AI and Legal Argumentation: Aligning the Autonomous Levels of AI Legal Reasoning

TL;DR

This paper explores the integration of AI into legal argumentation, proposing a new framework to measure AI's autonomous reasoning levels and its potential to achieve human-like legal argumentation.

Contribution

It introduces a novel meta-approach applying Levels of Autonomy to AI legal reasoning, advancing the assessment of AI's maturity in legal argumentation.

Findings

Proposes a new framework for measuring AI autonomy in legal reasoning

Highlights the potential for AI to reach human-equivalent legal argumentation

Provides a structured approach to gauge progress in AI legal reasoning

Abstract

Legal argumentation is a vital cornerstone of justice, underpinning an adversarial form of law, and extensive research has attempted to augment or undertake legal argumentation via the use of computer-based automation including Artificial Intelligence (AI). AI advances in Natural Language Processing (NLP) and Machine Learning (ML) have especially furthered the capabilities of leveraging AI for aiding legal professionals, doing so in ways that are modeled here as CARE, namely Crafting, Assessing, Refining, and Engaging in legal argumentation. In addition to AI-enabled legal argumentation serving to augment human-based lawyering, an aspirational goal of this multi-disciplinary field consists of ultimately achieving autonomously effected human-equivalent legal argumentation. As such, an innovative meta-approach is proposed to apply the Levels of Autonomy (LoA) of AI Legal Reasoning (AILR) to the maturation of AI and Legal Argumentation (AILA), proffering a new means of gauging progress in this ever-evolving and rigorously sought domain.