CYAIJul 29, 2025

Against racing to AGI: Cooperation, deterrence, and catastrophic risks

arXiv:2507.21839v12 citationsh-index: 1
Originality Synthesis-oriented
AI Analysis

This addresses the problem of catastrophic AI risks for policymakers and AI developers, advocating for incremental shifts in strategy rather than racing.

The paper argues against the AGI Racing view, contending that accelerating AI development increases catastrophic risks like nuclear instability and undermines AI safety research, while international cooperation offers lower-risk alternatives with similar benefits.

AGI Racing is the view that it is in the self-interest of major actors in AI development, especially powerful nations, to accelerate their frontier AI development to build highly capable AI, especially artificial general intelligence (AGI), before competitors have a chance. We argue against AGI Racing. First, the downsides of racing to AGI are much higher than portrayed by this view. Racing to AGI would substantially increase catastrophic risks from AI, including nuclear instability, and undermine the prospects of technical AI safety research to be effective. Second, the expected benefits of racing may be lower than proponents of AGI Racing hold. In particular, it is questionable whether winning the race enables complete domination over losers. Third, international cooperation and coordination, and perhaps carefully crafted deterrence measures, constitute viable alternatives to racing to AGI which have much smaller risks and promise to deliver most of the benefits that racing to AGI is supposed to provide. Hence, racing to AGI is not in anyone's self-interest as other actions, particularly incentivizing and seeking international cooperation around AI issues, are preferable.

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