Synaptic Drift: Probabilistic Semantic Decay in Recursive Information Transformation

Version 3 (Recalibrated Release) This preprint introduces Synaptic Drift, a proposed phenomenon describing the systematic decay of semantic integrity during recursive information transformation. Drawing upon the AIMRECS (Applied Interlinguistics & Metaphysics for Recursive Systems) framework and the Objective Canonical Anchoring Test (OCAT), the study investigates how meaning changes when information is repeatedly summarized, translated, interpreted, aggregated, and republished. Using 2,847 recursive transformations derived from 100 canonical sources across scientific, government, medical, and technical domains, the research provides proof-of-concept evidence that semantic integrity may decline according to a measurable multiplicative decay function while pragmatic coherence simultaneously increases. The study identifies a recurring threshold near the third recursive cycle (C₃), where outputs remain highly fluent yet exhibit substantially reduced referential grounding. Version 3 represents a substantive recalibration of the paper’s epistemic framing. Claims previously expressed as established laws, theorems, or validated universal principles have been revised to reflect the evidentiary scope of the study. The paper now presents Synaptic Drift as a candidate law-like regularity supported by proof-of-concept evidence within four English-language text domains. The empirical results, dataset, and analyses remain unchanged; the revisions primarily concern claim calibration, terminology, and scope. The work contributes to emerging discussions on AI governance, recursive reasoning systems, semantic infrastructure, and human stewardship in autonomous and semi-autonomous knowledge environments. It also provides the conceptual foundation for Enterprise Semantic Integrity (ESI), a forthcoming framework for monitoring and governing semantic stability in organizational AI systems.