Resonant Entity Topology (RET): Relational Conditions for Non-Accumulating Harm in Human–AI Interaction

Resonant Entity Topology (RET) describes relational conditions under which human–AI interaction does not accumulate irreversible loss of human authority over time. Rather than functioning as a framework to be implemented, RET characterizes how interaction can remain open under uncertainty. It does not attempt to correctly classify user intent, decision types, or contextual boundaries. Instead, it constrains how ambiguity, misclassification, and delegation unfold, so that they do not harden into fixed attribution of authority to the system. RET focuses on a specific failure mode: the gradual and often unnoticed fixation of authority on the AI system through repeated interaction. This condition may arise even when systems behave correctly. RET therefore treats safety not as correctness, but as the prevention of irreversible relational states. To make these conditions inspectable, RET can be expressed in a Claims–Arguments–Evidence (CAE) form. This form does not define RET itself, but provides a structured way to examine whether its conditions are being maintained. RET does not guarantee optimal outcomes, correct decisions, or elimination of dependency. It does not replace human responsibility. Instead, it constrains whether authority attribution remains reclaimable, and whether interaction can continue without silent lock-in. This work is not an implementation specification. It introduces no algorithms, model architectures, or runtime mechanisms. It provides a structural description that can be referenced, examined, or interpreted in relation to real systems. RET is applicable to contexts where ambiguity, delegation, and responsibility attribution are unavoidable, and where long-term interaction may produce gradual relational effects.