Supporting Discussions About Forensic Bayesian Networks Using Argumentation

Remi Wieten, Floris Bex, Hendrik Prakken, Silja Renooij

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

3 Citations (Scopus)

Abstract

Bayesian networks (BNs) are powerful tools that are increasingly being used by forensic and legal experts to reason about the uncertain conclusions that can be inferred from the evidence in a case. Although in BN construction it is good practice to document the model itself, the importance of documenting design decisions has received little attention. Such decisions, including the (possibly conflicting) reasons behind them, are important for legal experts to understand and accept probabilistic models of cases. Moreover, when disagreements arise between domain experts involved in the construction of BNs, there are no systematic means to resolve such disagreements. Therefore, we propose an approach that allows domain experts to explicitly express and capture their reasons pro and con modelling decisions using argumentation, and that resolves their disagreements as much as possible. Our approach is based on a case study, in which the argumentation structure of an actual disagreement between two forensic BN experts is analysed.
Original languageEnglish
Title of host publicationSeventeenth International Conference on Artificial Intelligence and Law
Subtitle of host publicationproceedings of the conference
Place of PublicationNew York, NY
PublisherACM Press
Pages143-152
Number of pages10
ISBN (Print)978-1-4503-6754-7
Publication statusPublished - 2019
Event17th International Conference on Articial Intelligence and Law
- Montreal, Canada
Duration: 17-Jun-201921-Jun-2019
https://icail2019-cyberjustice.com

Conference

Conference17th International Conference on Articial Intelligence and Law
Abbreviated titleICAIL 2019
CountryCanada
CityMontreal
Period17/06/201921/06/2019
Internet address

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