Diversity in Big Data: A Review

Marina Drosou; H. V. Jagadish; Evaggelia Pitoura; Julia Stoyanovich

doi:10.1089/big.2016.0054

Diversity in Big Data: A Review

Marina Drosou, H. V. Jagadish, Evaggelia Pitoura, Julia Stoyanovich

Research output: Contribution to journal › Review article › peer-review

Abstract

Big data technology offers unprecedented opportunities to society as a whole and also to its individual members. At the same time, this technology poses significant risks to those it overlooks. In this article, we give an overview of recent technical work on diversity, particularly in selection tasks, discuss connections between diversity and fairness, and identify promising directions for future work that will position diversity as an important component of a data-responsible society. We argue that diversity should come to the forefront of our discourse, for reasons that are both ethical - to mitigate the risks of exclusion - and utilitarian, to enable more powerful, accurate, and engaging data analysis and use.

Original language	English (US)
Pages (from-to)	73-84
Number of pages	12
Journal	Big Data
Volume	5
Issue number	2
DOIs	https://doi.org/10.1089/big.2016.0054
State	Published - Jun 2017

Keywords

data
diversity
empirical studies
models and algorithms
responsibly

ASJC Scopus subject areas

Information Systems
Computer Science Applications
Information Systems and Management

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10.1089/big.2016.0054

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abstract = "Big data technology offers unprecedented opportunities to society as a whole and also to its individual members. At the same time, this technology poses significant risks to those it overlooks. In this article, we give an overview of recent technical work on diversity, particularly in selection tasks, discuss connections between diversity and fairness, and identify promising directions for future work that will position diversity as an important component of a data-responsible society. We argue that diversity should come to the forefront of our discourse, for reasons that are both ethical - to mitigate the risks of exclusion - and utilitarian, to enable more powerful, accurate, and engaging data analysis and use.",

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Diversity in Big Data: A Review

Abstract

Keywords

ASJC Scopus subject areas

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