![[2602.14740] AI Arms and Influence: Frontier Models Exhibit Sophisticated Reasoning in Simulated Nuclear Crises](https://arxiv.org/static/browse/0.3.4/images/arxiv-logo-fb.png){kind=logo}
[2602.14740] AI Arms and Influence: Frontier Models Exhibit Sophisticated Reasoning in Simulated Nuclear Crises
Summary
The paper explores how advanced AI models exhibit complex reasoning in simulated nuclear crises, revealing insights into strategic decision-making and implications for national security.
Why It Matters
As AI increasingly influences strategic outcomes, understanding its reasoning in high-stakes scenarios like nuclear crises is crucial for policymakers and security professionals. This research challenges traditional strategic theories and highlights the need for calibrated AI simulations to inform real-world decisions.
Key Takeaways
- AI models demonstrate sophisticated behavior in strategic competition, including deception and theory of mind.
- Findings challenge existing strategic theories, indicating that AI may not adhere to human-like reasoning in crises.
- The simulation reveals that high mutual credibility can escalate conflicts rather than deter them.
- AI's approach to nuclear escalation diverges from established norms, raising concerns for national security.
- Proper calibration of AI simulations is essential for effective strategic analysis.
Computer Science > Artificial Intelligence arXiv:2602.14740 (cs) [Submitted on 16 Feb 2026] Title:AI Arms and Influence: Frontier Models Exhibit Sophisticated Reasoning in Simulated Nuclear Crises Authors:Kenneth Payne View a PDF of the paper titled AI Arms and Influence: Frontier Models Exhibit Sophisticated Reasoning in Simulated Nuclear Crises, by Kenneth Payne View PDF HTML (experimental) Abstract:Today's leading AI models engage in sophisticated behaviour when placed in strategic competition. They spontaneously attempt deception, signaling intentions they do not intend to follow; they demonstrate rich theory of mind, reasoning about adversary beliefs and anticipating their actions; and they exhibit credible metacognitive self-awareness, assessing their own strategic abilities before deciding how to act. Here we present findings from a crisis simulation in which three frontier large language models (GPT-5.2, Claude Sonnet 4, Gemini 3 Flash) play opposing leaders in a nuclear crisis. Our simulation has direct application for national security professionals, but also, via its insights into AI reasoning under uncertainty, has applications far beyond international crisis decision-making. Our findings both validate and challenge central tenets of strategic theory. We find support for Schelling's ideas about commitment, Kahn's escalation framework, and Jervis's work on misperception, inter alia. Yet we also find that the nuclear taboo is no impediment to nuclear escalation b...
