“Part Man, Part Machine, All Cop”: Automation in Policing

Digitisation, automation, and datafication permeate policing and justice more and more each year—from predictive policing methods through recidivism prediction to automated biometric identification at the border. The sociotechnical issues surrounding the use of such systems raise questions and revea...

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Main Authors: Angelika Adensamer, Lukas Daniel Klausner
Format: Article
Language:English
Published: Frontiers Media S.A. 2021-06-01
Series:Frontiers in Artificial Intelligence
Subjects:
Online Access:https://www.frontiersin.org/articles/10.3389/frai.2021.655486/full
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author Angelika Adensamer
Lukas Daniel Klausner
author_facet Angelika Adensamer
Lukas Daniel Klausner
author_sort Angelika Adensamer
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description Digitisation, automation, and datafication permeate policing and justice more and more each year—from predictive policing methods through recidivism prediction to automated biometric identification at the border. The sociotechnical issues surrounding the use of such systems raise questions and reveal problems, both old and new. Our article reviews contemporary issues surrounding automation in policing and the legal system, finds common issues and themes in various different examples, introduces the distinction between human “retail bias” and algorithmic “wholesale bias”, and argues for shifting the viewpoint on the debate to focus on both workers' rights and organisational responsibility as well as fundamental rights and the right to an effective remedy.
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spelling doaj.art-610790e1ce7a46a28e176d22de30dd602022-12-21T21:59:05ZengFrontiers Media S.A.Frontiers in Artificial Intelligence2624-82122021-06-01410.3389/frai.2021.655486655486“Part Man, Part Machine, All Cop”: Automation in PolicingAngelika Adensamer0Lukas Daniel Klausner1Vienna Centre for Societal Security, Vienna, AustriaInstitute of IT Security Research, St. Pölten University of Applied Sciences, St. Pölten, AustriaDigitisation, automation, and datafication permeate policing and justice more and more each year—from predictive policing methods through recidivism prediction to automated biometric identification at the border. The sociotechnical issues surrounding the use of such systems raise questions and reveal problems, both old and new. Our article reviews contemporary issues surrounding automation in policing and the legal system, finds common issues and themes in various different examples, introduces the distinction between human “retail bias” and algorithmic “wholesale bias”, and argues for shifting the viewpoint on the debate to focus on both workers' rights and organisational responsibility as well as fundamental rights and the right to an effective remedy.https://www.frontiersin.org/articles/10.3389/frai.2021.655486/fullalgorithmic decision supportautomated decision-makingbiometric identificationfacial recognitionorganisational responsibilitypredictive policing
spellingShingle Angelika Adensamer
Lukas Daniel Klausner
“Part Man, Part Machine, All Cop”: Automation in Policing
Frontiers in Artificial Intelligence
algorithmic decision support
automated decision-making
biometric identification
facial recognition
organisational responsibility
predictive policing
title “Part Man, Part Machine, All Cop”: Automation in Policing
title_full “Part Man, Part Machine, All Cop”: Automation in Policing
title_fullStr “Part Man, Part Machine, All Cop”: Automation in Policing
title_full_unstemmed “Part Man, Part Machine, All Cop”: Automation in Policing
title_short “Part Man, Part Machine, All Cop”: Automation in Policing
title_sort part man part machine all cop automation in policing
topic algorithmic decision support
automated decision-making
biometric identification
facial recognition
organisational responsibility
predictive policing
url https://www.frontiersin.org/articles/10.3389/frai.2021.655486/full
work_keys_str_mv AT angelikaadensamer partmanpartmachineallcopautomationinpolicing
AT lukasdanielklausner partmanpartmachineallcopautomationinpolicing