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Criminal Prohibition of Wrongful Re‑identification: Legal Solution or Minefield for Big Data?
The collapse of confidence in anonymization (sometimes also known as de-identification) as a robust approach for preserving the privacy of personal data has incited an outpouring of new approaches that aim to fill the resulting trifecta of technical, organizational, and regulatory privacy gaps left...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Netherlands
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5715031/ https://www.ncbi.nlm.nih.gov/pubmed/28913771 http://dx.doi.org/10.1007/s11673-017-9806-9 |
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author | Phillips, Mark Dove, Edward S. Knoppers, Bartha M. |
author_facet | Phillips, Mark Dove, Edward S. Knoppers, Bartha M. |
author_sort | Phillips, Mark |
collection | PubMed |
description | The collapse of confidence in anonymization (sometimes also known as de-identification) as a robust approach for preserving the privacy of personal data has incited an outpouring of new approaches that aim to fill the resulting trifecta of technical, organizational, and regulatory privacy gaps left in its wake. In the latter category, and in large part due to the growth of Big Data–driven biomedical research, falls a growing chorus of calls for criminal and penal offences to sanction wrongful re-identification of “anonymized” data. This chorus cuts across the fault lines of polarized privacy law scholarship that at times seems to advocate privacy protection at the expense of Big Data research or vice versa. Focusing on Big Data in the context of biomedicine, this article surveys the approaches that criminal or penal law might take toward wrongful re-identification of health data. It contextualizes the strategies within their respective legal regimes as well as in relation to emerging privacy debates focusing on personal data use and data linkage and assesses the relative merit of criminalization. We conclude that this approach suffers from several flaws and that alternative social and legal strategies to deter wrongful re-identification may be preferable. |
format | Online Article Text |
id | pubmed-5715031 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Springer Netherlands |
record_format | MEDLINE/PubMed |
spelling | pubmed-57150312017-12-11 Criminal Prohibition of Wrongful Re‑identification: Legal Solution or Minefield for Big Data? Phillips, Mark Dove, Edward S. Knoppers, Bartha M. J Bioeth Inq Symposium: Ethics and Epistemology of Big Data The collapse of confidence in anonymization (sometimes also known as de-identification) as a robust approach for preserving the privacy of personal data has incited an outpouring of new approaches that aim to fill the resulting trifecta of technical, organizational, and regulatory privacy gaps left in its wake. In the latter category, and in large part due to the growth of Big Data–driven biomedical research, falls a growing chorus of calls for criminal and penal offences to sanction wrongful re-identification of “anonymized” data. This chorus cuts across the fault lines of polarized privacy law scholarship that at times seems to advocate privacy protection at the expense of Big Data research or vice versa. Focusing on Big Data in the context of biomedicine, this article surveys the approaches that criminal or penal law might take toward wrongful re-identification of health data. It contextualizes the strategies within their respective legal regimes as well as in relation to emerging privacy debates focusing on personal data use and data linkage and assesses the relative merit of criminalization. We conclude that this approach suffers from several flaws and that alternative social and legal strategies to deter wrongful re-identification may be preferable. Springer Netherlands 2017-09-14 2017 /pmc/articles/PMC5715031/ /pubmed/28913771 http://dx.doi.org/10.1007/s11673-017-9806-9 Text en © The Author(s) 2017 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
spellingShingle | Symposium: Ethics and Epistemology of Big Data Phillips, Mark Dove, Edward S. Knoppers, Bartha M. Criminal Prohibition of Wrongful Re‑identification: Legal Solution or Minefield for Big Data? |
title | Criminal Prohibition of Wrongful Re‑identification: Legal Solution or Minefield for Big Data? |
title_full | Criminal Prohibition of Wrongful Re‑identification: Legal Solution or Minefield for Big Data? |
title_fullStr | Criminal Prohibition of Wrongful Re‑identification: Legal Solution or Minefield for Big Data? |
title_full_unstemmed | Criminal Prohibition of Wrongful Re‑identification: Legal Solution or Minefield for Big Data? |
title_short | Criminal Prohibition of Wrongful Re‑identification: Legal Solution or Minefield for Big Data? |
title_sort | criminal prohibition of wrongful re‑identification: legal solution or minefield for big data? |
topic | Symposium: Ethics and Epistemology of Big Data |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5715031/ https://www.ncbi.nlm.nih.gov/pubmed/28913771 http://dx.doi.org/10.1007/s11673-017-9806-9 |
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