In a digital epoch where cyberspace is the emerging nexus of geopolitical
contention, the melding of information operations and Large Language Models
(LLMs) heralds a paradigm shift, replete with immense opportunities and
intricate challenges. As tools like the Mistral 7B LLM (Mistral, 2023)
democratise access to LLM capabilities (Jin et al., 2023), a vast spectrum of
actors, from sovereign nations to rogue entities (Howard et al., 2023), find
themselves equipped with potent narrative-shaping instruments (Goldstein et
al., 2023). This paper puts forth a framework for navigating this brave new
world in the "ClausewitzGPT" equation. This novel formulation not only seeks to
quantify the risks inherent in machine-speed LLM-augmented operations but also
underscores the vital role of autonomous AI agents (Wang, Xie, et al., 2023).
These agents, embodying ethical considerations (Hendrycks et al., 2021), emerge
as indispensable components (Wang, Ma, et al., 2023), ensuring that as we race
forward, we do not lose sight of moral compasses and societal imperatives.
Mathematically underpinned and inspired by the timeless tenets of
Clausewitz's military strategy (Clausewitz, 1832), this thesis delves into the
intricate dynamics of AI-augmented information operations. With references to
recent findings and research (Department of State, 2023), it highlights the
staggering year-on-year growth of AI information campaigns (Evgeny Pashentsev,
2023), stressing the urgency of our current juncture. The synthesis of
Enlightenment thinking, and Clausewitz's principles provides a foundational
lens, emphasising the imperative of clear strategic vision, ethical
considerations, and holistic understanding in the face of rapid technological
advancement.

在数字时代中，信息操作和大语言模型的融合标志着一个充满机遇和挑战的新时代。本文提出了一个用于应对这个全新世界的框架，探讨了人工智能增强信息操作的复杂动态，重视自主 AI 代理的道德考虑，并强调清晰的战略愿景、伦理考虑和整体理解在快速技术进步面前的重要性。

克劳塞维茨 GPT 框架：理论大语言模型增强信息行动的新前沿

ClausewitzGPT Framework: A New Frontier in Theoretical Large Language  Model Enhanced Information Operations

Among the goals of information operations are to change the overall
information environment vis-á-vis specific actors. For example, "trolling
campaigns" seek to undermine the credibility of specific public figures,
leading others to distrust them and intimidating these figures into silence. To
accomplish these aims, information operations frequently make use of "trolls"
-- malicious online actors who target verbal abuse at these figures. In Brazil,
in particular, allies of Brazil's current president have been accused of
operating a "hate cabinet" -- a trolling operation that targets journalists who
have alleged corruption by this politician and other members of his regime.
Leading approaches to detecting harmful speech, such as Google's Perspective
API, seek to identify specific messages with harmful content. While this
approach is helpful in identifying content to downrank, flag, or remove, it is
known to be brittle, and may miss attempts to introduce more subtle biases into
the discourse. Here, we aim to develop a measure that might be used to assess
how targeted information operations seek to change the overall valence, or
appraisal, of specific actors. Preliminary results suggest known campaigns
target female journalists more so than male journalists, and that these
campaigns may leave detectable traces in overall Twitter discourse.

该研究旨在开发一种可用于评估目标信息操作改变特定角色总体价值或评估的措施。初步结果表明已知的活动更多地针对女记者，这些活动可能会在整体 Twitter 讨论中留下可检测的痕迹。