AI Insight
This paper proposes a mathematical framework modeling the spread of large language model (LLM) adoption through populations analogously to viral transmission. The authors identify that the interaction between social transmission, user recovery, and collective reinforcement can create tipping points leading to "technological lock-in," where populations rapidly shift toward persistent LLM dependence with corresponding declines in independent cognitive competence. The model also suggests conditions for "cognitive immunization" through reduced transmission rates and increased reversibility of adoption.
Why it matters
The research raises important questions about how widespread AI tool adoption might fundamentally alter human cognitive capabilities and autonomy at a population level. Understanding these dynamics could inform policy decisions about AI integration in education, professional settings, and society broadly, particularly regarding maintaining cognitive independence.
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⚠️ Preprint – Noch nicht peer-reviewed
Dieser Artikel wurde noch nicht von unabhängigen Experten begutachtet. Die Ergebnisse sind vorläufig und sollten mit Vorsicht interpretiert werden.
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.