Cargando…
Genetic data are not always personal—disaggregating the identifiability and sensitivity of genetic data
In both the EU and USA, genetic data are recognized as a special category of data that requires heightened privacy protection. Identifiability and sensitivity are central pillars of the regulatory framework in both jurisdictions: the privacy concerns stem from the assumption that genetic data are ca...
Autor principal: | |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10676748/ https://www.ncbi.nlm.nih.gov/pubmed/38023689 http://dx.doi.org/10.1093/jlb/lsad029 |
_version_ | 1785141351523811328 |
---|---|
author | Rahnasto, Johanna |
author_facet | Rahnasto, Johanna |
author_sort | Rahnasto, Johanna |
collection | PubMed |
description | In both the EU and USA, genetic data are recognized as a special category of data that requires heightened privacy protection. Identifiability and sensitivity are central pillars of the regulatory framework in both jurisdictions: the privacy concerns stem from the assumption that genetic data are capable of identifying the individual and reveals sensitive information about them. But not all genetic data are identifiable and sensitive, nor are genetic data necessarily different from other types of big data in terms of these issues. This article argues that a more nuanced approach is needed to assess the threat to privacy interests posed by uses of genetic data. The privacy interests involved should be distinguished in terms of proposed use, the amount of data in question, and its uniqueness and informational content. When these factors are disaggregated, it is clear that both regulatory schemes could better achieve their goals by focusing more on the ways genetic data can be used rather than on their status as a special category of data. |
format | Online Article Text |
id | pubmed-10676748 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-106767482023-07-24 Genetic data are not always personal—disaggregating the identifiability and sensitivity of genetic data Rahnasto, Johanna J Law Biosci Original Article In both the EU and USA, genetic data are recognized as a special category of data that requires heightened privacy protection. Identifiability and sensitivity are central pillars of the regulatory framework in both jurisdictions: the privacy concerns stem from the assumption that genetic data are capable of identifying the individual and reveals sensitive information about them. But not all genetic data are identifiable and sensitive, nor are genetic data necessarily different from other types of big data in terms of these issues. This article argues that a more nuanced approach is needed to assess the threat to privacy interests posed by uses of genetic data. The privacy interests involved should be distinguished in terms of proposed use, the amount of data in question, and its uniqueness and informational content. When these factors are disaggregated, it is clear that both regulatory schemes could better achieve their goals by focusing more on the ways genetic data can be used rather than on their status as a special category of data. Oxford University Press 2023-07-24 /pmc/articles/PMC10676748/ /pubmed/38023689 http://dx.doi.org/10.1093/jlb/lsad029 Text en © The Author(s) 2023. Published by Oxford University Press on behalf of Duke University School of Law, Harvard Law School, Oxford University Press, and Stanford Law School. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution NonCommercial-NoDerivs licence (https://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial reproduction and distribution of the work, in any medium, provided the original work is not altered or transformed in any way, and that the work properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Original Article Rahnasto, Johanna Genetic data are not always personal—disaggregating the identifiability and sensitivity of genetic data |
title | Genetic data are not always personal—disaggregating the identifiability and sensitivity of genetic data |
title_full | Genetic data are not always personal—disaggregating the identifiability and sensitivity of genetic data |
title_fullStr | Genetic data are not always personal—disaggregating the identifiability and sensitivity of genetic data |
title_full_unstemmed | Genetic data are not always personal—disaggregating the identifiability and sensitivity of genetic data |
title_short | Genetic data are not always personal—disaggregating the identifiability and sensitivity of genetic data |
title_sort | genetic data are not always personal—disaggregating the identifiability and sensitivity of genetic data |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10676748/ https://www.ncbi.nlm.nih.gov/pubmed/38023689 http://dx.doi.org/10.1093/jlb/lsad029 |
work_keys_str_mv | AT rahnastojohanna geneticdataarenotalwayspersonaldisaggregatingtheidentifiabilityandsensitivityofgeneticdata |