A Hybrid Artificial Intelligence Methodology for Legal Analysis

Authors

  • Monica Palmirani
  • Salvatore Sapienza
  • Kevin Ashley

DOI:

https://doi.org/10.15168/2284-4503-3206

Keywords:

Legal analysis, methodology, machine learning, hybrid AI

Abstract

The following study introduces “Hybrid Artificial Intelligence Methodology for Legal Analysis” (HAIMLA). It consists of a six-step method to design, develop, validate and deploy artificial intelligence (AI) systems for legal analyses that are built on asynchronous unsupervised and supervised techniques applied to legal texts serialised in the Akoma Ntoso XML standard. HAIMLA methodology is drawn upon the existing literature and case studies in AI & Law and it is grounded on consolidated philosophical approaches. Taken together, this background inspires design requirements that constitute the essential pillars of HAIMLA and new directions for future refinements and implementations.

 

This study has been conducted with the support of the European Commission funds within ERC HyperModeLex (Grant agreement ID: 101055185). The contribution of Salvatore Sapienza is supported by Programma Operativo Nazionale (PON) “Ricerca e Innovazione” 2014–2020 CCI2014IT16M2OP005, by the Italian Ministry of University and Research.

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Published

2024-10-17

How to Cite

1.
Palmirani M, Sapienza S, Ashley K. A Hybrid Artificial Intelligence Methodology for Legal Analysis. BioLaw [Internet]. 2024 Oct. 17 [cited 2024 Dec. 22];(3):389-40. Available from: https://teseo.unitn.it/biolaw/article/view/3206

Issue

Section

Artifical Intelligence and Law - Essays

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