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

Ethics and Information Technology 21 (3):197-208 (2019)

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.
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DOI 10.1007/s10676-019-09502-5
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References found in this work BETA

From Individual to Group Privacy in Big Data Analytics.Brent Mittelstadt - 2017 - Philosophy and Technology 30 (4):475-494.
Privacy Exchanges: Restoring Consent in Privacy Self-Management.Mario Pascalev - 2017 - Ethics and Information Technology 19 (1):39-48.
The Human Use of Human Beings.Norbert Wiener - 1952 - British Journal for the Philosophy of Science 3 (9):91-92.

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