IO Factory: Simulating AI-Enabled Influence Campaigns at Scale

Source

• Source name: arXiv
• Source kind: paper
• Authors / organization: Lukasz Olejnik, Wenchao Dong, Jonas R. Kunst, Signe Riemer-Sørensen, Tobias Herb, Meeyoung Cha, Daniel Thilo Schroeder
• Venue: arXiv: cs.AI
• Published: 2026-08-11
• Collected: 2026-08-12
• URL: http://arxiv.org/abs/2608.10920v1
• PDF: https://arxiv.org/pdf/2608.10920v1
• DOI: UNKNOWN
• Registry group: academic_apis_and_preprints
• Evidence role: canonical_academic_index
• Language: en
• Country / region: UNKNOWN

Plain-Language Brief

The authors introduce IO Factory, an AI-driven framework for simulating complex information and influence campaigns at scale. These campaigns involve AI swarms that adapt to platform feedback and disguise organized campaigns as ordinary social interaction. The system is designed to analyze the entire process of planning, execution, exposure, interpretation, measurement, and adaptation. It produces inspectable evidence of exposure and measured movement in belief variables. The framework supports reproducible research and red-team analysis of coordinated influence.

What the Document Says

• The authors introduce IO Factory, an AI-driven framework for simulating complex information and influence campaigns.
• These campaigns involve AI swarms that adapt to platform feedback and disguise organized campaigns as ordinary social interaction.
• IO Factory represents the process inside a controlled simulated platform, linking actor roles, platform actions, exposure records, structured model-based evaluations, and configured changes in the simulated population.
• The system produces inspectable evidence of exposure and measured movement in belief variables.
• IO Factory supports reproducible research and red-team analysis of coordinated influence.
• The framework was evaluated across configurations of up to 100,000 agents.

Key Concepts Mentioned

• IO Factory
• AI swarms
• information and influence campaigns
• simulated platform
• belief variables

Claims Made by the Document

• IO Factory can simulate complex information and influence campaigns at scale.
• These campaigns involve AI swarms that adapt to platform feedback.
• IO Factory supports reproducible research and red-team analysis of coordinated influence.

Evidence Used

• The text describes the introduction and purpose of IO Factory, its architecture, and its evaluation.

Methods / Approach

• Simulation of information and influence campaigns using an AI-driven framework.

Limitations Stated by the Authors

UNKNOWN

Limitations Noted by the Agent

Agent interpretation — not from the source.

While the text describes the results of evaluating IO Factory across configurations of up to 100,000 agents, it does not specify any limitations or errors identified by the authors.

Open Questions

• What specific AI models are used in IO Factory?
• How accurately does IO Factory simulate real-world influence campaigns?

Notes for Future Q&A

May include interpretation. Labeled where it does.

The text does not provide detailed information about the specific AI models used in IO Factory or the accuracy of its simulations.

Raw Abstract / Excerpt

We introduce IO Factory, an AI-driven framework for simulating information and influence campaigns as fully integrated, traceable processes. The threat of digital manipulation now extends beyond persuasive text from individual language models to AI swarms, i.e., persistent groups of coordinated agents that adapt to platform feedback and disguise organized campaigns as ordinary social interaction. Because such campaigns cannot be identified from isolated messages alone, they must be analyzed across a continuous spectrum of planning, platform action, exposure, interpretation, measurement, and adaptation. IO Factory represents this process inside a controlled simulated platform, linking actor roles, platform actions, exposure records, structured model-based evaluations, and configured changes in the simulated population. We implement the architecture and evaluate it across configurations of up to 100,000 agents. The results show that IO Factory executes campaign timelines at scale and produces inspectable evidence of exposure and measured movement in configured belief variables. By recording the actors, objectives, action constraints, exposure paths, and measurement rules used in each run, IO Factory supports reproducible research and red-team analysis of coordinated influence.