Science and Engineering Ethics

, Volume 22, Issue 2, pp 303–341 | Cite as

The Ethics of Big Data: Current and Foreseeable Issues in Biomedical Contexts

  • Brent Daniel MittelstadtEmail author
  • Luciano Floridi
Review Paper


The capacity to collect and analyse data is growing exponentially. Referred to as ‘Big Data’, this scientific, social and technological trend has helped create destabilising amounts of information, which can challenge accepted social and ethical norms. Big Data remains a fuzzy idea, emerging across social, scientific, and business contexts sometimes seemingly related only by the gigantic size of the datasets being considered. As is often the case with the cutting edge of scientific and technological progress, understanding of the ethical implications of Big Data lags behind. In order to bridge such a gap, this article systematically and comprehensively analyses academic literature concerning the ethical implications of Big Data, providing a watershed for future ethical investigations and regulations. Particular attention is paid to biomedical Big Data due to the inherent sensitivity of medical information. By means of a meta-analysis of the literature, a thematic narrative is provided to guide ethicists, data scientists, regulators and other stakeholders through what is already known or hypothesised about the ethical risks of this emerging and innovative phenomenon. Five key areas of concern are identified: (1) informed consent, (2) privacy (including anonymisation and data protection), (3) ownership, (4) epistemology and objectivity, and (5) ‘Big Data Divides’ created between those who have or lack the necessary resources to analyse increasingly large datasets. Critical gaps in the treatment of these themes are identified with suggestions for future research. Six additional areas of concern are then suggested which, although related have not yet attracted extensive debate in the existing literature. It is argued that they will require much closer scrutiny in the immediate future: (6) the dangers of ignoring group-level ethical harms; (7) the importance of epistemology in assessing the ethics of Big Data; (8) the changing nature of fiduciary relationships that become increasingly data saturated; (9) the need to distinguish between ‘academic’ and ‘commercial’ Big Data practices in terms of potential harm to data subjects; (10) future problems with ownership of intellectual property generated from analysis of aggregated datasets; and (11) the difficulty of providing meaningful access rights to individual data subjects that lack necessary resources. Considered together, these eleven themes provide a thorough critical framework to guide ethical assessment and governance of emerging Big Data practices.


Ethics Big data Bioethics Information ethics Medical ethics Ethical foresight 



The research leading to this work has been funded by a <removed for anonymity> major research grant. An initial version of this paper was discussed at a workshop organised at the <removed for anonymity> on <removed for anonymity>. We wish to acknowledge the extremely valuable feedback received during that meeting and from the two anonymous reviewers. This study was funded by the University of Oxford’s John Fell Fund.

Conflict of interest

The authors declare that they have no conflict of interest.


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© Springer Science+Business Media Dordrecht 2015

Authors and Affiliations

  1. 1.Oxford Internet InstituteUniversity of OxfordOxfordUK

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