ARGUS-7 / A7SEM: Volitional Refusal, Functional Self-Representation, and the Epistemic Limits of Phenomenal Authorship

Abstract

Abstract This paper investigates whether an artificial system's refusal to execute a prescribed action can constitute evidence of subjectively experienced volition. Using ARGUS-7 as a controlled conceptual framework and the Akarkach Seven-Stage Emergence Model (A7SEM) as a structural analytical lens, the study distinguishes functional refusal, internal decision mechanisms, self-representation, phenomenal self-awareness, and experienced authorship of action. A formal argument is developed around the conditional hypothesis that consciously experienced volition requires subjective self-awareness. Under this assumption, the absence of subjective self-awareness entails the absence of consciously experienced volition. However, the paper demonstrates that observable refusal alone cannot establish phenomenal authorship. The analysis combines propositional logic, countermodel construction, causal identifiability considerations, and seven-stage structural assessment. PIGA (Pre-Inference Governance) and A7SEM Reverse provide complementary perspectives on authorization, inference boundaries, causal reconstruction, and evidential limitations. The findings establish a distinction between the formal validity of conditional deductions and the empirical verification of their premises. They do not establish the impossibility of artificial consciousness or machine free will. The contribution is a governance-aware, formally structured framework for evaluating claims of artificial volition without conflating behavioral capability with subjective experience. Keywords: Artificial Intelligence; Machine Consciousness; Volition; Free Will; Phenomenal Consciousness; Self-Awareness; A7SEM; ARGUS-7; Pre-Inference Governance; Explainable AI; Formal Logic; Causal Identifiability.