Abstract for: Algorithmic Friction and Yin-Yang Cybernetics: Reconstructing the Foundational Logic of System Dynamics in the Age of AI

This research addresses the systemic instability of contemporary AI architectures. We posit that the "black-box" crisis stems from a genetic flaw in Leibnizian Determinism, which historically excised the ecological balancing mechanisms of the I Ching. Current AI functions as a runaway Reinforcing Loop (R-loop), creating a "Predictive Iron Cage" that lacks the necessary systemic resistance. We introduce "Yin-Yang Cybernetics" to rectify this historical modeling error. By mapping the I Ching onto modern System Dynamics, we re-characterize "Yang" as computational acceleration and "Yin" as substantial resistance (Balancing Loops/Delays). The proposed "Algorithmic Friction" framework deliberately engineers ethical "speed bumps" into high-velocity AI information flows to restore systemic resilience and human moral agency. Preliminary theoretical modeling indicates that introducing deliberate "fault lines" and "reflective delays" sacrifices marginal short-term efficiency for exponential gains in long-term ecological stability. Initial mapping suggests that Eastern ontology provides the missing "B-loop" required to govern runaway deterministic systems. The framework has been theoretically validated through comparative analysis with established complexity theories. Traditional Western ethical frameworks fail to penetrate foundational code structures. "Yin-Yang Cybernetics" demonstrates that sustainable AI futures must be co-crafted through the "friction" between human intuition and algorithmic logic. This shift from frictionless computation to governed uncertainty is essential for preserving human dignity. The research invites the SD community to lead the ontological reconstruction of AI governance.