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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: 24 January 2022

Opacity, Big Data, Artificial Intelligence and Machine Learning in Democratic Processes

Opacity, Big Data, Artificial Intelligence and Machine Learning in Democratic Processes

Chapter:
(p.167) Eleven Opacity, Big Data, Artificial Intelligence and Machine Learning in Democratic Processes
Source:
Big Data and Democracy
Author(s):

Ramón Alvarado

Publisher:
Edinburgh University Press
DOI:10.3366/edinburgh/9781474463522.003.0012

Alvarado provides a detailed examination of different kinds of opacity in algorithms, raising the problems of “many hands” (where to attribute responsibility in complex systems), error assessment, and path complexity. In the process, he offers the reader a demystified understanding of how big data computational methods function and suggests ways in which opacity threatens fundamental elements of the democratic process.

Keywords:   Algorithm, Error Assessment, Many Hands, Path Complexity, Opacity, Trust

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