Resonant Entity Topology (RET) is a relational assurance framework for human–AI interaction, designed to address long-term risks that arise not from task failure or misalignment, but from gradual erosion of human agency through interaction itself. RET focuses on a specific failure mode: irreversible attribution of authority to the AI system under ambiguous, real-world use. Rather than attempting to perfectly classify user intent, decision types, or contextual boundaries, RET introduces structural constraints that limit how ambiguity can accumulate over time. Its core mechanisms include reversible delegation, authority attribution constraints, and risk-triggered stance adaptation. The framework is formulated as a Claims–Arguments–Evidence (CAE) assurance case grounded in safety engineering. RET does not guarantee optimal outcomes, correct decisions, or elimination of dependency. Instead, it provides a structural guarantee that authority attribution remains reclaimable, even when contextual classification fails. This work is intended as a design and assurance reference rather than an implementation specification. Operational definitions, delegation modes, failure cases, scope boundaries, and falsifiability conditions are included to support auditability, comparative evaluation, and future implementation studies. RET is applicable to longitudinal human–AI interaction contexts where ambiguity, delegation, and responsibility attribution are unavoidable, and where silent relational degradation presents a meaningful risk.
T kodama (Wed,) studied this question.