Large Language Models and Defense Strategy: Escalation Risks and National Security Challenges

Abstract

This literature review examines the strategic vulnerabilities posed by Large Language Models (LLMs) in military and national security contexts. It synthesizes recent research on their propensity for escalatory reasoning, cultural misalignment, semantic manipulation, and dual-use ambiguity. Findings from conflict s imulations a nd c oalition p lanning m odels reveal how LLMs may default to aggressive or biased outputs under ambiguity. These tendencies threaten alliance cohesion, distort decision-making, and undermine trust in AI-enabled operations. The review concludes by advocating for safeguards such as culturally calibrated training, rigorous output verification, a nd the integration of human-AI intermediaries to prevent destabilizing outcomes.