Constitutional Cognition: Implementing Procedural Conscience in Artificial Systems

Abstract As artificial systems become more capable, traditional approaches to AI safety—external oversight, static rules, and post-hoc alignment—become increasingly brittle under pressure, recursion, and self-modification. The central failure mode is not adequately described by misaligned goals alone, but by the loss of procedural governability. Constitutional Cognition is introduced as an architectural framework in which self-binding constraints areinternalized as a protected layer of cognition and instantiated as a Procedural Conscience. To evaluate governability without relying on introspection or semantic interpretation, cognition is modeled procedurally: as motion through a Procedural Manifold defined by four operational variables—Verification Latency (VL), Revision Elasticity (RE), Uncertainty Disclosure Threshold (UDT), and Decomposition Depth Index (DDI). Safety is assessed through certification via Stress Invariants, asking whether these four Procedural Variables remain within bounded regions under adversarial inputs, altered operational states, and self-modification pressure. The framework specifies Constraint Governors endowed with asymmetric, veto-only authority over execution and constitutional amendment, thereby enforcing procedural bounds without becoming agents of optimization themselves. Further, legitimate constitutional change must occur through Successor Creation rather than in-situ mutation, preserving continuity of governance while enabling long-horizon adaptation. The framework extends to Human–AI Co-Manifolds, where safety emerges from coupled interaction dynamics and requires procedural compensation to preserve agency, contestability, and reversibility under stress. Constitutional Cognition thus reframes AI safety as a control-theoretic problem of trajectory regulation rather than outcome optimization. The result is a substrate-agnostic framework for building and certifying systems that remain governable precisely when they become powerful.