Artificial intelligence as applied to the legal domain has gained momentum thanks to the large, annotated corporate legal and case-law collections, human chats, and social media information now available in open data. Often represented in XML or other Semantic Web technologies, these now make it possible to use the AI theory developed by the JURIX community in over thirty years of research. Innovative machine and deep-learning techniques with which to classify legal texts and detect terms, principles, concepts, evidence, named entities, and rules are also emerging, and the last five years have seen a gradual increase in their practical application. This book presents papers from the 31st International Conference on Legal Knowledge and Information Systems (JURIX 2018), held in Groningen, the Netherlands, in December 2018. The support of the Dutch Foundation for Legal Knowledge Based Systems for the JURIX conference has transformed a domestic workshop into an international event, with theoretical contributions, applied work, demo prototypes, a hackathon, and a doctoral consortium. Of the 72 submissions received, 17 full papers and 11 short papers were selected for publication, representing an acceptance rate of approximately 38%. Machine learning for the legal domain prevails in the JURIX 2018 program, with traditional research mainstreams concerning legal reasoning and argumentation, natural-language processing, legal-text retrieval, and legal semantic modelling. An emerging topic is blockchain, which has graduated from the workshop area to the main program. The book offers an overview of the ways in which innovative information technologies are merging with legal theory, argumentation, and practice.