Governance opacity over AI systems shifts in kind as capability asymmetry grows, and the strongest forms defeat the disclosure-based remedies governance ordinarily relies on. This paper applies a six-dimension framework from political theory (legitimacy, accountability, corrigibility, non-domination, subsidiarity, institutional resilience) to six AI governance arrangements already in operation, ordered by increasing capability asymmetry between system and overseer. Proprietary secrecy yields to disclosure at the low end, but at the high end the governed system either games its own evaluation or sits inside the governance process, and transparency remedies lose traction. Legitimacy and non-domination strain more consistently across the sample than corrigibility and resilience, which respond more readily to institutional design quality. The sample cannot separate institutional design maturity from capability asymmetry, and the patterns are offered as hypotheses for multi-rater validation.

翻译：随着能力不对称性的增长，人工智能系统的治理不透明性在性质上发生变化，最强形式击败了治理通常依赖的基于披露的补救措施。本文运用政治理论中的六维框架（合法性、问责性、可修正性、非支配性、辅助性原则、制度韧性），对六种已运行的人工智能治理安排进行分析，这些安排按系统与监管者之间能力不对称性的递增顺序排列。在低端，专有保密让位于披露，但在高端，被治理系统要么操纵自身的评估，要么嵌入治理过程内部，透明度补救措施失去效力。在整个样本中，合法性和非支配性维度的张力比可修正性和韧性维度更为一致，后者对制度设计质量响应更灵敏。该样本无法将制度设计成熟度与能力不对称性分开，这些模式作为假设供多人评审验证。