Ethical Issues in Social Science Research Employing Big Data

Author:

Hosseini MohammadORCID,Wieczorek MichałORCID,Gordijn BertORCID

Abstract

AbstractThis paper analyzes the ethics of social science research (SSR) employing big data. We begin by highlighting the research gap found on the intersection between big data ethics, SSR and research ethics. We then discuss three aspects of big data SSR which make it warrant special attention from a research ethics angle: (1) the interpretative character of both SSR and big data, (2) complexities of anticipating and managing risks in publication and reuse of big data SSR, and (3) the paucity of regulatory oversight and ethical recommendations on protecting individual subjects as well as societies when conducting big data SSR. Against this backdrop, we propose using David Resnik’s research ethics framework to analyze some of the most pressing ethical issues of big data SSR. Focusing on the principles of honesty, carefulness, openness, efficiency, respect for subjects, and social responsibility, we discuss three clusters of ethical issues: those related to methodological biases and personal prejudices, those connected to risks arising from data availability and reuse, and those leading to individual and social harms. Finally, we advance considerations to observe in developing future ethical guidelines about big data SSR.

Funder

Horizon 2020 Research and Innovation Programme

H2020 Marie Skłodowska-Curie Actions

Northwestern University Clinical and Translational Sciences Institute

Publisher

Springer Science and Business Media LLC

Subject

Management of Technology and Innovation,Health Policy,Issues, ethics and legal aspects,Health (social science)

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