用法律中的规则与判例机制，解决AI对齐中的价值观多元与模糊原则具体化问题。
Rules, Cases, and Reasoning: Positivist Legal Theory as a Framework for Pluralistic AI Alignment
- 借鉴法律中规则与判例互动机制，让抽象原则逐步具象化
- 通过历史案例积累实现价值共识，同时保留多元观点空间
- 适合关注民主化AI对齐与价值多样性研究的学者
法律理论可应对对齐研究中的两个核心问题：价值观多元性与规范模糊性。研究人员需明确如‘帮助性’和‘公平性’等模糊原则的具体含义，并确保技术不排斥其他生活观念与价值立场。法律同样面临此类挑战。主流法律理论表明，法律通过民主权威制定的一般规则与长期判例应用的互动来解决这些问题。规则提供框架，判例则赋予其具体内涵，使实践意义逐渐凝聚，同时为价值分歧保留空间。该思路提示改进现有民主化对齐流程——利用AI生成案例以充实规则内容，从而实现更具包容性的对齐。
原文摘要 · Abstract (English)
Legal theory can address two related key problems of alignment: pluralism and specification. Alignment researchers must determine how to specify what is concretely meant by vague principles like helpfulness and fairness and they must ensure that their techniques do not exclude alternative perspectives on life and values. The law faces these same problems. Leading legal theories suggest the law solves these problems through the interaction of rules and cases, where general rules promulgated by a democratic authority are given specific content through their application over time. Concrete applications allow for convergence on practical meaning while preserving space for disagreement on values. These approaches suggest improvements to existing democratic alignment processes that use AI to create cases that give content to rules, allowing for more pluralist alignment.
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