  In this paper, we introduce the latent racial bias, a metric and method to
evaluate the racial bias within specific events. For the purpose of this paper
we explore the British Home Office dataset of stop-and-search incidents. We
explore the racial bias in the choice of targets, using a number of statistical
models such as graphical probabilistic and TrueSkill Ranking. Firstly, we
propose a probabilistic graphical models for modelling racial bias within
stop-and-searches and explore varying priors. Secondly using our inference
methods, we produce a set of probability distributions for different
racial/ethnic groups based on said model and data. Finally, we produce a set of
examples of applications of this model, predicting biases not only for stops
but also in the reactive response by law officers.
