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EDBT
2016
ACM

Data Responsibly: Fairness, Neutrality and Transparency in Data Analysis

3 years 21 days ago
Data Responsibly: Fairness, Neutrality and Transparency in Data Analysis
Big data technology holds incredible promise of improving people’s lives, accelerating scientific discovery and innovation, and bringing about positive societal change. Yet, if not used responsibly, this technology can propel economic inequality, destabilize global markets and affirm systemic bias. While the potential benefits of big data are well-accepted, the importance of using these techniques in a fair and transparent manner is rarely considered. The primary goal of this tutorial is to draw the attention of the data management community to the important emerging subject of responsible data management and analysis. We will offer our perspective on the issue, will give an overview of existing technical work, primarily from the data mining and algorithms communities, and will motivate future research directions.
Julia Stoyanovich, Serge Abiteboul, Gerome Miklau
Added 02 Apr 2016
Updated 02 Apr 2016
Type Journal
Year 2016
Where EDBT
Authors Julia Stoyanovich, Serge Abiteboul, Gerome Miklau
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