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.We state
The genomics revolution – opening, understanding and manipulating ‘the book of life’ – results in fruitful questions about ‘good data’, dignity, ethics and law.
They are fruitful because they require engagement with issues that extend beyond diagnostics, therapeutic practice and the interaction of life-sciences research with business. They are also fruitful because they can be addressed through reference to past philosophical inquiries by figures such as Kant and Locke and to instances such the exploitation of vulnerable people in Nazi Germany and Jim Crow America where scientific ends were deemed to justify outrageous means.
We live in a world where there is excitement about genomic tools such as CRISPR, where governments are endorsing the establishment of population-scale health databases to facilitate advances in public health while strengthening national champions in an emerging global bioeconomy, where corporations such as Myriad are exploiting genomic patents, and where consumers are unwarily gifting familial data to private sector initiatives such as 23andMe or Ancestry.com.
In that world it is pertinent to examine assumptions about the nature, derivation and use of genomic data. Such an examination offers an opportunity for thinking about ways in which potential harms can be minimized, so that data functions as a social good rather than as a commodity subject to data stripmining. It also offers an opportunity to think about personhood. Most saliently, in an age of Big Data and algorithmic governance are individuals people who must be respected, or commodities that can be mined by the artificial persons that we characterize as corporations and governments, creations that exist to foster our flourishing?
This chapter accordingly considers ‘good data’ – and good data practice – through a lens of genomics. The chapter initially discusses genomics as a way of seeing that enables us to read individuals and populations as abstractions: repositories of genetic data (and hence potential susceptibilities, disorders and even behavioural traits) rather than persons. Through that lens it is tempting for the researcher to regard ‘good data’ as a matter of what is big (comprehensive) and better (more accurate) and commodifiable through law that provides patent holders with exclusive rights. As nations move swiftly to whole-of-population data collection, analysis and sharing, the chapter suggests that construing bigger and better as necessarily beneficial to people is contrary to the dignity that is central to personhood. From both a bioethics and legal perspective, typically centred on property rights, we are often asking the wrong questions about ‘good data’. ‘Bigger’ and ‘better’ may be beneficial from a data perspective; without an adequate ethical and legal framework, however, those benefits will not necessarily be extended to its human contributors.
The chapter accordingly critiques contemporary genomic initiatives such as Ancestry.com, National Geographic’s Genographic Project, 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.
The chapter concludes by arguing that 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. Goodness may be fostered by respectful clinical protocols, best practice on the part of research funders/regulators and enhanced awareness on the part of consumers rather than merely by exclusions under intellectual property law or an international agreement regarding genetic privacy and genomic rights.'What Is (in) Good Data?' by Monique Mann,. S Kate Devitt and Angela Daly offers an overview of the book.
The editors comment
In recent years, there has been an exponential increase in the collection, aggregation and automated analysis of information by government and private actors. In response to this there has been significant critique regarding what could be termed ‘bad’ data practices in the globalised digital economy. These include the mass gathering of data about individuals, in opaque, unethical and at times illegal ways, and the increased use of that data in unaccountable and discriminatory forms of algorithmic decision-making.
This edited collection has emerged from our frustration and depression over the previous years of our academic and activist careers critiquing these dystopian ‘Bad Data’ practices. Rather, in this text on ‘Good Data’ we seek to move our work from critique to imagining and articulating a more optimistic vision of the datafied future. We see many previous considerations of Bad Data practices, including our own, as only providing critiques rather than engaging constructively with a new vision of how digital technologies and data can be used productively and justly to further social, economic, cultural and political goals. The objective of the Good Data project is to start a multi-disciplinary and multi-stakeholder conversation around promoting good and ethical data practices and initiatives, towards a fair and just digital economy and society. In doing so, we combine expertise from various disciplines and sectors, including law, criminology, justice, public health, data science, digital media, and philosophy. The contributors to this text also have expertise in areas such as renewable energy, sociology, social media, digital humanities, and political science. There are many fields of knowledge that need to come together to build the Good Data future. This project has also brought together academic, government and industry experts along with rights advocates and activists to examine and propose initiatives that seeks to promote and embed social justice, due process rights, autonomy, freedom from discrimination and environmental sustainability principles.
