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  • 1
    Online Resource
    Online Resource
    New York, NY : Oxford University Press
    UID:
    gbv_1750832437
    Format: 1 Online-Ressource (ix, 210 Seiten)
    ISBN: 9780190684129 , 9780190684112
    Series Statement: Oxford scholarship online
    Content: "The scope of criminal justice surveillance, from the police to the prisons, has expanded rapidly in recent decades. At the same time, the use of big data has spread across a range of fields, including finance, politics, health, and marketing. While law enforcement's use of big data is hotly contested, very little is known about how the police actually use it in daily operations and with what consequences. This book offers an inside look at how police use big data and new surveillance technologies, leveraging on-the-ground fieldwork with one of the most technologically advanced law enforcement agencies in the world-the Los Angeles Police Department. Drawing on original interviews and ethnographic observations from over two years of fieldwork with the LAPD, the text examines the causes and consequences of big data and algorithmic control. It reveals how the police use predictive analytics and new surveillance technologies to deploy resources, identify criminal suspects, and conduct investigations; how the adoption of big data analytics transforms police organizational practices; and how the police themselves respond to these new data-driven practices. While big data analytics has the potential to reduce bias, increase efficiency, and improve prediction accuracy, the book argues that it also reproduces and deepens existing patterns of inequality, threatens privacy, and challenges civil liberties"--
    Additional Edition: ISBN 9780190684099
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 9780190684099
    Additional Edition: Erscheint auch als Druck-Ausgabe Brayne, Sarah Predict and surveil New York, NY : Oxford University Press, 2021 ISBN 9780190684099
    Language: English
    Keywords: Los Angeles, Calif. Police Department ; Strafverfolgung ; Big Data ; Täterprofil ; Analyse ; Privatsphäre
    URL: Volltext  (lizenzpflichtig)
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