Computational machineries dedicated to the attribution of legal responsibility should be based on (or, make use of) a stack of definitions relating the notion of legal responsibility to a number of suitably chosen causal notions. This paper presents a general analysis of legal responsibility and of causation in fact based on Hart and Honoré’s work. Some physical aspects of causation in fact are then treated within the “lite” version of DOLCE foundational ontology written in OWL-DL, a standard description logic for (...) the Semantic Web. (shrink)

Reasoning about causation in fact is an essential element of attributing legal responsibility. Therefore, the automation of the attribution of legal responsibility requires a modelling effort aimed at the following: a thorough understanding of the relation between the legal concepts of responsibility and of causation in fact; a thorough understanding of the relation between causation in fact and the common sense concept of causation; and, finally, the specification of an ontology of the concepts that are minimally required for (automatic) common (...) sense reasoning about causation. This article offers a worked-out example of the indicated analysis. Such example consists of: a definition of the legal concept of responsibility (in terms of liability and accountability); a definition of the legal concept of causation in fact (in terms of the initiation of physical processes by an agent and of the provision of reasons and/or opportunities to other agents); CausatiOnt, an AI-like ontology of the common sense (causal) concepts that are minimally needed for reasoning about the legal concept of causation in fact (in particular, the concepts of category, dimension, object, agent, process, event and act). (shrink)