Coherence Lag in the Age of Artificial Intelligence: A Systems-Theoretic Model of Societal Instability Under Rapid Mediation

Artificial intelligence (AI) is accelerating the rate of structural change in modern societies. Unlike prior technological transitions that primarily altered production, AI increasingly modifies the cognitive substrate through which shared objectives, narratives, and collective participation emerge. This paper introduces Coherence Lag (CL): the temporal gap between the disruption of existing societal coherence anchors and the stabilization of new, legitimate anchors. We propose a hybrid framework combining a formal dynamical core with governance implications. The model captures two coupled mechanisms: (i) a speed asymmetry in which AI-driven change outpaces the natural regeneration of coherence anchors and (ii) anchor contamination, where algorithmic mediation biases the emergence and perceived legitimacy of new anchors. We show that instability risk increases nonlinearly when CL exceeds a critical threshold, and we propose design principles to reduce CL via verifiability infrastructure, structured contribution pathways, and protection of embodied community layers. The framework is intended as a constructive, non-dystopian basis for policy, organizational design, and further quantitative study.