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Big Data and Democracy$
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Kevin Macnish and Jai Galliott

Print publication date: 2020

Print ISBN-13: 9781474463522

Published to Edinburgh Scholarship Online: September 2021

DOI: 10.3366/edinburgh/9781474463522.001.0001

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PRINTED FROM EDINBURGH SCHOLARSHIP ONLINE (www.edinburgh.universitypressscholarship.com). (c) Copyright Edinburgh University Press, 2021. All Rights Reserved. An individual user may print out a PDF of a single chapter of a monograph in ESO for personal use.date: 29 November 2021

Trust and Algorithmic Opacity

Trust and Algorithmic Opacity

Chapter:
(p.153) Ten Trust and Algorithmic Opacity
Source:
Big Data and Democracy
Author(s):

Steve McKinlay

Publisher:
Edinburgh University Press
DOI:10.3366/edinburgh/9781474463522.003.0011

In this chapter, McKinlay argues that the use of big data algorithms introduces a key problem in terms of epistemic opacity. Opacity in various forms is an issue which many authors identify as posing problems for democratic functioning and accountability. In McKinlay’s case, the argument focuses on the impact that epistemic opacity has on our ability to trust non-human agents. He holds that while the outputs of big data-derived decisions can be significant for citizens, where we do not have the ability to understand how these decisions were made, we cannot ultimately trust the decider. Decisions based on mere probability are not, he argues, sufficiently grounded for democratic systems and risk harming citizens.

Keywords:   Accountability, Agency, Algorithm, Opacity, Transparency, Trust

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