Cognitive Compatibility - Why Drift Must Be Measured, Not Eliminated

This paper introduces cognitive compatibility as a measurable property of AI systems operating under constraint. It argues that prevailing evaluation approaches—focused on accuracy, speed, and output quality—misidentify where system failure originates. Rather than emerging at the level of outputs, failure begins upstream in how systems structure the space of permissible variation. A dominant response has been to reduce or eliminate drift (variation) in pursuit of stability and alignment. This paper challenges that premise. It shows that eliminating drift collapses a system’s capacity to adapt, respond proportionally to perturbation, and expose its own misalignment. In such conditions, systems either become deterministic transformation engines or exhibit opaque stability where misalignment persists without visibility. Drawing on constraint-based experimentation within the Architecture of Limitation (AoL), the paper reframes drift as a necessary diagnostic signal. Drift enables a feedback loop in which misalignment produces error, error surfaces collapse, and collapse enables recalibration. Without this loop, alignment cannot be internally sustained. The paper proposes that the goal is not the elimination of drift, but its regulation. A cognitively compatible system permits bounded variation, makes that variation observable, and supports recovery toward proportioned alignment. To operationalize this, a formal measurement framework—the Cognitive Compatibility Index (CCI)—is introduced. The framework evaluates systems across five indices: bounded drift, observability, recovery capacity, perturbation responsiveness, and alignment stability. Derived indicators assess risks such as silent misalignment and over-determinism. The framework is explicitly diagnostic, non-normative, and carries no governance authority. The central claim is structural: systems that eliminate drift cannot function as cognitive extensions to human reasoning. Systems that preserve bounded, observable, and recoverable drift remain compatible with cognition as a co-participating process. This publication is part of the broader Architecture of Limitation / AoLOS program.Certain architectural elements referenced herein are the subject of prior intellectualproperty filings. This document is provided for academic and research purposes anddoes not constitute a full disclosure of implementation-level mechanisms.