Data science ethical considerations: a systematic literature review and proposed project framework

Jeffrey Saltz, Neil Dewar

Research output: Contribution to journalArticle

3 Scopus citations

Abstract

Data science, and the related field of big data, is an emerging discipline involving the analysis of data to solve problems and develop insights. This rapidly growing domain promises many benefits to both consumers and businesses. However, the use of big data analytics can also introduce many ethical concerns, stemming from, for example, the possible loss of privacy or the harming of a sub-category of the population via a classification algorithm. To help address these potential ethical challenges, this paper maps and describes the main ethical themes that were identified via systematic literature review. It then identifies a possible structure to integrate these themes within a data science project, thus helping to provide some structure in the on-going debate with respect to the possible ethical situations that can arise when using data science analytics.

Original languageEnglish (US)
JournalEthics and Information Technology
DOIs
StatePublished - Jan 1 2019

Keywords

  • Big data
  • Code of conduct
  • Data science
  • Ethics

ASJC Scopus subject areas

  • Computer Science Applications
  • Library and Information Sciences

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