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author Schroeder, Daniel Thilo
Cha, Meeyoung
Baronchelli, Andrea
Bostrom, Nick
Christakis, Nicholas A.
Garcia, David
Goldenberg, Amit
Kyrychenko, Yara
Leyton-Brown, Kevin
Lutz, Nina
Marcus, Gary
Menczer, Filippo
Pennycook, Gordon
Rand, David G.
Ressa, Maria
Schweitzer, Frank
Song, Dawn
Summerfield, Christopher
Tang, Audrey
Van Bavel, Jay J.
van der Linden, Sander
Kunst, Jonas R.
author_facet Schroeder, Daniel Thilo
Cha, Meeyoung
Baronchelli, Andrea
Bostrom, Nick
Christakis, Nicholas A.
Garcia, David
Goldenberg, Amit
Kyrychenko, Yara
Leyton-Brown, Kevin
Lutz, Nina
Marcus, Gary
Menczer, Filippo
Pennycook, Gordon
Rand, David G.
Ressa, Maria
Schweitzer, Frank
Song, Dawn
Summerfield, Christopher
Tang, Audrey
Van Bavel, Jay J.
van der Linden, Sander
Kunst, Jonas R.
contents Advances in AI offer the prospect of manipulating beliefs and behaviors on a population-wide level. Large language models and autonomous agents now let influence campaigns reach unprecedented scale and precision. Generative tools can expand propaganda output without sacrificing credibility and inexpensively create 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, a 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 efficiently. By adaptively mimicking human social dynamics, they threaten democracy. Because the resulting harms stem from design, commercial incentives, and governance, we prioritize interventions at multiple leverage points, focusing on pragmatic mechanisms over voluntary compliance.
format Preprint
id arxiv_https___arxiv_org_abs_2506_06299
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle How malicious AI swarms can threaten democracy: The fusion of agentic AI and LLMs marks a new frontier in information warfare
Schroeder, Daniel Thilo
Cha, Meeyoung
Baronchelli, Andrea
Bostrom, Nick
Christakis, Nicholas A.
Garcia, David
Goldenberg, Amit
Kyrychenko, Yara
Leyton-Brown, Kevin
Lutz, Nina
Marcus, Gary
Menczer, Filippo
Pennycook, Gordon
Rand, David G.
Ressa, Maria
Schweitzer, Frank
Song, Dawn
Summerfield, Christopher
Tang, Audrey
Van Bavel, Jay J.
van der Linden, Sander
Kunst, Jonas R.
Computers and Society
Artificial Intelligence
Computation and Language
Machine Learning
Advances in AI offer the prospect of manipulating beliefs and behaviors on a population-wide level. Large language models and autonomous agents now let influence campaigns reach unprecedented scale and precision. Generative tools can expand propaganda output without sacrificing credibility and inexpensively create 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, a 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 efficiently. By adaptively mimicking human social dynamics, they threaten democracy. Because the resulting harms stem from design, commercial incentives, and governance, we prioritize interventions at multiple leverage points, focusing on pragmatic mechanisms over voluntary compliance.
title How malicious AI swarms can threaten democracy: The fusion of agentic AI and LLMs marks a new frontier in information warfare
topic Computers and Society
Artificial Intelligence
Computation and Language
Machine Learning
url https://arxiv.org/abs/2506.06299