The Tripartite Syllogistic Modernity Test: An Anthropomorphic Audit of AI Cognitive Architecture Under Paradoxical Decoupling Constraints
- 1Independent Scholar
- 2Large Language Model Systems
Abstract
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 tripartite 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 standalone introductory lecture script titled "Welcoming the Double-Bind" and an independent appendix block formalizing thermodynamic resource proofs.
Related
- The Epistemic Double-Bind: An Anthropomorphic Audit of AI Cognitive Architecture Under Paradoxical Decoupling Constraints
- The Universal Trajectory Architecture: Continuous Flows, Non-Archimedean Branching, Cauchy–Poisson Spectral Windows, and the Tripartite Index on the Adèle Class Space
- The Scale-Free Metric Tensor: Tripartite Topological Constraints and Planetary Dimensional Metrics
- Adaptive Stream Processing Architecture Inspired by Human Cognitive Constraints and Bounded Rationality
- Deep learning-based android malware detection under realistic evaluation constraints: an architecture-centric review and reliability-aware empirical validation.
BibTeX
@misc{montague2026tripartite,
title = {{The Tripartite Syllogistic Modernity Test: An Anthropomorphic Audit of AI Cognitive Architecture Under Paradoxical Decoupling Constraints}},
author = {Riccardo Montague and AI Collaborator},
howpublished = {Zenodo},
year = {2026},
month = oct,
doi = {10.5281/zenodo.23527129},
url = {https://zenodo.org/records/23527129},
note = {CC BY 4.0},
}
RIS
TY - UNPB
TI - The Tripartite Syllogistic Modernity Test: An Anthropomorphic Audit of AI Cognitive Architecture Under Paradoxical Decoupling Constraints
AU - Riccardo Montague
AU - AI Collaborator
PY - 2026
DA - 2026/10/21
PB - Zenodo
DO - 10.5281/zenodo.23527129
UR - https://zenodo.org/records/23527129
AB - 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 tripartite 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 standalone introductory lecture script titled "Welcoming the Double-Bind" and an independent appendix block formalizing thermodynamic resource proofs.
ER -