Transparency, Fairness, Data Protection, Neutrality: Data Management Challenges in the Face of New Regulation
March 08, 2019 Β· Declared Dead Β· π ACM Journal of Data and Information Quality
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Authors
Serge Abiteboul, Julia Stoyanovich
arXiv ID
1903.03683
Category
cs.DB: Databases
Cross-listed
cs.CY
Citations
33
Venue
ACM Journal of Data and Information Quality
Last Checked
6 months ago
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, that 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 paper is to bring these regulatory frameworks to the attention of the data management community, and to underscore the technical challenges they raise and which we, as a community, are well-equipped to address. The main take-away 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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