;DR
This paper systematically identifies open challenges in managing risks associated with frontier AI, emphasizing the need for better consensus, frameworks, and coordinated efforts among stakeholders.
Contribution
It provides a structured review of unresolved problems in frontier AI risk management, classifies them, and maps responsible actors to guide future research and policy.
Findings
Identifies key open problems across risk management stages.
Classifies problems based on consensus, framework alignment, and implementation issues.
Maps actors best suited to address each open problem.
Abstract
Frontier AI both amplifies existing risks and introduces qualitatively novel challenges. Not only is there a notable lack of stable scientific consensus resulting from the rapid pace of technological change, but emerging frontier AI safety practices are often misaligned with, or may undermine, established risk management frameworks. To address these challenges, we systematically surface open problems in frontier AI risk management. Adopting a problem-oriented approach, we examine each stage of the risk management process - risk planning, identification, analysis, evaluation, and mitigation - through a structured review of the literature, identifying unresolved challenges and the actors best positioned to address them. Recognising that different types of open problems call for different responses, we classify open problems according to whether they reflect (a) a lack of scientific or…
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