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Transparency, Fairness, Data Protection, Neutrality: Data Management Challenges in the Face of New Regulation

Authors:

Serge Abiteboul,

Julia StoyanovichAuthors Info & Claims

Journal of Data and Information Quality (JDIQ), Volume 11, Issue 3

Article No.: 15, Pages 1 - 9

https://doi.org/10.1145/3310231

Published: 26 June 2019 Publication History

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Abstract

The data revolution continues to transform every sector of science, industry, and government. Due to the incredible impact of data-driven technology on society, we are becoming increasingly aware of the imperative to use data and algorithms responsibly—in accordance with laws and ethical norms. In this article, we discuss three recent regulatory frameworks: the European Union’s General Data Protection Regulation (GDPR), the New York City Automated Decisions Systems (ADS) Law, and the Net Neutrality principle, which aim to protect the rights of individuals who are impacted by data collection and analysis. These frameworks are prominent examples of a global trend: Governments are starting to recognize the need to regulate data-driven algorithmic technology.

Our goal in this article is to bring these regulatory frameworks to the attention of the data management community and to underscore the technical challenges they raise and that we, as a community, are well-equipped to address. The main takeaway of this article is that legal and ethical norms cannot be incorporated into data-driven systems as an afterthought. Rather, we must think in terms of responsibility by design, viewing it as a systems requirement.

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Transparency, Fairness, Data Protection, Neutrality: Data Management Challenges in the Face of New Regulation

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Information & Contributors

Information

Published In

cover image Journal of Data and Information Quality

Journal of Data and Information Quality Volume 11, Issue 3

Special Issue on Combating Digital Misinformation and Disinformation and On the Horizon

September 2019

160 pages

ISSN:1936-1955

EISSN:1936-1963

DOI:10.1145/3331015

Editor:
Tiziana Catarci
Sapienza University of Rome, Rome, Italy

Issue’s Table of Contents

Copyright © 2019 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 26 June 2019

Accepted: 01 December 2018

Received: 01 December 2018

Published in JDIQ Volume 11, Issue 3

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Shah SPeristeras VMagnisalis I(2024)A CONCEPTUAL FRAMEWORK FOR THE GOVERNMENT BIG DATA ECOSYSTEM (‘datagov.eco’)Data & Knowledge Engineering10.1016/j.datak.2024.102348(102348)Online publication date: Sep-2024
https://doi.org/10.1016/j.datak.2024.102348
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https://doi.org/10.1016/j.cola.2024.101299
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