The opportunity prior: a proof-based prior for criminal cases

Abstract

One of the greatest challenges to the use of probabilistic reasoning in the assessment of criminal evidence is the ‘problem of the prior’, i.e. the difficulty in establishing an acceptable prior probability of guilt. Even strong supporters of a Bayesian approach have often preferred to ignore priors and focus on the likelihood ratio (LR) of the evidence. But to calculate if the probability of guilt, given the evidence reaches the probability required for conviction (the standard of proof), the LR has to be combined with a prior. In this article, we propose a solution to the ‘problem of the prior’: the defendant shall be treated as a member of the set of ‘possible perpetrators’ defined as the people who had the same or better opportunity as the defendant to commit the crime. For this purpose, we introduce the concept of an ‘extended crime scene’. The number of people who had the same or better opportunity as the defendant is the number of people who were just as close or closer to the crime scene, in time and space. We demonstrate how the opportunity prior is incorporated into a generic Bayesian network model that allows us to integrate other evidence about the case.