AI无法真正理解价值与决策,本质是被动工具。
Epistemic Scarcity: The Economics of Unresolvable Unknowns
- 从主观价值出发,认为AI无法主动理解目标与意义
- 指出算法无法创造规范,也无法承担道德责任
- 适合关注人工智能伦理与自由社会的读者
本文基于米塞斯先验推理和奥地利学派企业家理论,对人工智能与算法治理进行实践哲学分析,挑战机器系统维持经济与认知秩序的能力。传统新古典与行为模型将决策视为约束下的优化,而本文将其视为不确定条件下的目的性行动。批判主流公平、问责与透明(FAT)框架为建构理性主义延伸,违背以自愿行动与产权为基础的自由秩序。算法无法生成规范、解读制度或承担责任,始终处于模糊、错位与惰性状态。通过‘认知稀缺’概念,探讨信息过载如何削弱真知辨别力,既催生创业洞察,也助长软威权。最终主张:人工智能争论关乎人类自主、制度演进与理性选择的未来。奥地利学派强调行动、主观性与自发秩序,是应对计算社会控制的唯一连贯替代路径。
原文摘要 · Abstract (English)
This paper presents a praxeological analysis of artificial intelligence and algorithmic governance, challenging assumptions about the capacity of machine systems to sustain economic and epistemic order. Drawing on Misesian a priori reasoning and Austrian theories of entrepreneurship, we argue that AI systems are incapable of performing the core functions of economic coordination: interpreting ends, discovering means, and communicating subjective value through prices. Where neoclassical and behavioural models treat decisions as optimisation under constraint, we frame them as purposive actions under uncertainty. We critique dominant ethical AI frameworks such as Fairness, Accountability, and Transparency (FAT) as extensions of constructivist rationalism, which conflict with a liberal order grounded in voluntary action and property rights. Attempts to encode moral reasoning in algorithms reflect a misunderstanding of ethics and economics. However complex, AI systems cannot originate norms, interpret institutions, or bear responsibility. They remain opaque, misaligned, and inert. Using the concept of epistemic scarcity, we explore how information abundance degrades truth discernment, enabling both entrepreneurial insight and soft totalitarianism. Our analysis ends with a civilisational claim: the debate over AI concerns the future of human autonomy, institutional evolution, and reasoned choice. The Austrian tradition, focused on action, subjectivity, and spontaneous order, offers the only coherent alternative to rising computational social control.
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