Data Experts as the Balancing Power of Big Data Ethics

In this theoretical paper, we explore Big Data ethics in the broader context of general data ethics, stakeholder groups, demand for governance and regulation, social norms, and human values. We follow and expand on the digital divide, governance, and regulatory theories, and we apply them to many le...

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Main Authors: Richard Novak, Antonin Pavlicek
Format: Article
Language:English
Published: MDPI AG 2021-02-01
Series:Information
Subjects:
Online Access:https://www.mdpi.com/2078-2489/12/3/97
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author Richard Novak
Antonin Pavlicek
author_facet Richard Novak
Antonin Pavlicek
author_sort Richard Novak
collection DOAJ
description In this theoretical paper, we explore Big Data ethics in the broader context of general data ethics, stakeholder groups, demand for governance and regulation, social norms, and human values. We follow and expand on the digital divide, governance, and regulatory theories, and we apply them to many levels and contexts, such as state and society, organization, enterprise governance of IT (EGIT), and data projects, among others. We introduce the new role and responsibility of data experts as an important stakeholder group in the balance of power of Big Data ethics because they simultaneously hold a position in groups of data-rich organizations and data-poor users. We argue that the balancing role of data experts consists of motivation and competence, a sense of responsibility for data ethics, and the possibility and means to influence Big Data issues. Finally, we conclude our research by model mapping the role of data experts in Big Data ethics and proposing them as a balancing power.
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spelling doaj.art-473c27dd70fe4c25af25762f464f93782023-12-11T18:19:29ZengMDPI AGInformation2078-24892021-02-011239710.3390/info12030097Data Experts as the Balancing Power of Big Data EthicsRichard Novak0Antonin Pavlicek1Department of Systems Analysis, Faculty of Informatics and Statistics, Prague University of Economics and Business, 130 67 Prague, Czech RepublicDepartment of Systems Analysis, Faculty of Informatics and Statistics, Prague University of Economics and Business, 130 67 Prague, Czech RepublicIn this theoretical paper, we explore Big Data ethics in the broader context of general data ethics, stakeholder groups, demand for governance and regulation, social norms, and human values. We follow and expand on the digital divide, governance, and regulatory theories, and we apply them to many levels and contexts, such as state and society, organization, enterprise governance of IT (EGIT), and data projects, among others. We introduce the new role and responsibility of data experts as an important stakeholder group in the balance of power of Big Data ethics because they simultaneously hold a position in groups of data-rich organizations and data-poor users. We argue that the balancing role of data experts consists of motivation and competence, a sense of responsibility for data ethics, and the possibility and means to influence Big Data issues. Finally, we conclude our research by model mapping the role of data experts in Big Data ethics and proposing them as a balancing power.https://www.mdpi.com/2078-2489/12/3/97big data ethicsbalancing powerdata expertsdata-richdata-poorgovernance
spellingShingle Richard Novak
Antonin Pavlicek
Data Experts as the Balancing Power of Big Data Ethics
Information
big data ethics
balancing power
data experts
data-rich
data-poor
governance
title Data Experts as the Balancing Power of Big Data Ethics
title_full Data Experts as the Balancing Power of Big Data Ethics
title_fullStr Data Experts as the Balancing Power of Big Data Ethics
title_full_unstemmed Data Experts as the Balancing Power of Big Data Ethics
title_short Data Experts as the Balancing Power of Big Data Ethics
title_sort data experts as the balancing power of big data ethics
topic big data ethics
balancing power
data experts
data-rich
data-poor
governance
url https://www.mdpi.com/2078-2489/12/3/97
work_keys_str_mv AT richardnovak dataexpertsasthebalancingpowerofbigdataethics
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