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      Technologies of Crime Prediction: The Reception of Algorithms in Policing and Criminal Courts

      1 , 2
      Social Problems
      Oxford University Press (OUP)

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          Abstract

          The number of predictive technologies used in the U.S. criminal justice system is on the rise. Yet there is little research to date on the reception of algorithms in criminal justice institutions. We draw on ethnographic fieldwork conducted within a large urban police department and a midsized criminal court to assess the impact of predictive technologies at different stages of the criminal justice process. We first show that similar arguments are mobilized to justify the adoption of predictive algorithms in law enforcement and criminal courts. In both cases, algorithms are described as more objective and efficient than humans’ discretionary judgment. We then study how predictive algorithms are used, documenting similar processes of professional resistance among law enforcement and legal professionals. In both cases, resentment toward predictive algorithms is fueled by fears of deskilling and heightened managerial surveillance. Two practical strategies of resistance emerge: foot-dragging and data obfuscation. We conclude by discussing how predictive technologies do not replace, but rather displace discretion to less visible—and therefore less accountable—areas within organizations, a shift which has important implications for inequality and the administration of justice in the age of big data.

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          THE NEW PENOLOGY: NOTES ON THE EMERGING STRATEGY OF CORRECTIONS AND ITS IMPLICATIONS*

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            The spreading of disorder.

            Imagine that the neighborhood you are living in is covered with graffiti, litter, and unreturned shopping carts. Would this reality cause you to litter more, trespass, or even steal? A thesis known as the broken windows theory suggests that signs of disorderly and petty criminal behavior trigger more disorderly and petty criminal behavior, thus causing the behavior to spread. This may cause neighborhoods to decay and the quality of life of its inhabitants to deteriorate. For a city government, this may be a vital policy issue. But does disorder really spread in neighborhoods? So far there has not been strong empirical support, and it is not clear what constitutes disorder and what may make it spread. We generated hypotheses about the spread of disorder and tested them in six field experiments. We found that, when people observe that others violated a certain social norm or legitimate rule, they are more likely to violate other norms or rules, which causes disorder to spread.
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              Big Data Surveillance: The Case of Policing

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                Author and article information

                Journal
                Social Problems
                Oxford University Press (OUP)
                0037-7791
                1533-8533
                March 05 2020
                March 05 2020
                Affiliations
                [1 ]University of Texas at Austin
                [2 ]Stanford University
                Article
                10.1093/socpro/spaa004
                972c51e7-7522-4045-99b9-097a6f8c9139
                © 2020

                https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model

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