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An international research team involving Konstanz scientist David Garcia warns that the next generation of influence operations may not look like obvious "copy-paste bots," but like coordinated communities: fleets of AI-driven personas that can adapt in real time, infiltrate groups, and manufacture the appearance of public agreement at scale.

A chorus of seemingly independent voices creates the illusion of consensus while spreading disinformation. In the journal Science, the authors describe how the fusion of large language models (LLMs) with multi-agent systems could enable "malicious AI swarms" that imitate authentic social dynamics—and threaten democratic discourse by counterfeiting social proof and consensus.

‘Synthetic consensus’

The article argues that the central risk is not only false content, but "synthetic consensus": the illusion that "everyone is saying this," which can influence beliefs and norms even when individual claims are contested. This persistent influence can drive deeper cultural changes beyond norm shifts, subtly altering a community’s language, symbols, and identity.

"The danger is no longer just fake news, but that the very foundation of democratic discourse —independent voices—collapses when a single actor can control thousands of unique, AI-generated profiles," says Jonas R. Kunst from BI Norwegian Business School.

In addition, by flooding the web with fabricated chatter, malicious AI swarms can contaminate training data of regular artificial intelligence, extending their influence to established AI platforms. This threat is not theoretical, the authors warn: analysis suggests such tactics are already in use.

What is an AI swarm?

The authors define a malicious AI swarm as a set of AI-controlled agents that can maintain persistent identities and memory; coordinate toward shared objectives while varying tone and content; adapt in real time to engagement and human responses; operate with minimal oversight; and deploy across platforms. Compared with earlier botnets, such swarms could be harder to detect because they can generate heterogeneous, context-aware content while still moving in coordinated patterns.

How to counter AI swarms

"Beyond the bias or safety of individual chatbots or models, we have to study new risks that emerge from the interaction between many AI agents. For this, it is essential to apply behavioral sciences to AI agents and to study their collective behavior when they interact in large groups," says Garcia, professor for Social and Behavioral Data Science at the University of Konstanz.

Instead of moderating posts one by one, the authors argue for defenses that track coordinated behavior and content provenance: detect statistically unlikely coordination, offer privacy-preserving verification options, and share evidence through a distributed AI Influence Observatory, while also reducing incentives by limiting monetization of inauthentic engagement and increasing accountability.

More information: Daniel Thilo Schroeder et al, How malicious AI swarms can threaten democracy, Science (2026). DOI: 10.1126/science.adz1697

Citation: The next generation of disinformation: AI swarms can threaten democracy by manufacturing fake public consensus (2026, January 23) retrieved 23 January 2026 from https://techxplore.com/news/2026-01-generation-disinformation-ai-swarms-threaten.html

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