AI 条件下判断失真通用模型 - A General Model of Judgment Distortion under AI Conditions

Abstract As generative AI becomes deeply embedded in high-irreversibility judgment domains such as investment decision-making, regulatory enforcement, research evaluation, and intellectual property governance, judgment distortion is evolving from isolated failure cases into a cross-domain, reproducible structural phenomenon. Grounded in the Three Laws of CESI Judgment Physics, this paper proposes a General Judgment Distortion Model under AI Conditions (G-JDM) to explain why AI-augmented systems consistently exhibit judgment collapse, responsibility displacement, and decoupling from real-world constraints across institutional contexts. The paper argues that judgment distortion does not originate from AI errors, bias, or opacity, but from a fundamental mismatch: symbolic generation capacity scales exponentially while judgment-bearing and verification capacity remains constrained. Under irreversible conditions, this mismatch leads to unavoidable structural failure governed by the Judgment Irreversibility Theorem (JIT), the Judgment Cost Conservation Law (JCCL), and the Judgment Loop Displacement Law (JLDL). Rather than offering normative recommendations, this study establishes non-negotiable boundary conditions for AI governance in judgment-critical systems. The proposed model is directly transferable across domains and provides a physics-level explanation for systemic judgment failure in the intelligent era. It should be noted that the General Judgment Distortion Model (G-JDM) is methodologically and ontologically distinct from content-based cognitive distortion models in psychology (e.g., JMCD), as it operates at the level of judgment physics rather than individual belief structures. 随着生成式 AI 被系统性嵌入投融资、监管、科研评估与知识产权等高不可逆判断场景, 判断失真正从个别失败现象演化为跨领域、可复制的结构性问题。本文在 CESI 判断物理学三定律的统一约束下, 提出一个 “AI 条件下判断失真通用模型” (General Judgment Distortion Model, G-JDM), 用于解释为何在不同制度环境中, AI 会一致性地诱发判断坍缩、责任位移与现实脱锚。 本文论证: 判断失真并非源于 AI 的错误、偏见或不透明性, 而是当 符号生成能力被指数级放大, 而判断承担能力与验证回路未同步扩展 时, 判断系统在不可逆条件下面临的必然物理结果。该失真过程严格服从判断不可逆性定理(JIT)、判断代价守恒定律(JCCL)与判断回路位移定律(JLDL), 并呈现出跨领域同构的失败模式。 本文进一步表明, 当前以“合规” “伦理”或“最佳实践”为导向的 AI 治理框架, 无法触及判断失真的根源。判断物理学视角揭示: 判断失真是系统性、非道德化、不可通过意志修复的结构结果。该模型可直接迁移至投融资决策、监管执法、科研评价等高风险判断系统, 为智能时代的判断治理确立不可被违背的边界条件。 本文所述“判断失真”并非指个体认知偏差, 而是指在不可逆条件下由结构约束引发的系统性判断坍缩, 与心理学意义上的认知扭曲模型不构成理论竞争关系。