Forecasting Failure: Why Structurally Sound AI Governance Collapses Before It Is Abused
“The system shatters under its own weight before it is ever abused.”悪用される前に、自らの重みで砕け散る。
“It is a physical suicide, executed by goodwill.” それは、善意によって完遂される、自死。
Structure.
Framing → Pre-abuse Failure → Four Failure Trajectories → ALTRION as Analytical Probe → Design Targets.
Current discourse on AI governance predominantly focuses on adversarial robustness, regulatory non-compliance, and malicious misuse. This paper argues that such framing overlooks a more pervasive and insidious risk: pre-abuse failure, defined as the structural collapse of governance mechanisms that occurs not through malice or external attack, but through the thermodynamic inevitability (as an analytical analogy) of organizational entropy and cognitive economy.
Using a procedurally explicit workflow architecture (ALTRION) as an analytical probe, we identify four self-reinforcing trajectories of failure: Cognitive Externalization, Responsibility Inversion, Organizational Entropy, and Legibility Capture. We conclude that long-term AI safety requires not just stronger enforcement against bad actors, but a fundamental redesign of how human oversight interacts with the physics of institutional bureaucracy.
Keywords
AI Governance; Sociotechnical Systems; Organizational Failure; pre-abuse failure; ALTRION