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Algorithmic Regulation$
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Karen Yeung and Martin Lodge

Print publication date: 2019

Print ISBN-13: 9780198838494

Published to Oxford Scholarship Online: October 2019

DOI: 10.1093/oso/9780198838494.001.0001

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PRINTED FROM OXFORD SCHOLARSHIP ONLINE (oxford.universitypressscholarship.com). (c) Copyright Oxford University Press, 2021. All Rights Reserved. An individual user may print out a PDF of a single chapter of a monograph in OSO for personal use. date: 20 September 2021

Reflecting on Public Service Regulation by Algorithm

Reflecting on Public Service Regulation by Algorithm

Chapter:
(p.178) 8 Reflecting on Public Service Regulation by Algorithm
Source:
Algorithmic Regulation
Author(s):

Martin Lodge

Andrea Mennicken

Publisher:
Oxford University Press
DOI:10.1093/oso/9780198838494.003.0008

This chapter focuses on the potentials and challenges posed by the utilization of machine learning algorithms in the regulation of public services, that is services supplied by or on behalf of government to a particular jurisdiction’s community, including healthcare, education, or correctional services. It argues that the widespread enthusiasm for algorithmic regulation hides much deeper differences in worldviews about regulatory approaches, and that advancing the utilization of algorithmic regulation potentially transforms existing mixes of regulatory approaches in non-anticipated ways. It also argues that regulating through algorithmic regulation presents distinct administrative problems in terms of knowledge creation, coordination, and integration, as well as ambiguity over objectives. These challenges for the use of machine learning algorithms in public service algorithmic regulation require renewed attention to questions of the ‘regulation of regulators’.

Keywords:   machine learning, algorithms, public services, algorithmic regulation, public service regulation

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