“Strictly Biomedical? Sketching the Ethics of the Big Data Ecosystem in Biomedicine”

Effy Vayena, Urs Gasser

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

21 Scopus citations

Abstract

In today’s ever evolving data ecosystem it is evident that data generated for a wide range of purposes unrelated to biomedicine possess tremendous potential value for biomedical research. Analyses of our Google searches, social media content, loyalty card points and the like are used to draw a fairly accurate picture of our health, our future health, our attitudes towards vaccination, disease outbreaks within a county and epidemic trajectories in other continents. These data sets are different from traditional biomedical data, if a biomedical purpose is the categorical variable. Yet the results their analyses yield are of serious biomedical relevance. This paper discusses important but unresolved challenges within typical biomedical data, and it explores examples of non-biomedical Big Data with high biomedical value, including the specific conundrums these engender, especially when we apply biomedical data concepts to them. It also highlights the “digital phenotype” project, illustrating the Big Data ecosystem in action and an approach believed as likely to yield biomedical and health knowledge. We argue that to address the challenges and make full use of the opportunities that Big Data offers to biomedicine, a new ethical framework taking a data ecosystem approach is urgently needed. We conclude by discussing key components, design requirements and substantive normative elements of such a framework.

Original languageEnglish
Title of host publicationLaw, Governance and Technology Series
PublisherSpringer Science and Business Media B.V.
Pages17-39
Number of pages23
DOIs
StatePublished - 2016
Externally publishedYes

Publication series

NameLaw, Governance and Technology Series
Volume29
ISSN (Print)2352-1902
ISSN (Electronic)2352-1910

Keywords

  • Biomedical Data
  • Ethical Framework
  • Mobile Phone Data
  • Personal Health Information
  • Privacy Risk

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