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 language | English |
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Title of host publication | Seventeenth International Conference on Artificial Intelligence and Law |
Subtitle of host publication | proceedings of the conference |
Place of Publication | New York, NY |
Publisher | ACM Press |
Pages | 143-152 |
Number of pages | 10 |
ISBN (Print) | 978-1-4503-6754-7 |
Publication status | Published - 2019 |
Event | 17th International Conference on Articial Intelligence and Law - Montreal, Canada Duration: 17-Jun-2019 → 21-Jun-2019 https://icail2019-cyberjustice.com |
Conference
Conference | 17th International Conference on Articial Intelligence and Law |
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Abbreviated title | ICAIL 2019 |
Country/Territory | Canada |
City | Montreal |
Period | 17/06/2019 → 21/06/2019 |
Internet address |