A probabilistic formalisation of contextual bias: From forensic analysis to systemic bias in the criminal justice system

Maria Cuellar, Jacqueline Mauro and Amanda Luby

Journal of the Royal Statistical Society Series A, 2022, vol. 185, issue S2, S620-S643

Abstract: Researchers have found evidence of contextual bias in forensic science, but the discussion of contextual bias is currently qualitative. We formalise existing empirical research and show quantitatively how biases can be propagated throughout the legal system, all the way up to the final determination of guilt in a criminal trial. We provide a probabilistic framework for describing how information is updated in a forensic analysis setting by using the ratio form of Bayes' rule. We analyse results from empirical studies using this framework and employ simulations to demonstrate how bias can be compounded where experiments do not exist. We find that even minor biases in the earlier stages of forensic analysis can lead to large, compounded biases in the final determination of guilt in a criminal trial.

Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:bla:jorssa:v:185:y:2022:i:s2:p:s620-s643

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