Technologies of Crime Prediction: Comparing the Reception of Big Data Analytics in Policing and Courts

• In Event: 4111 - Innovation, Technology, in Studies of Crime and Social Control

Abstract

An increasing number of algorithmic technologies are being taken up in the U.S. criminal justice system. Yet there is little research to date on the actual impact of the adoption of big data analytics on the functioning of criminal justice institutions. In this project, we draw on ethnographic fieldwork conducted within a large urban police department and a midsized criminal court to assess the uses and interpretations of predictive technologies at different stages of the criminal justice process. We first show that similar arguments are mobilized to justify their widespread adoption in law enforcement and court contexts. In both cases, predictive algorithms are described as more objective and efficient than discretionary gut feelings. We then turn to the actual uses of predictive analytics on the ground and document similar processes of professional resistance among law enforcement and legal professionals. In both cases, resentment against predictive technologies is fueled by fears of deskilling and heightened managerial surveillance, although important differences in resistance emerge based on actors’ positions within their organizational hierarchy. After sketching differences between policing and criminal courts, the article concludes by delineating the implications of such findings for the daily administration of criminal justice in the age of big data.  

Authors

• Sarah Brayne, University of Texas-Austin

• Angele Christin, Data & Society Research Institute