'Democratic Data: A Relational Theory For Data Governance' bySalome Viljoen comments
Data governance law — the law regulating how data about people is collected, processed, and used — is the subject of lively theorizing. Concerns over datafication (the transformation of information or knowledge about people into a commodity) and its harmful personal and social effects have produced an abundance of proposals for reform. Different theories advance different legal interests in information, resulting in various individualist claims and remedies. Some seek to reassert individual control for data subjects over the terms of their datafication, while others aim to maximize data subject financial gain. But these proposals share a common conceptual flaw: they miss the central importance of population-level relations among individuals for how data collection produces both social value and social harm. The data collection practices of the most powerful technology companies are primarily aimed at deriving population-level insights from data subjects for population-level applicability, not individual-level insights specific to the data subject in question. Put simply, the point of data production is to put people into population-based relations with one another; this activity drives data collection practices in the digital economy and results in some of the most pressing forms of social informational harm. Individualist data subject rights cannot represent, let alone address, these population-level effects.
Treating data’s population-level effects as central to the task of data governance opens up new terrain. The proper aim of data governance is not to reassert individual control over the terms of one’s own datafication or to maximize personal gain, but instead to develop the institutional responses necessary to represent the relevant population-level interests at stake in data production. This shifts the task of reform from granting individuals rights to exit or payment, to securing recognition and standing to shape the purposes and conditions of data production for those with interests at stake in such choices. From this reorientation, data governance law may develop legal reforms capable of responding to the harms of datafication without foreclosing socially beneficial forms of data production.
Part One describes the stakes and the status quo of data governance. It documents the significance of data processing for the digital economy. It then evaluates how the predominant legal regimes that govern data collection and use — contract and privacy law — code data as an individual medium. This conceptualization is referred to throughout the Article as “data as individual medium” (DIM). DIM regimes apprehend data’s capacity to cause individual harm as the legally relevant feature of datafication; from this theory of harm follows the tendency of DIM regimes to subject data to private individual ordering. Part Two presents the core argument of the Article regarding the incentives and implications of data social relations within the data political economy. Data’s capacity to transmit social and relational meaning renders data production especially capable of benefitting and harming others beyond the data subject from whom data is collected. It also results in population-level interests in data production that are not reducible to the individual interests that generally feature in data governance. Thus, data’s relationality presents both a conceptual challenge for data governance reform. Part Three evaluates two prominent legal reform proposals that have emerged in response to concerns over datafication. Propertarian proposals respond to growing wealth inequality in the data economy by formalizing individual propertarian rights over data as a personal asset. Dignitarian reforms respond to how excessive data extraction can erode individual autonomy by granting fundamental rights protections to data as an extension of personal selfhood. While propertarian and dignitarian proposals differ on the theories of injustice underlying datafication and accordingly provide different solutions, both resolve to individualist claims and remedies that do not represent, let alone address, the relational nature of data collection and use. Part Four proposes an alternative approach: data as a democratic medium (DDM). This alternative conceptual approach apprehends data’s capacity to cause social harm as a fundamentally relevant feature of datafication; from this follows a commitment to collective institutional forms of ordering. Conceiving of data as a public resource subject to democratic ordering accounts for the importance of population-based relationality in the digital economy. This recognizes a greater number of relevant interests in data production and recasts the subject of legal concern from interpersonal violation to the condition of population-level data relations under which data is produced and used. DDM therefore responds not only to salient forms of injustice identified by other data governance reforms, but also to significant forms of injustice missed by individualist accounts. In doing so, DDM also provides a theory of data governance from which to defend forms of socially beneficial data production that individualist accounts may foreclose. Part Four concludes by outlining some examples of what regimes that conceive of data as democratic could look like in practice.