从专家系统到大模型，看AI如何理解与生成法律解释
Legal interpretation and AI: from expert systems to argumentation and LLMs
- 用知识工程、论证框架和语言模型分阶段实现法律解释自动化
- 大模型可生成符合法律逻辑的解释建议，已在实务中部署
- 适合法律科技从业者与AI伦理研究者参考
人工智能与法律研究在不同阶段以多种方式探索法律解释问题。早期专家系统研究聚焦于法律知识工程，旨在将人工生成的解释精确转化为知识库，确保一致应用。论证研究致力于刻画解释性论点的结构及其辩证互动，以评估论点在论证框架内的可接受性。机器学习研究则关注通过通用与专用语言模型自动产生解释性建议与论据，如今该技术正日益应用于法律实践。
原文摘要 · Abstract (English)
AI and Law research has encountered legal interpretation in different ways, in the context of its evolving approaches and methodologies. Research on expert system has focused on legal knowledge engineering, with the goal of ensuring that human-generated interpretations can be precisely transferred into knowledge-bases, to be consistently applied. Research on argumentation has aimed at representing the structure of interpretive arguments, as well as their dialectical interactions, to assess of the acceptability of interpretive claims within argumentation frameworks. Research on machine learning has focused on the automated generation of interpretive suggestions and arguments, through general and specialised language models, now being increasingly deployed in legal practice.
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