Epistemologies of predictive policing

Mathematical social science, social physics and machine learning

Bibliographic Data

ID5260802
AuthorsJens Hälterlein (0000-0002-0328-2029, University of Freiburg, corresponding author)
Year2021
Volume8
Issue1
Publication date2021-01-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueBig Data & Society (JOURNAL)
Journal identifiersISSN: 2053-9517 • E-ISSN: 2053-9517
PublisherSAGE Publications Inc (PUBLISHER)
DOI10.1177/20539517211003118
OpenAlexW3137585408
LanguageEN
Citations received19
References cited64

Predictive policing has become a new panacea for crime prevention. However, we still know too little about the performance of computational methods in the context of predictive policing. The paper provides a detailed analysis of existing approaches to algorithmic crime forecasting. First, it is explained how predictive policing makes use of predictive models to generate crime forecasts. Afterwards, three epistemologies of predictive policing are distinguished: mathematical social science, social physics and machine learning. Finally, it is shown that these epistemologies have significant implications for the constitution of predictive knowledge in terms of its genesis, scope, intelligibility and accessibility. It is the different ways future crimes are rendered knowledgeable in order to act upon them that reaffirm or reconfigure the status of criminological knowledge within the criminal justice system, direct the attention of law enforcement agencies to particular types of crimes and criminals and blank out others, satisfy the claim for the meaningfulness of predictions or break with it and allow professionals to understand the algorithmic systems they shall rely on or turn them into a black box. By distinguishing epistemologies and analysing their implications, this analysis provides insight into the techno-scientific foundations of predictive policing and enables us to critically engage with the socio-technical practices of algorithmic crime forecasting

Criminal justice · Criminology · Data science · Law enforcement · Political science · Predictive analytics · Sociology · Computer Science · Crime Patterns and Interventions · Cybercrime and Law Enforcement Studies · Law · Wildlife Conservation and Criminology Analyses · Artificial Intelligence

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