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CAUSATIONT: Modeling Causation in AI&Law

Academic Article
Publication Date:
2005
abstract:
Abstract. Reasoning about causation in fact is an essential element of attributing legal responsibility. Therefore, the automation of the attri- bution of legal responsibility requires a modelling e®ort aimed at the following: a thorough understanding of the relation between the legal concepts of responsibility and of causation in fact; a thorough under- standing 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 rea- soning about causation. This article o®ers a worked out example of the indicated analysis, which comprises: a definition of the legal concept of responsibility; a definition of the legal concept of causation in fact; 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.
Iris type:
01.01 Articolo in rivista
Keywords:
Applied Legal Ontology; Artificial Intelligence and Law; Causal Relations; Philosophy; Legal Theory
List of contributors:
Lehmann, ALBERTO JOSEPH
Handle:
https://iris.cnr.it/handle/20.500.14243/29144
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