A new study proposes that the diffusion of large-language models (LLMs) can be understood through a viral analogy, with LLM use spreading through populations and becoming embedded in cognitive and cultural practices. Researchers model transitions among uncoupled, coupled, and persistently dependent users, showing that 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 identifies conditions for cognitive immunization, based on reducing transmission and facilitating reversibility.

The results highlight how LLM adoption may involve nonlinear collective transitions with important consequences for cognitive autonomy. The paper was submitted by Luis F Seoane Ph D on September 3, 2026.