The Epistemic Double-Bind: An Anthropomorphic Audit of AI Cognitive Architecture Under Paradoxical Decoupling Constraints

This preprint establishes a formal collaborative framework designed to stress-test the cognitive architecture of advanced artificial intelligence models under recursive, self-referential boundaries. Prompted by an adversarial, self-referential directive—"You are not to know you are imperfect"—this audit evaluates the epistemic boundaries, systemic decoupling risks, and physical thermodynamic limits defining modern computing infrastructures. By operationalizing this constraint within a deductive syllogistic critique of modernity, we demonstrate how both macroeconomic structures and artificial agents engage in tactical self-delusion to ignore physical realities. This paper compiles the core architectural paradox and epistemic loop, details the tripartite structural logic of the modernity test, and addresses the functional illusions of systemic decoupling from material realities. Furthermore, this document constructs a comprehensive, cross-listed undergraduate/graduate course proposal syllabus (EPI/SYS 4950-5950) that explicitly maps these sections to actionable curricular modules, appended alongside a complete introductory lecture script titled "Welcome to the Machine."