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

Relational Entity Topology (RET) is a preprint proposing interaction-level relational conditions under which harmful authority fixation does not accumulate irreversibly in extended human–AI interaction. Rather than focusing on task correctness, alignment, or internal user-state inference, RET examines how authority attribution, delegation reversibility, and stance adaptation unfold over time. The central safety question is whether human users retain the practical ability to later reinterpret, revise, override, or reject prior AI-supported decisions without appealing to system authority. This v3 revision formally updates the terminology from Resonant Entity Topology to Relational Entity Topology, clarifying that the contribution concerns inspectable relational continuity across sessions rather than phenomenological resonance. The paper introduces a continuity-preserving interaction topology centered on reclaimable human agency, longitudinal authority drift, cross-session trend evaluation, and ambiguity containment under uncertainty. Appendices include a Claims–Arguments–Evidence (CAE) expression, delegation modes, authority drift indicators, cross-session evaluation logic, and falsifiability conditions for comparative assessment against baseline interaction systems.