AI Contagion in Social Networks: Recursive Feedback Loops Threaten Collective Knowledge
A new preprint models how AI systems interacting with social networks can create recursive feedback loops that destabilize collective knowledge. The study derives a regulatory frontier for the minimum filtering needed to maintain informational stability and analyzes how network structures such as homophily and core-periphery arrangements influence systemic risk. The work provides a mathematical framework for understanding the stability of AI-mediated information systems.
Why it matters: This research offers a quantitative basis for regulating AI-generated content in social networks to help prevent the destabilization of collective knowledge.
Full story at: arXiv Computers and Society ↗