AI in law evolved from rule-based expert systems to advanced argumentation models.
Large Language Models (LLMs) now assist in legal interpretation and reasoning tasks.
The shift reflects AI's growing ability to handle complex, nuanced legal arguments.
Integration of AI raises questions about accuracy, ethics, and human oversight in legal decisions.
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arXiv:2603.05392v1 Announce Type: new
Abstract: 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 a
# Artificial Intelligence (AI)
**Artificial Intelligence (AI)** is a specialized field of computer science dedicated to the development and study of computational systems capable of performing tasks typically associated with human intelligence. These tasks include learning, reasoning, problem-solvi...
A large language model (LLM) is a language model trained with self-supervised machine learning on a vast amount of text, designed for natural language processing tasks, especially language generation. The largest and most capable LLMs are generative pre-trained transformers (GPTs) that provide the c...
--> Computer Science > Artificial Intelligence arXiv:2603.05392 [Submitted on 5 Mar 2026] Title: Legal interpretation and AI: from expert systems to argumentation and LLMs Authors: Václav Janeček , Giovanni Sartor View a PDF of the paper titled Legal interpretation and AI: from expert systems to argumentation and LLMs, by V\'aclav Jane\v ek and Giovanni Sartor View PDF Abstract: 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. Subjects: Artificial Intelligence (cs.AI) Cite as: arXiv:2603.05392 [cs.AI] (or arXiv:2603.05392v1 [cs.AI] for this version) https://doi.org/10.48550/arXiv.2603.05392 Focus to learn more arXiv-issued DOI via DataCite (pending registration) Submission history From: Giovanni Sartor [ view email ] [v1] Thu, 5 Mar 2026 17:22:56 UTC (647 KB) Full-text links: Access Paper: View a PDF of the paper titled Legal interpretation and AI: from expert systems to argumentation and LLMs, by V\'aclav Jane\v ek and Giovanni Sartor View PDF view license Current browse context: cs.AI < prev | next > new | recent | 2026-03 Change to browse by: cs References & Citations NASA ADS Google Scholar Semantic Scholar export BibTeX citation Loading... BibTeX formatted citation × loading... Data provided by: Bookmark Bibliographic Tools Bibliographic an...
