Design, Validation, and Risk Assessment of LLM-Based Generative AI Systems Operating in the Legal Sector
Large Language Models (LLMs) are increasingly capable of supporting user decisions and performing various tasks autonomously in a wide range of professional domains, including the legal sector. In this work, we describe the general lifecycle of LLM-based systems and the architecture of a system designed to support legal experts in the process of generating maxims from judgments. We propose three application-specific performance metrics and a general-purpose assessment method suitable for the comparison of different systems in any content generation task. Finally, we discuss the results achieved by the system prototype that, according to a board of magistrates, outperforms human experts in the task of generating maxims from judgments.
Authors
- Antonio Moschitta (ORCID: https://orcid.org/0000-0001-9807-5948)
- Emanuele Buchicchio (ORCID: https://orcid.org/0000-0002-2786-5931)
- Francesco Santoni (ORCID: https://orcid.org/0000-0003-4964-8556)
- Alessio De Angelis (ORCID: https://orcid.org/0000-0001-7953-4272)
- Paolo Carbone (ORCID: https://orcid.org/0000-0003-0540-1287)
- Lucio San Marco
Institutions
- University of Perugia (IT)
Publication Details
- Published
- 2024-10-16
- DOI
- https://doi.org/10.1109/isse63315.2024.10741134
- Citations
- 3
- Primary Topic
- Law, AI, and Intellectual Property
- Type
- article
- Field-Weighted Citation Impact
- 1.04