Large Language Models and Defense Strategy: Escalation Risks and National Security Challenges
Name
MIT-LIN-151484.pdf
Description
Main Report
Size
394.12 KB
Format
Adobe PDF
Checksum (MD5)
eff973118b7e59b0c923e335a2a5df07
Author(s)
Hou, Jonathan
Lax, Edwin
Date Issued
February 17, 2026
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.
Subjects
Large Language Models (LLMs)
MIT Department
Lincoln Laboratory
Persistent DSpace Link
