用形式化语言构建可审计的AI治理规则，让系统行为透明可验证。
Implementing Computational Law in Wolfram Language for the Governance of Artificial Intelligence
- 用沃尔弗拉姆语言实现可计算的法律逻辑框架
- GPT-4翻译法律条文时出现误译与隐性错误
- 适合关注AI合规与可解释性的研究者
我们如何治理那些推理过程无法完全解析的AI系统？治理不依赖于理解系统推理，而是明确其必须、允许和禁止的行为，并验证是否遵守。本文在沃尔弗拉姆语言中实现了重言式输入/输出逻辑（Reified I/O Logic），该逻辑是DAPRECO知识库的基础：包含核心I/O公理、义务、许可、构成性规范、重言事件及时间算子。随后测试GPT-4将英文法律陈述转化为形式化表达的能力，发现存在幻觉函数、遗漏时间范围、偏离形式系统等问题，最严重情况下代码看似可运行且合理，却悄然编码了错误规范。一个案例研究展示，通过计算合同可直接将规则形式化并嵌入具身智能体（如AI看门狗）的操作代码中，生成可审计的行为符号解释。本文主张计算法律可作为治理工具，理想目标是将可执行的法律形式化。
原文摘要 · Abstract (English)
How do we govern AI systems whose reasoning we cannot fully inspect? Governance does not require understanding a system's reasoning. It requires stating what the system is obliged, permitted, and forbidden to do, and checking whether it complied. I present an implementation of Reified Input/Output Logic, the formalism behind the DAPRECO knowledge base, in Wolfram Language: the core I/O axioms, obligations, permissions, constitutive norms, reified eventualities, and temporal operators. I then test whether GPT-4 can translate English legal statements into the formalism, and report the failures: hallucinated functions, omitted temporal scope, deviation from the formalism, and (in the worst cases) code that runs, reads plausibly, but silently encodes the wrong norm. A case study, an AI guard dog operating under a computational contract, shows how formalized rules can extend from a contract directly into the operational code of an embodied agent, producing symbolic, auditable justifications for its behaviour. I argue that computational law can be used as a governance tool and that a desirable goal would be to formalize the law that can and ought to be programmatically executable.
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