AI让判断能力近乎免费，反倒是可信信号和真实来源变稀缺。
Institutions for the Post-Scarcity of Judgment
- AI可大规模生成看似可靠的判断，成本趋近于零
- 真实信号、合法身份、可信来源与认知整合力成新稀缺资源
- 适合关注政策设计、制度重构与AI治理的读者
每次重大技术革命都会逆转某种稀缺性，并重塑相应制度。当前对AI革命的普遍看法认为：AI大幅降低了预测成本，而判断仍属稀缺。本文提出观点反转——具备胜任力的判断（如选择、排序、归因、认证）已可规模化生产，边际成本接近于零；但四项关键要素变得稀缺：经验证据、合法性、真实来源与社会对委托认知的容忍度。由于判断是制度的核心内容，过去用于制造合法判断的机构（法院、期刊、执照机构、立法机关）如今与技术在功能上直接竞争。文章横跨科学制度、职业认证、知识产权、民主正当性及基础模型集中化等领域，提出三步策略：将AI政策转向制度重构；将来源验证建设为公共品；建立应对战略主体的制度组合形式化框架。
原文摘要 · Abstract (English)
Each major technological revolution inverts a particular scarcity and rebuilds institutions around the shift. The near-consensus diagnosis of the AI revolution holds that AI collapses the cost of prediction while judgment remains scarce. This Opinion argues the inversion has now flipped: competent-looking judgment (selecting, ranking, attributing, certifying) is produced at scale and at marginal cost approaching zero, and four complements become scarce: verified signal, legitimacy, authentic provenance, and integration capacity (the community's tolerance for delegated cognition). Because judgment is the substance of institutions, the institutions built to manufacture legitimate judgment (courts, journals, licensing bodies, legislatures) now compete with the technology for the same functional role. The piece traces the pattern across scientific institutions, professional licensing, intellectual property, democratic legitimacy, and foundation-model concentration, and closes with a three-move agenda: reframe AI policy as institutional redesign, build provenance and verification as commons, and develop the formal apparatus for institutional composition under strategic agents.
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