The winter, the summer and the summer dream of artificial intelligence in law

IF 3.1 2区社会学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

Artificial Intelligence and Law Pub Date : 2022-02-03 DOI:10.1007/s10506-022-09309-8

Enrico Francesconi

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引用次数: 10

Abstract

This paper reflects my address as IAAIL president at ICAIL 2021. It is aimed to give my vision of the status of the AI and Law discipline, and possible future perspectives. In this respect, I go through different seasons of AI research (of AI and Law in particular): from the Winter of AI, namely a period of mistrust in AI (throughout the eighties until early nineties), to the Summer of AI, namely the current period of great interest in the discipline with lots of expectations. One of the results of the first decades of AI research is that “intelligence requires knowledge”. Since its inception the Web proved to be an extraordinary vehicle for knowledge creation and sharing, therefore it’s not a surprise if the evolution of AI has followed the evolution of the Web. I argue that a bottom-up approach, in terms of machine/deep learning and NLP to extract knowledge from raw data, combined with a top-down approach, in terms of legal knowledge representation and models for legal reasoning and argumentation, may represent a promotion for the development of the Semantic Web, as well as of AI systems. Finally, I provide my insight in the potential of AI development, which takes into account technological opportunities and theoretical limits.

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法律中人工智能的冬、夏、夏之梦

本文反映了我作为IAAIL主席在ICAIL 2021上的讲话。它的目的是给出我对人工智能和法律学科现状的看法，以及可能的未来前景。在这方面，我经历了人工智能研究的不同季节（尤其是人工智能和法律）：从人工智能的冬天，即对人工智能的不信任时期（整个80年代到90年代初），到人工智能的夏天，即当前对该学科非常感兴趣并充满期望的时期。人工智能研究最初几十年的成果之一是“智能需要知识”。自诞生以来，网络就被证明是知识创造和共享的非凡载体，因此，如果人工智能的进化遵循了网络的进化，也就不足为奇了。我认为，在机器/深度学习和NLP方面，自下而上的方法从原始数据中提取知识，再加上在法律知识表示和法律推理和论证模型方面的自上而下的方法，可能会促进语义网以及人工智能系统的发展。最后，我提供了我对人工智能发展潜力的见解，其中考虑了技术机遇和理论限制。

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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来源期刊

Artificial Intelligence and Law Multiple-

CiteScore

9.50

自引率

26.80%

发文量

期刊介绍： Artificial Intelligence and Law is an international forum for the dissemination of original interdisciplinary research in the following areas: Theoretical or empirical studies in artificial intelligence (AI), cognitive psychology, jurisprudence, linguistics, or philosophy which address the development of formal or computational models of legal knowledge, reasoning, and decision making. In-depth studies of innovative artificial intelligence systems that are being used in the legal domain. Studies which address the legal, ethical and social implications of the field of Artificial Intelligence and Law. Topics of interest include, but are not limited to, the following: Computational models of legal reasoning and decision making; judgmental reasoning, adversarial reasoning, case-based reasoning, deontic reasoning, and normative reasoning. Formal representation of legal knowledge: deontic notions, normative modalities, rights, factors, values, rules. Jurisprudential theories of legal reasoning. Specialized logics for law. Psychological and linguistic studies concerning legal reasoning. Legal expert systems; statutory systems, legal practice systems, predictive systems, and normative systems. AI and law support for legislative drafting, judicial decision-making, and public administration. Intelligent processing of legal documents; conceptual retrieval of cases and statutes, automatic text understanding, intelligent document assembly systems, hypertext, and semantic markup of legal documents. Intelligent processing of legal information on the World Wide Web, legal ontologies, automated intelligent legal agents, electronic legal institutions, computational models of legal texts. Ramifications for AI and Law in e-Commerce, automatic contracting and negotiation, digital rights management, and automated dispute resolution. Ramifications for AI and Law in e-governance, e-government, e-Democracy, and knowledge-based systems supporting public services, public dialogue and mediation. Intelligent computer-assisted instructional systems in law or ethics. Evaluation and auditing techniques for legal AI systems. Systemic problems in the construction and delivery of legal AI systems. Impact of AI on the law and legal institutions. Ethical issues concerning legal AI systems. In addition to original research contributions, the Journal will include a Book Review section, a series of Technology Reports describing existing and emerging products, applications and technologies, and a Research Notes section of occasional essays posing interesting and timely research challenges for the field of Artificial Intelligence and Law. Financial support for the Journal of Artificial Intelligence and Law is provided by the University of Pittsburgh School of Law.