Not as Good as Gold? Genomics, Data and Dignity

Bruce Baer Arnold, Wendy Bonython

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Abstract

Genomics enables us to read individuals and populations as abstractions - repositories of genetic data rather than persons. Through that lens it is tempting to regard 'good data' as a matter of what is big (comprehensive) and better (more accurate), rather than considering whether it is beneficial to or respectful of its human contributors. As nations move swiftly to whole-of-population data collection, analysis and sharing, this chapter suggests that construing bigger and better data as necessarily beneficial to people is contrary to the dignity that is central to personhood. From both a bioethics and legal perspective we are often asking the wrong questions about 'good data'. The chapter critiques contemporary genomic initiatives such as the Genographic Project, Ancestry.com, deCODE and 23andMe in arguing it is imperative to consider meaningful consent regarding data collection and use, alongside establishment of a genomic commons that addresses problems inherent in propertization of the genome through patent law. Public and private goods can be fostered through regulation that ensures data quality and an information framework centred on public education about genomic data, encouraging responsible use of data within and across national borders. If the genome is 'the book of life' we must ensure that 'good' data is available to all and is understood rather than monopolized, mishandled or misread.
Original languageEnglish
Title of host publicationGood Data
EditorsAngela Daly, S. Kate Devitt, Monique Mann
Place of PublicationAmsterdam
PublisherInstitute of Network Cultures
Chapter8
Pages135-155
Number of pages21
ISBN (Electronic)9789492302274, 9789492302281
Publication statusPublished - 2019

Publication series

NameTheory on Demand
PublisherInstitute of Network Cultures
Volume29

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  • Cite this

    Arnold, B. B., & Bonython, W. (2019). Not as Good as Gold? Genomics, Data and Dignity. In A. Daly, S. K. Devitt, & M. Mann (Eds.), Good Data (pp. 135-155). (Theory on Demand; Vol. 29). Institute of Network Cultures. https://networkcultures.org/blog/publication/tod-29-good-data/