Machine learning and legal argument

Mumford, J ORCID: 0000-0003-2467-5785, Atkinson, K ORCID: 0000-0002-5683-4106 and Bench-Capon, T
(2021) Machine learning and legal argument. In: 21st Workshop on Computational Models of Natural Argument, 2021-9-2 - 2021-9-3.

[img] Text
CMNA_2021.pdf - Author Accepted Manuscript

Download (232kB) | Preview


Although the argumentation justifying decisions in particular cases has always been central to AI and Law, it has recently become a burning issue as black box machine learning approaches become prevalent. In this paper we review the understanding of legal argument that has been developed in AI and Law, and indicate the most appropriate ways in which Machine Learning approaches can contribute to legal argument. We identify some key questions that must be explored to provide acceptable explanations for legal ML systems. This provides the context and directions of our current research project.

Item Type: Conference or Workshop Item (Unspecified)
Divisions: Faculty of Science and Engineering > School of Electrical Engineering, Electronics and Computer Science
Depositing User: Symplectic Admin
Date Deposited: 06 Sep 2021 07:31
Last Modified: 18 Jan 2023 21:30