Large-Language Models as a Cognitive Virus

2026-09-03

AI Summary

研究通过病毒传播模型探讨大型语言模型在人群中的扩散及其对认知的影响，提出减少传播和增强可逆性以实现认知免疫的方法。

Abstract

Large-language models (LLMs) are rapidly becoming part of human culture, reshaping how information is produced, transmitted, and used. Here we propose that their diffusion can be understood through a viral analogy, with LLM use spreading through populations, becoming embedded in cognitive and cultural practices. We model transitions among uncoupled, coupled, and persistently dependent users, and show that the interplay between social transmission, recovery, and collective reinforcement can generate tipping points and technological lock-in. A central consequence is the possibility of runaway dynamics: once a critical threshold is crossed, small increases in adoption can trigger rapid population-level shifts toward persistent dependence, with abrupt losses in cognitive competence. The same framework, however, identifies conditions for cognitive immunization, based on reducing transmission and facilitating reversibility. Our results highlight how LLM adoption may involve nonlinear collective transitions with important consequences for cognitive autonomy.

Problem

• Large-language models
• cognitive virus
• technological lock-in
• cognitive autonomy
• social transmission

Innovation

• viral analogy
• cognitive autonomy
• technological lock-in
• social transmission