作者：王禄生
作者介绍：东南大学法学院研究员
出版日期：2020年4月9日
内容提要 作为“领域大数据理论”的重要组成部分，法律大数据的基础理论研究由 于过分受通用大数据技术的框架影响而在本体论、认识论与方法论方面存在不足。在本体 论方面，将法律大数据视为通用大数据技术在法律领域的平移应用，并将大数据的通用特征 视作法律大数据的领域特征；在认识论方面，奉行数据驱动的经验主义，忽视甚至排斥法学 理论嵌入；在方法论方面，过度重视技术瓶颈的解决，而淡化“领域知识壁垒”的应对。下 一步，要在充分认识领域特殊性的基础上展开法律大数据“领域理论”研究。在本体论层面， 构建法律大数据的领域特征，实现“4V 特征”与“3A 特征”的结合；在认识论层面，打造“轻 量级理论驱动”的法律大数据领域认识论；在方法论层面，关注法律大数据所面临的“领域 知识壁垒”，并从提升法律人地位、推动领域大数据技术创新和打造法律知识工程师培养体 系三方面予以应对。
关键词 法律大数据 法律人工智能 领域理论 轻量级理论驱动 领域知识壁垒
Abstract: As an essential part of the‘domain theory of big data’, the basic theoretical research of legal big data is too much influenced by the framework of general big data technology and has shortcomings in ontology, epistemology and methodology. In terms of ontology, legal big data is regarded as the application of big data technology in law, and the general characteristics of big data are considered as the domain characteristics of legal big data. In terms of epistemology, empiricism epistemology driven by data is adopted and it ignores or even excludes the embedding of legal theory. In terms of methodology, too much attention is paid to the solution of the technical bottleneck, while the solution of the‘domain knowledge barrier’is ignored. The next step is to construct the‘domain theory’of legal big data on the basis of fully considering the particularity of the legal domain. Construct the domain features of legal big data at the ontological level, and promote the transformation from‘4V features’to‘3A features’. At the level of epistemology, we should build a lightweight theory-driven epistemology in the domain of legal big data. In terms of methodology, we should pay attention to the‘domain knowledge barrier’faced by legal big data, and deal with it from three aspects: improving the status of the legal profession, promoting the domain technical innovation of legal big data, and building the training system of legal knowledge engineers.