Informational Autoimmunity: The Fallout from Ungoverned AI Deployment — A Framework for Human Capital Atrophy Independent of AI Capability

Résumé fourni par la source

This paper introduces Informational Autoimmunity (IA), a proposed framework describing a systemic market and cognitive failure mode arising in organizations and individuals alike under ungoverned deployment of large language models (LLMs): an escalating verification burden borne by the recipients of machine-generated output. Contemporary institutional practice assumes that zero-marginal-cost content production yields linear productivity gains. We argue instead that a Jevons-type dynamic in attention (in which collapsing production costs drive total verification demand upward) decouples output velocity from organizational consumption capacity, and that organizations systematically misread the resulting friction as employee redundancy, dismantling the human judgment infrastructure they most need. We formalize the framework as a heuristic identity, decompose the displacement of human cognitive capital into five hypothesized pathologies, state falsifiable calibration hypotheses about decision-velocity decay, and outline a measurement protocol now being instrumented in live organizational engagements. We close by proposing a governance architecture of selective friction intended to re-couple production and verification. All quantitative magnitudes in this paper are stated as hypotheses awaiting measurement, not as findings. UPTICK Research Working Paper No. 2026-01.

Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.