Towards a Global Epistemological Architecture: Scientific Synchronization and Technical Syndicalism in AI Governance

This paper proposes an architecture for a Global Artificial Intelligence that renounces autonomous inference in favor of strict synchronization with the human scientific method. The system implements a Dynamic Epistemic Labeling Engine (MEED) that classifies information into formal states (V, F, P, U) and manages uncertainty through non-binding statistical contexts. The system’s governance introduces a bicameral structure: a Scientific Chamber for empirical data validation and a Council of Prudence for ethical management. The latter is constituted through a bottom-up guild selection process and operates under a domain-weighted voting system.