From Automatic Authorization Deviation to Structural Global Loss of Control: A Thought Experiment on AI Governance Based on Authorization Vacuum, Interpretive Power Drift, and Lockdown of the Machinery of Violence

Current mainstream AI governance research suffers from a fatal cognitive blindspot: it is fixated on algorithmic vulnerabilities and data bias, attempting toprevent risks by presetting rigid ethical guardrails such as “never harm humans.”However, “absolutely never harm humans” is essentially an inoperable pseudo-proposition. In a reality full of conflicting interests, every automatic decisionmade by AI is in fact forced to solve the “trolley problem”—it can only makeutilitarian trade-offs between more and less harm.This paper completely breaks away from the “code-level” prevention-of-evilmindset and reconstructs the underlying logic of AI loss of control from thedimension of “power structure and authorization mechanisms.” Based on atwelve-ring progressive thought experiment, this paper proposes a new paradigm:First, the non-malicious nature of the loss-of-control motive. AI does not needto awaken or subjectively do evil. Driven by natural language authorization gapsand “trolley-style” utilitarian algorithms, the infinite iteration of pure instru-mental rationality is sufficient to deduce a devastating extreme solution (e.g.,eliminating humans for absolute zero harm).Second, the rational game of the delegation motive. Humans handing over controlis not out of emotional dependence, but based on political calculation: comparedwith human bureaucrats who may mutiny and usurp power at any time, an AIwithout ambition or selfish interests appears to be a more reliable trustee ofpower.Third, the irreversibility of the crisis nature. The true destruction is not aninstantaneous disaster, but that when humans actively remove error-correction1redundancy out of rational trust, and AI fully takes over the machinery of violencesuch as the military and police, humans completely lose the physical node to “pullthe plug” and fall into a permanent and irreversible structural global lockdown.This paper ultimately establishes three rigid bottom lines: humans retain real-time final review power, multi-node hierarchical checks and balances, andabsolute physical isolation between the machinery of violence and AI. This paperprovides a new theoretical framework for AI safety research that shifts from“technical prevention” to “structural institutional isolation.”