RT Article
T1 Big data surveillance: the case of policing
JF American sociological review
VO 82
IS 5
SP 977
OP 1008
A1 Brayne, Sarah
LA English
YR 2017
UL https://krimdok.uni-tuebingen.de/Record/1567274374
AB This article examines the intersection of two structural developments: the growth of surveillance and the rise of “big data.” Drawing on observations and interviews conducted within the Los Angeles Police Department, I offer an empirical account of how the adoption of big data analytics does—and does not—transform police surveillance practices. I argue that the adoption of big data analytics facilitates amplifications of prior surveillance practices and fundamental transformations in surveillance activities. First, discretionary assessments of risk are supplemented and quantified using risk scores. Second, data are used for predictive, rather than reactive or explanatory, purposes. Third, the proliferation of automatic alert systems makes it possible to systematically surveil an unprecedentedly large number of people. Fourth, the threshold for inclusion in law enforcement databases is lower, now including individuals who have not had direct police contact. Fifth, previously separate data systems are merged, facilitating the spread of surveillance into a wide range of institutions. Based on these findings, I develop a theoretical model of big data surveillance that can be applied to institutional domains beyond the criminal justice system. Finally, I highlight the social consequences of big data surveillance for law and social inequality.
K1 Police
K1 Big data
K1 Inequaltiy
K1 Crime
K1 Law
K1 Polizei
K1 Überwachungstechnologien
K1 Soziale Ungleichheit
DO 10.1177/0003122417725865