AI and Law is a classic field for AI research: it poses difficult and interesting problems for AI, and its projects inform both AI and its focal domain, the law itself. This special issue reports on a range of projects, from those where the law motivates fundamental research and whose results reach beyond the legal domain, to those that partake of the benefits of techniques and wisdom from AI as a whole. For instance, projects tackling legal argument have not only created programs that produce legal arguments but also led to insights and advances in the logic of argumentation. Projects with an applications bent have often provided insights about the limitations and nuances of existing techniques, and have served as the catalysts for developing new approaches. For instance, harnessing models of legal argument to teach law students how to argue has led to refinements to and extensions of the models. There is a synergy not only between law and AI, but also between AI and AI and Law. In fact, the work on Case-Based Reasoning (CBR) done in the AI and Law community provided one of the most important streams of results that contributed to the birth of that area in the mid-1980s. Currently, work on legal argumentation is having a similar impact on the international non-standard logic and argumentation communities.
AI and Law is much more than an applications area. Its concerns touch upon issues at the very heart of AI: reasoning, representation, and learning. For the AI researcher interested in symbolic methods-or methods of whatever stripe-that are focused on providing explanations and justifications, AI and Law is an excellent arena. No matter how a reasoner arrives at a legal answer it must be explained, justified, compared to and contrasted with alternatives. For the researcher interested in topics like negotiation, decision-making, e-commerce, natural language, information retrieval and extraction, and data mining, AI and Law is a rich source of problems and inspiration.