Work

Large Language Models and Explainable Law: a Hybrid Methodology

Year: 2023

Type: preprint

Abstract: The paper advocates for LLMs to enhance the accessibility, usage and explainability of rule-based legal systems, contributing to a democratic and stakeholder-oriented view of legal technology. A methodology is developed to explore the potential use of LLMs for translating the explanations produced by rule-based systems, from high-level programming languages to natural language, allowing all users a fast, clear, and accessible interaction with such technologies. The study continues by building upon these explanations to empower laypeople with the ability to execute complex juridical tasks on their own, using a Chain of Prompts for the autonomous legal comparison of different rule-based inferences, applied to the same factual case.

Source: arXiv (Cornell University)

DOI: 10.48550/arxiv.2311.11811

Authors: Billi, Marco, Parenti, Alessandro, Pisano, Giuseppe, Sanchi, Marco

Institutions: GNA University, University of Bologna

Language: English

Topic: Artificial Intelligence in Law

Subfield: Political Science and International Relations

Field: Social Sciences

Domain: Social Sciences

SDG: Peace, justice, and strong institutions

Open Access status: green

Funder: European Commission