Building Bayesian networks for legal evidence with narratives: a case study evaluation

In a criminal trial, evidence is used to draw conclusions about what happened concerning a supposed crime. Traditionally, the three main approaches to modeling reasoning with evidence are argumentative, narrative and probabilistic approaches. Integrating these three approaches could arguably enhance...

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Bibliographic Details
Published in:Artificial intelligence and law 2014-12, Vol.22 (4), p.375-421
Main Authors: Vlek, Charlotte S., Prakken, Henry, Renooij, Silja, Verheij, Bart
Format: Article
Language:English
Subjects:
Analysis
Applied sciences
Artificial Intelligence
Bayesian analysis
Case studies
Computer Science
Computer science
control theory
systems
Construction
Crime
Design engineering
Evidence
Evidence (Law)
Exact sciences and technology
Expert systems
General aspects
Information retrieval. Graph
Information Storage and Retrieval
Intellectual Property
IT Law
Legal
Legal Aspects of Computing
Legal studies
Legislation. Standardization
Marijuana
Media Law
Murders & murder attempts
Narratives
Networks
Philosophy of Law
Studies
Theoretical computing
Trials
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Summary:In a criminal trial, evidence is used to draw conclusions about what happened concerning a supposed crime. Traditionally, the three main approaches to modeling reasoning with evidence are argumentative, narrative and probabilistic approaches. Integrating these three approaches could arguably enhance the communication between an expert and a judge or jury. In previous work, techniques were proposed to represent narratives in a Bayesian network and to use narratives as a basis for systematizing the construction of a Bayesian network for a legal case. In this paper, these techniques are combined to form a design method for constructing a Bayesian network based on narratives. This design method is evaluated by means of an extensive case study concerning the notorious Dutch case of the Anjum murders.
ISSN:0924-8463
1572-8382
DOI:10.1007/s10506-014-9161-7