发表机构
Universitat Pompeu Fabra; Institució Catalana de la Recerca i Estudis Avancats (ICREA); CSIC-UPF; Santa Fe Institute; Barcelona Computational Foundation (BCOM); Neuroelectrics; Okinawa Institute of Science and Technology Graduate University; University of Padua; Istituto Nazionale di Fisica Nucleare, Sez. Padova（庞培法布拉大学; 加泰罗尼亚研究与高级研究所; 西班牙国家研究委员会-庞培法布拉大学联合研究所; 圣塔菲研究所; 巴塞罗那计算基金会; 神经电子公司; 冲绳科学技术大学院大学; 帕多瓦大学; 意大利国家核物理研究所帕多瓦分部）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文将大语言模型（LLM）类比为认知病毒，通过建模用户状态转变揭示其扩散会产生临界点与失控动态，同时提出认知免疫条件，凸显LLM采用对认知自主性的非线性影响。
AI 中文摘要
大语言模型（LLM）正迅速成为人类文化的一部分，重塑着信息的生产、传播与使用方式。本文提出可通过病毒类比理解其扩散过程：LLM的使用在人群中传播，嵌入认知与文化实践。我们对非耦合用户、耦合用户及持续依赖用户之间的转变进行建模，结果显示社会传播、恢复与集体强化的相互作用可产生临界点与技术锁定。核心结论是存在失控动态：一旦突破临界阈值，采用率的小幅提升即可触发人群向持续依赖的快速转变，导致认知能力骤然下降。不过，该框架也识别出认知免疫的条件，即通过减少传播并促进可逆性来实现。我们的研究结果强调，LLM的采用可能涉及非线性集体转变，对认知自主性具有重要影响。
英文摘要
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.
Comments12 pages, 3 figures
