An International Consortium for Evaluations of Societal-Scale Risks from Advanced AI
Ross Gruetzemacher, Alan Chan, Kevin Frazier, Christy Manning,, \v{S}t\v{e}p\'an Los, James Fox, Jos\'e Hern\'andez-Orallo, John Burden,, Matija Franklin, Cl\'iodhna N\'i Ghuidhir, Mark Bailey, Daniel Eth, Toby, Pilditch, Kyle Kilian

TL;DR
This paper advocates for establishing an international consortium involving AI developers and evaluators to improve governance, risk assessment, and coordination in advanced AI development to mitigate societal risks.
Contribution
It proposes a novel international consortium model for AI risk evaluation, addressing current ecosystem shortcomings and enhancing global coordination and oversight.
Findings
Current evaluation ecosystem faces coordination challenges
A consortium can improve risk assessment and oversight
Concrete steps for establishing the consortium are outlined
Abstract
Given rapid progress toward advanced AI and risks from frontier AI systems (advanced AI systems pushing the boundaries of the AI capabilities frontier), the creation and implementation of AI governance and regulatory schemes deserves prioritization and substantial investment. However, the status quo is untenable and, frankly, dangerous. A regulatory gap has permitted AI labs to conduct research, development, and deployment activities with minimal oversight. In response, frontier AI system evaluations have been proposed as a way of assessing risks from the development and deployment of frontier AI systems. Yet, the budding AI risk evaluation ecosystem faces significant coordination challenges, such as a limited diversity of evaluators, suboptimal allocation of effort, and perverse incentives. This paper proposes a solution in the form of an international consortium for AI risk…
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Taxonomy
TopicsEthics and Social Impacts of AI · Explainable Artificial Intelligence (XAI) · Artificial Intelligence in Healthcare and Education
