Artificial Intelligence Application in Law: A Scientometric Review

Isaac Kofi Nti, S. Boateng, Juanita Ahia Quarcoo, P. Nimbe
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引用次数: 1

Abstract

Several topics, problems, and established legal principles are already being challenged using artificial intelligence (AI) in numerous applications. The powers of AI have been snowballing to the point where it is evident that AI applications in law and various economic sectors aid in promoting a good society. However, questions such as who the prolific authors, papers, and institutions are, as well as what the specific and thematic areas of application are, remain unanswered. In the current study, 177 papers on artificial intelligence applications in law published between 1960 and April 29, 2022, were pulled from Scopus using keywords and analysed scientometrically. We identified the strongest citation bursts, the most prolific authors, countries/regions, and primary research interests, as well as their evolution trends and collaborative relationships over the past 62 years. The analysis also identified co-authorship networks, collaboration networks of countries/regions, co-occurrence networks of keywords, and timeline visualization of keywords. This study concludes that systematic study and enough attention are still lacking in artificial intelligence application in law (AIL). The methodical design of the required platforms, as well as the collecting, cleansing, and storage of data; the collaboration of many stakeholders, researchers, and nations/regions; are all problems that AIL must still overcome. Both researchers and industry professionals who are devoted to AIL will find value in the findings.
人工智能在法律中的应用:科学计量学综述
人工智能(AI)在许多应用中已经对一些主题、问题和既定的法律原则提出了挑战。人工智能的力量一直在滚雪球,很明显,人工智能在法律和各种经济领域的应用有助于促进一个美好的社会。然而,诸如谁是多产的作者、论文和机构,以及应用的具体和主题领域是什么等问题仍然没有答案。在目前的研究中,使用关键词从Scopus检索了1960年至2022年4月29日期间发表的177篇关于人工智能在法律中的应用的论文,并对其进行了科学计量学分析。我们确定了在过去62年中最强的引文爆发、最多产的作者、国家/地区、主要研究兴趣,以及它们的演变趋势和合作关系。该分析还确定了合著网络、国家/地区协作网络、关键词共现网络和关键词时间轴可视化。本研究认为,人工智能在法律中的应用还缺乏系统的研究和足够的重视。系统地设计所需的平台,以及收集、清理和存储数据;许多利益攸关方、研究人员和国家/区域的合作;都是美国航空公司必须克服的问题。致力于人工智能的研究人员和行业专业人士都会发现这些发现的价值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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