Triadic Relational Ontology as a Practical Constraint for Machine Consciousness Testing - Isabelle, Christopher (Proceedings of the AAAI Symposium Series, 2026)
As AI systems scale, many proposed indicators of machineconsciousness track capability rather than consciousness,reducing discriminative power precisely when discriminationbecomes important. This paper proposes Triadic RelationalOntology (TRO) as a constraint on test design: if machineconsciousness exists, it must involve a sustained triadicorganization comprising (i) a temporally coherent self pole(S), (ii) a genuinely distinct world/other pole (W), and(iii) relational mediation (R) that maintains self–otherdifferentiation under perturbation. TRO predictsqualitative collapse modes (dyadic, solipsistic, anddecoupled) that do not monotonically scale withperformance. We outline an implementable intervention-basedprotocol for transformer language models and address twoconceptual risks that commonly sink such proposals: probecircularity (via counterfactual validation and cross-methodconvergence requirements) and S/W/R proxy bootstrapping(via staged identification with independent causalvalidation). Passing TRO-aligned tests is not treated asproof of consciousness; rather, TRO is proposed as a way togenerate meaningful negative evidence and constrain futurebenchmarks in a CIMC-aligned program of discriminativetesting.