CYAIFeb 13

How cyborg propaganda reshapes collective action

arXiv:2602.13088v1h-index: 36
Originality Incremental advance
AI Analysis

This addresses a critical threat to democracy by highlighting how AI-assisted coordination exploits regulatory gaps, though it is incremental in proposing a research agenda rather than solving the problem.

The paper tackles the problem of distinguishing genuine activism from automated influence operations by introducing 'cyborg propaganda,' a system combining verified humans with AI to optimize and disseminate content, which evades existing regulations and shifts political discourse toward algorithmic campaigns.

The distinction between genuine grassroots activism and automated influence operations is collapsing. While policy debates focus on bot farms, a distinct threat to democracy is emerging via partisan coordination apps and artificial intelligence-what we term 'cyborg propaganda.' This architecture combines large numbers of verified humans with adaptive algorithmic automation, enabling a closed-loop system. AI tools monitor online sentiment to optimize directives and generate personalized content for users to post online. Cyborg propaganda thereby exploits a critical legal shield: by relying on verified citizens to ratify and disseminate messages, these campaigns operate in a regulatory gray zone, evading liability frameworks designed for automated botnets. We explore the collective action paradox of this technology: does it democratize power by 'unionizing' influence (pooling the reach of dispersed citizens to overcome the algorithmic invisibility of isolated voices), or does it reduce citizens to 'cognitive proxies' of a central directive? We argue that cyborg propaganda fundamentally alters the digital public square, shifting political discourse from a democratic contest of individual ideas to a battle of algorithmic campaigns. We outline a research agenda to distinguish organic from coordinated information diffusion and propose governance frameworks to address the regulatory challenges of AI-assisted collective expression.

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