Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review


This chapter explores definitions and understandings of the term ‘bias’ common to the disciplines of law, computer science and criminology, which are crucial to understanding the significance of bias in digital criminology. By doing so, we highlight similarities and differences in such definitions and understandings. The chapter presents selected examples of biases that can occur in relation to the use of data-driven and algorithmic tools within criminal justice, highlighting scholarly discourse on analysis, as well as risk and mitigation from the perspectives of the above disciplines. The term bias is frequently used to refer to unlawful discrimination based on protected characteristics, such as race, which can commonly occur in the criminal justice system (Richardson, Schultz and Crawford, 2019). We offer a taxonomy of bias to help researchers looking at bias in these contexts. Although out of scope for this chapter, we note the overlap between issues of bias and other important rights, including those relating to privacy and data protection, and the issue of collection and use of sensitive demographic data for the purposes of mitigating bias (CDEI, 2023).
Original languageEnglish
Title of host publicationHandbook of Digital Criminology
EditorsMareile Kaufmann, Heidi Mork Lomell
Place of PublicationBerlin, Germany
PublisherDe Gruyter
Publication statusAccepted/In press - 6 Feb 2024

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