On Large Language Models in National Security Applications
William N. Caballero, Phillip R. Jenkins

TL;DR
This paper discusses the transformative potential of large language models in national security, highlighting their benefits, risks, current applications, and the need for safeguards to ensure reliable and strategic use.
Contribution
It analyzes the integration of LLMs in national security, coupling them with decision-theoretic principles, and explores their applications, risks, and strategic implications.
Findings
LLMs can enhance decision-making and operational efficiency in national security.
Current applications include wargaming and automatic summarization by the US Department of Defense.
Risks such as hallucinations and adversarial attacks require rigorous safeguards.
Abstract
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…
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Taxonomy
TopicsNetwork Security and Intrusion Detection · Topic Modeling
MethodsAttention Is All You Need · Linear Layer · Multi-Head Attention · Softmax · Residual Connection · Byte Pair Encoding · Layer Normalization · Label Smoothing · Adam · Dropout
