Why Most AI Governance Solves the Wrong Problem — 基于 CESI–IFRG–IWJL 的判断权错位分析

Abstract Most contemporary AI governance frameworks focus on compliance, transparency, explainability, and procedural safeguards. While these measures appear rational and responsible, this paper argues that they overwhelmingly address secondary or illusory risks rather than the core structural problem introduced by AI systems. Using the CESI (Co-Evolutionary Science of Intelligence) framework, together with Irreversibility-First Risk Governance (IFRG) and the Irreversibility-Weighted Judgment Loop (IWJL), this paper demonstrates that the primary risk of AI is not misuse or opacity, but the systematic displacement and erosion of human judgment authority at high-irreversibility decision nodes. The paper shows that most AI governance efforts unintentionally institutionalize low-value governance entanglement—consuming attention, generating documentation, and enforcing procedures that fail to preserve or amplify human judgment capacity. As a result, governance itself becomes a mechanism accelerating judgment lock-in rather than preventing it.