CAUSATIONT: Modeling Causation in AI&Law

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.

Tipo Pubblicazione: 
Articolo
Author or Creator: 
Lehmann
J.
Breuker
Brouwer
B.
Publisher: 
Springer, Berlin , Germania
Source: 
Lecture notes in computer science 3369 (2005): 77–96.
info:cnr-pdr/source/autori:Lehmann, J., Breuker, J., & Brouwer, B./titolo:CAUSATIONT: Modeling Causation in AI&Law/doi:/rivista:Lecture notes in computer science/anno:2005/pagina_da:77/pagina_a:96/intervallo_pagine:77–96/volume:3369
Date: 
2005
Resource Identifier: 
http://www.cnr.it/prodotto/i/46758