This report presents the takeaways of the inaugural Workshop on Generative AI and Law (GenLaw), held in July 2023. A cross-disciplinary group of practitioners and scholars from computer science and law convened to discuss the technical, doctrinal, and policy challenges presented by law for Generative AI, and by Generative AI for law, with an emphasis on U.S. law in particular. We begin the report with a high-level statement about why Generative AI is both immensely significant and immensely challenging for law. To meet these challenges, we conclude that there is an essential need for 1) a shared knowledge base that provides a common conceptual language for experts across disciplines; 2) clarification of the distinctive technical capabilities of generative-AI systems, as compared and contrasted to other computer and AI systems; 3) a logical taxonomy of the legal issues these systems raise; and, 4) a concrete research agenda to promote collaboration and knowledge-sharing on emerging issues at the intersection of Generative AI and law. In this report, we synthesize the key takeaways from the GenLaw workshop that begin to address these needs. All of the listed authors contributed to the workshop upon which this report is based, but they and their organizations do not necessarily endorse all of the specific claims in this report.

翻译：本报告总结了2023年7月举行的首届生成式人工智能与法律研讨会（GenLaw）的核心成果。来自计算机科学和法学领域的跨学科从业者与学者共同探讨了法律对生成式人工智能，以及生成式人工智能对法律所构成的技术、理论与实践挑战，重点聚焦美国法律体系。报告首先从宏观层面阐述了为何生成式人工智能对法律领域既具有重大意义又带来严峻挑战。为应对这些挑战，我们认为亟需：1）建立共享知识库，为跨学科专家提供通用概念语言；2）明确生成式人工智能系统相对于其他计算机和人工智能系统的独特技术能力；3）构建这些系统所引发的法律问题的逻辑分类体系；4）制定具体的研究议程，以促进生成式人工智能与法律交叉领域新兴问题的协作与知识共享。本报告综合了GenLaw研讨会中初步回应上述需求的关键成果。所有列名作者均参与了作为报告基础的研讨会，但作者及其所属机构未必完全认同报告中的所有具体观点。