  The overwhelming success of GPT-4 in early 2023 highlighted the
transformative potential of large language models (LLMs) across various
sectors, including national security. This article explores the implications of
LLM integration within national security contexts, analyzing their potential to
revolutionize information processing, decision-making, and operational
efficiency. Whereas LLMs offer substantial benefits, such as automating tasks
and enhancing data analysis, they also pose significant risks, including
hallucinations, data privacy concerns, and vulnerability to adversarial
attacks. Through their coupling with decision-theoretic principles and Bayesian
reasoning, LLMs can significantly improve decision-making processes within
national security organizations. Namely, LLMs can facilitate the transition
from data to actionable decisions, enabling decision-makers to quickly receive
and distill available information with less manpower. Current applications
within the US Department of Defense and beyond are explored, e.g., the USAF's
use of LLMs for wargaming and automatic summarization, that illustrate their
potential to streamline operations and support decision-making. However, these
applications necessitate rigorous safeguards to ensure accuracy and
reliability. The broader implications of LLM integration extend to strategic
planning, international relations, and the broader geopolitical landscape, with
adversarial nations leveraging LLMs for disinformation and cyber operations,
emphasizing the need for robust countermeasures. Despite exhibiting "sparks" of
artificial general intelligence, LLMs are best suited for supporting roles
rather than leading strategic decisions. Their use in training and wargaming
can provide valuable insights and personalized learning experiences for
military personnel, thereby improving operational readiness.
