How Malicious AI Swarms Can Threaten Democracy: The Fusion of Agentic AI and LLMs Marks a New Frontier in Information Warfare

Daniel Thilo Schroeder, Meeyoung Cha, Andrea Baronchelli, Nick Bostrom, Nicholas A. Christakis +17 more
5/18/2025
cs.CYcs.AIcs.CL

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Abstract

Public opinion manipulation has entered a new phase, amplifying its roots in rhetoric and propaganda. Advances in large language models (LLMs) and autonomous agents now let influence campaigns reach unprecedented scale and precision. Researchers warn AI could foster mass manipulation. Generative tools can expand propaganda output without sacrificing credibility and inexpensively create election falsehoods that are rated as more human-like than those written by humans. Techniques meant to refine AI reasoning, such as chain-of-thought prompting, can just as effectively be used to generate more convincing falsehoods. Enabled by these capabilities, another disruptive threat is emerging: swarms of collaborative, malicious AI agents. Fusing LLM reasoning with multi-agent architectures, these systems are capable of coordinating autonomously, infiltrating communities, and fabricating consensus cheaply. By adaptively mimicking human social dynamics, they threaten democracy.

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Cite this paper

@article{schroeder2025malicious,
  title  = {How Malicious AI Swarms Can Threaten Democracy: The Fusion of Agentic AI and LLMs Marks a New Frontier in Information Warfare},
  author = {Daniel Thilo Schroeder and Meeyoung Cha and Andrea Baronchelli and Nick Bostrom and Nicholas A. Christakis and David Garcia and Amit Goldenberg and Yara Kyrychenko and Kevin Leyton-Brown and Nina Lutz and Gary Marcus and Filippo Menczer and Gordon Pennycook and David G. Rand and Maria Ressa and Frank Schweitzer and Christopher Summerfield and Audrey Tang and Jay J. Van Bavel and Sander van der Linden and Dawn Song and Jonas R. Kunst},
  year   = {2025},
  eprint = {2506.06299},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2506.06299v3}
}

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