Case-Based Models of Legal Reasoning in a Civil Law Context

1.0 Introduction Researchers in Artificial Intelligence and Law (AI & Law) have developed a number of computational models of case-based legal reasoning. For example, see Hypo (Ashley, 1987; 1990), CABARET (Rissland & Skalak, 1991), GREBE (Branting, 1991; 1999), CATO (Aleven, 1997; 2003), BankXX (Rissland, Skalak, et al. 1996), and Split-Up (Zeleznikow, Stranieri, et al., 1995-1996). The models have originated in common law jurisdictions, often by lawyers/computer scientists influenced by common law legal practice and traditions. More recently, some of the case-based models have been developed by researchers in countries with more or less civil law traditions (Prakken & Sartor, 1997; Bench-Capon & Sartor, 2001). The latter developments beg the question of whether AI & Law models of case-based legal reasoning are relevant in civil law jurisdictions. This paper addresses that and some related questions: To what extent is reasoning with precedents, so central in common law legal practice, practiced in civil law jurisdictions? Do civil law judges and practitioners reason with cases? If so, are there significant differences between the ways they reason with cases and those of their common law counterparts? What is the relevance in a civil law context of computational models of case-based and analogical legal reasoning developed in the common law tradition? Can/should they be incorporated into legal practice in civil law jurisdictions and how?