The Practice of Predictive Identification

Optimising for Organisational Needs

Bibliographic Data

ID12729970
AuthorsFrank Jansen (0000-0002-1295-7788, Cardiff University, corresponding author), Fieke Jansen (corresponding author)
Year2024
Volume22
Issue3
Pages292-303
Publication date2024-09-07
Open AccessYes
TypeARTICLE
VenueSurveillance & Society (JOURNAL)
Journal identifiersISSN: 1477-7487 • E-ISSN: 1477-7487
PublisherSurveillance Studies Network (PUBLISHER • GB)
DOI10.24908/ss.v22i3.15788
OpenAlexW4402344596
LanguageEN
Citations received3

The advent of predictive policing systems demonstrates an increased interest in more novel forms of data processing for the purpose of crime control. This paper draws on interviews with police practitioners in the Netherlands and the UK to deconstruct the rationalities that are embedded within the turn to predictive identification. Debates on predictive policing have predominantly centred data in the analysis of the institutional and societal implication of prediction, linking its use to the premise of efficiency and accuracy and foregrounding issues around bias and discrimination. Yet, little is known about its actual practice. In policing, I find that studying data as practice surfaces new insights into the relationship between risk and the ways in which crime priorities are operationalised and the security mandate of the state is negotiated. Drawing on Harcourt’s (2008) observation that the desire to predict crime says more about the police than it does about a potential offender, I argue that predictive identification is not about prediction, nor about efficiency, but rather it is about optimisation. Here, datafication serves to overcome self-defined organisational challenges within the police

Biology · Business · Identification (biology · Process management · Risk analysis (engineering · Complex Systems and Decision Making · Computer Science

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