Legal interpretation and AI: From expert systems to argumentation and LLMs

AI and law research has encountered legal interpretation in different ways, in the context of its evolving approaches and methodologies. Research on expert systems 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 the acceptability of interpretive claims within argumentation frameworks. Research on machine learning has focused on automated generation of interpretive suggestions and arguments, through general and specialized generative AI tools, now being increasingly deployed in legal practice.