ABSTRACT
Modelling reasoning with precedents has been a central concern of AI and Law since its inception. A recent paper has provided a discussion (in jurisprudential terms) of whether such reasoning is best seen as rule application or analogy. We review some of the prominent AI and Law approaches and find that over the years there has been a move away from analogy to rule application. Even in those approaches which do use analogy, however, the analogies handled concern only analogies between cases represented as sets of factors, and do not consider analogies between the elements of the fact situations peculiar to particular cases. In actual practice, however, analogies are used to determine which factors are relevant in a case, and which party is favoured by particular aspects of the case situation. Such analogies relate not to factors, but to real-world elements of the case and are hard to make and critique without a comprehensive common sense ontology. Thus while we may be able to construct specific ontologies to model past examples of such analogical reasoning, which can be useful for simulation and teaching, the ability to perform analogical reasoning on novel situations is, and is likely to remain, infeasible. This conclusion suggests that there will always be limits to our ability to construct systems able to handle new cases presenting novel situations.
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Index Terms
- Reasoning with Legal Cases: Analogy or Rule Application?
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