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“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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Detalles Bibliográficos
Autores principales: Adensamer, Angelika, Klausner, Lukas Daniel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8269447/
https://www.ncbi.nlm.nih.gov/pubmed/34250464
http://dx.doi.org/10.3389/frai.2021.655486
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author Adensamer, Angelika
Klausner, Lukas Daniel
author_facet Adensamer, Angelika
Klausner, Lukas Daniel
author_sort Adensamer, Angelika
collection PubMed
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 pubmed-82694472021-07-10 “Part Man, Part Machine, All Cop”: Automation in Policing Adensamer, Angelika Klausner, Lukas Daniel Front Artif Intell Artificial Intelligence 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. Frontiers Media S.A. 2021-06-23 /pmc/articles/PMC8269447/ /pubmed/34250464 http://dx.doi.org/10.3389/frai.2021.655486 Text en Copyright © 2021 Adensamer and Klausner. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Artificial Intelligence
Adensamer, Angelika
Klausner, Lukas Daniel
“Part Man, Part Machine, All Cop”: Automation in 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 Artificial Intelligence
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8269447/
https://www.ncbi.nlm.nih.gov/pubmed/34250464
http://dx.doi.org/10.3389/frai.2021.655486
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