Latent Racial Bias -- Evaluating Racism in Police Stop-and-Searches

2020/05/08 by Akbir Khan, Khan, Akbir
Computer Science · Mathematics · #Advanced Statistical Methods and Models #Applications (stat.AP) #Bayesian Modeling and Causal Inference #FOS: Computer and information sciences

paper · pdf · doi:10.48550/arxiv.2005.13463

openalex publication_date 2020/05/08 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

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.

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