Transparency, Fairness, Data Protection, Neutrality

S. Abiteboul, Julia Stoyanovich
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引用次数: 30

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.
透明、公平、数据保护、中立
数据革命继续改变着科学、工业和政府的各个部门。由于数据驱动的技术对社会的巨大影响,我们越来越意识到根据法律和道德规范负责任地使用数据和算法的必要性。在本文中,我们将讨论三个最新的监管框架:欧盟的《通用数据保护条例》(GDPR)、纽约市自动决策系统法(ADS)和网络中立原则,旨在保护受数据收集和分析影响的个人的权利。这些框架是全球趋势的突出例子:各国政府开始认识到需要规范数据驱动的算法技术。我们在本文中的目标是让数据管理社区注意到这些监管框架,并强调它们带来的技术挑战,而我们作为一个社区,有能力解决这些挑战。本文的主要结论是,法律和道德规范不能作为事后的想法纳入数据驱动的系统。相反,我们必须根据设计的责任来考虑,将其视为系统需求。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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