A Relational Theory of Data Governance

Data-governance law-the legal regime that regulates how data about people is collected, processed, and used-is the subject of lively theorizing and several proposed legislative reforms. Different theories advance different legal interests in information. 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. Put simply, they miss the point of data production in a digital economy: to put people into population-based relations with one another. This relational aspect of data production drives much of the social value and harm of data collection and use in a digital economy. This Feature advances a theoretical account of data as social relations, constituted by both legal and technical systems. It shows how data relations result in supraindividual legal interests. Properly representing and adjudicating among those interests necessitates far more public and collective (i.e., democratic) forms of governing data production. Individualist data-subject rights cannot represent, let alone address, these population-level effects. This account offers two insights for data-governance law. First, it better reflects how and why data collection and use produce economic value as well as social harm in the digital economy. This brings the law governing data flows into line with the economic realities of how data production operates as a key input to the information economy. Second, this account offers an alternative normative argument for what makes datafication-the transformation of information about people into a commodity-wrongful. What makes datafication wrong is not (only) that it erodes the capacity for subject self-formation, but instead that it materializes unjust social relations: data relations that enact or amplify social inequality. This account indexes many of the most pressing forms of social informational harm that animate criticism of data extraction but fall outside typical accounts of informational harm. This account also offers a positive theory for socially beneficial data production. Addressing the inegalitarian harms of datafication-and developing socially beneficial alternatives-will require democratizing data social relations: moving from individual data-subject rights to more democratic institutions of data governance.