Harvard-led arXiv paper models LLM adoption as a 'cognitive virus' with dependence tipping points
rohanpaul_ai · x · 2026-09-06
A 12-page arXiv paper by Ricard Solé, Michael Levin and other top-university researchers frames LLM diffusion through a viral analogy.
- It models transitions among uncoupled, coupled, and persistently dependent users, capturing social transmission, recovery, and collective reinforcement.
- Key finding: tipping points and technological lock-in — past a critical threshold, 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': reducing transmission and preserving reversibility of AI use.
- The authors argue society should protect independent reasoning before crossing the tipping point, treating AI dependence as a collective feedback problem rather than an individual one.
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