The Application of Artificial Intelligence in Law : A Bibliometric Analysis

Abstract

Purpose : This research presented an extensive review of applications of artificial intelligence (AI) in law, identified existing trends, and revealed emerging themes and areas of focus in these disciplines. Methodology : This study performed a bibliometric analysis on 1,114 articles obtained from Scopus. It employed thematic analysis, co-occurrence analysis, and citation analysis to assess the contributions of different research components. Findings : This research illustrated the close and interdependent relationship between law and AI. Two of the emerging prominent themes were neural networks and adaptation control. Additionally, a niche theme showed how decision support systems, data mining, legal reasoning, argumentation, and optimization are vital. Moreover, AI and business law were connected with ethics, humanitarian law, case-based reasoning, decision support systems, machine learning, and big data. Among the leading publishers in this category are China, the USA, the UK, and Italy, all of whom have published a growing number of titles. The most popular keywords used were “laws and legislation,” “human,” and “machine learning.” Practical Implications : The research contributed to the AI and business law literature. Managers and policymakers can prioritize areas based on the thematic issues that emerged from the literature. It also highlighted the areas of difficulty for organizations, such as those involving human rights and data privacy. The results are intended to guide business law regulations for AI development. Originality : The study is unique, as it is one of the early studies that recognized the relationship between business law and AI, and recognized emerging themes and modern challenges.

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