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Artificial Intelligence and Nuclear Weapons Proliferation: The Technological Arms Race for visibility

2025-12-08 12:14:51
David M. Allison, Stephen Herzog

Abstract

A robust nonproliferation regime has contained the spread of nuclear weapons to just nine states. Yet, emerging and disruptive technologies are reshaping the landscape of nuclear risks, presenting a critical juncture for decision makers. This article lays out the contours of an overlooked but intensifying technological arms race for nuclear (in)visibility, driven by the interplay between proliferation-enabling technologies (PETs) and detection-enhancing technologies (DETs). We argue that the strategic pattern of proliferation will be increasingly shaped by the innovation pace in these domains. Artificial intelligence (AI) introduces unprecedented complexity to this equation, as its rapid scaling and knowledge substitution capabilities accelerate PET development and challenge traditional monitoring and verification methods. To analyze this dynamic, we develop a formal model centered on a Relative Advantage Index (RAI), quantifying the shifting balance between PETs and DETs. Our model explores how asymmetric technological advancement, particularly logistic AI-driven PET growth versus stepwise DET improvements, expands the band of uncertainty surrounding proliferation detectability. Through replicable scenario-based simulations, we evaluate the impact of varying PET growth rates and DET investment strategies on cumulative nuclear breakout risk. We identify a strategic fork ahead, where detection may no longer suffice without broader PET governance. Governments and international organizations should accordingly invest in policies and tools agile enough to keep pace with tomorrow's technology.

Abstract (translated)

一个稳健的不扩散制度已经将核武器扩散限制在了九个国家。然而,新兴和颠覆性技术正在重塑核风险的地缘政治格局,为决策者带来了关键时刻。本文阐述了一个被忽视但日益加剧的技术军备竞赛,这场竞赛围绕着核(不可见)性和由促进扩散技术(PETs)与增强检测技术(DETs)之间的相互作用所驱动。 我们论证说,未来的扩散战略将越来越受到这些领域创新速度的影响。人工智能(AI)为这一等式引入了前所未有的复杂性,其迅速扩展和知识替代能力加速了PET的发展,并挑战了传统的监测和验证方法。为了分析这种动态变化,我们开发了一个以相对优势指数(RAI)为中心的正式模型,量化PETs与DETs之间的平衡变动。 我们的模型探讨了技术发展不平衡(尤其是由逻辑AI驱动的PET增长与逐步改进的DET)如何扩大关于扩散可检测性的不确定性范围。通过基于情景的可重复模拟,我们评估了不同PET增长率和DET投资策略对累积核突破风险的影响。我们识别出一个战略岔路口,在此路口,仅靠增强检测可能不再足够有效,除非同时加强对促进扩散技术(PETs)的治理。 因此,政府和国际组织应当投资于能够与明日技术保持同步的政策工具和手段。

URL

https://arxiv.org/abs/2512.07487

PDF

https://arxiv.org/pdf/2512.07487.pdf


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