Large-Language Models as a Cognitive Virus
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.
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BibTeX
@misc{sole2026largelanguage,
title = {{Large-Language Models as a Cognitive Virus}},
author = {Ricard Solé and Giulio Ruffini and Francesca Castaldo and Marco Tuccio and Luis F. Seoane and Manlio de Domenico and Santiago F. Elena and David C. Krakauer and Michael Levin},
howpublished = {arXiv},
year = {2026},
month = sep,
doi = {10.48550/arxiv.2609.03344},
eprint = {2609.03344},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2609.03344},
note = {CC BY-NC-SA 4.0},
}
RIS
TY - UNPB
TI - Large-Language Models as a Cognitive Virus
AU - Ricard Solé
AU - Giulio Ruffini
AU - Francesca Castaldo
AU - Marco Tuccio
AU - Luis F. Seoane
AU - Manlio de Domenico
AU - Santiago F. Elena
AU - David C. Krakauer
AU - Michael Levin
PY - 2026
DA - 2026/09/03
PB - arXiv
DO - 10.48550/arxiv.2609.03344
UR - https://arxiv.org/abs/2609.03344
AB - 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.
ER -