Avoiding probabilistic reasoning fallacies in legal practice using Bayesian networks
Norman Fenton, Martin Neil · 2011
2 Probabilistic fallacies, such as the prosecutor fallacy, have been widely documented, yet these fallacies continue to occur in legal practice. This paper considers how best to avoid them, drawing on our experience as expert witnesses/advisors in recent trials. Although most fallacies are easily avoided by applying Bayes ' Theorem, attempts to explain this to lawyers using the standard mathematical formulas seem doomed to failure. For simple arguments it is possible to explain common fallacies using purely visual presentation alternatives to the Bayes formulas (such as event probability trees) in ways that are fully understandable to lay people. However, as the evidence (and dependence between different evidence) becomes more complex, these visual approaches become infeasible. We show how Bayesian networks can be used to address the more complex arguments in such a way that it is not necessary to expose the underlying complex Bayesian computations. We demonstrate this new approach in explaining well known fallacies and a new fallacy that arose in a recent major murder trial. We also address the barriers to more widespread take-up of these methods within the legal profession, including the need to ‘believe ’ the correctness of Bayesian calculations and the common reluctance to consider subjective prior probabilities.