A method for explaining Bayesian networks for legal evidence with scenarios

In a criminal trial, a judge or jury needs to reason about what happenedbased on the available evidence, often including statistical evidence. While aprobabilistic approach is suitable for analysing the statistical evidence, a judge orjury may be more inclined to use a narrative or argumentative approach whenconsidering the case as a whole. In this paper we propose a combination of twoapproaches, combining Bayesian networks with scenarios. Whereas a Bayesiannetwork is a popular tool for analysing parts of a case, constructing and understanding a network for an entire case is not straightforward. We propose anexplanation method for understanding a Bayesian network in terms of scenarios.This method builds on a previously proposed construction method, which weslightly adapt with the use of scenario schemes for the purpose of explaining. The resulting structure is explained in terms of scenarios, scenario quality and evidential support. A probabilistic interpretation of scenario quality is provided using the concept of scenario schemes. Finally, the method is evaluated by means of a case study