In this researchers working group seminar, Dr. Salomé Viljoen (Columbia Law School) and PhD researcher at the EUI Law department, Tommaso Fia, will present their papers on the alternative mechanisms of data governance.
Dr. Viljoen argues that the inegalitarian harms of datafication — and developing socially beneficial alternatives — require democratising data social relations: moving from individual data-subject rights to more democratic institutions of data governance. Tommaso Fia’s talk addresses the issue of data-driven value capture and value redistribution in the smart city. Therefore, it explores two solutions that can have distributional implications for the governance of ‘urban data commons’, ie Fritz Schumacher’s proposal of (large-scale) ownership in his classic Small is beautiful: Economics as if people mattered, and the (IP) benefit-sharing principle as applied to indigenous communities.
Salomé Viljoen (Columbia Law School) – 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.
Tommaso Fia (EUI) – Governance of Urban Data Commons as a Matter of Value Redistribution
In today’s urban environments, ‘datafication’ of social interactions and community activities is ubiquitous and actualises in various applications. One may think of sensor-enabled urban mobility, data-driven water supply systems, innovative waste management plants, and so forth. Data-driven solutions, forming the ‘smart city’, aim to tackle complex urban problems, but largely depend on marketising or privatising public services. Smart city models, therefore, tend to disguise processes of data appropriation by private enterprises. By contrast, there is a bourgeoning legal literature exploring how decentralised data infrastructures can open up access to ‘urban data commons’ (‘UDC’). A growing number of public-led (eg the DECODE Project in Barcelona), private-led (eg Sidewalk Toronto in Toronto), and informal projects have put data access into practice. These access-bolstering approaches aim to open up data access and foster data sharing, whereas they tend to neglect the redistribution of value flowing from the positive impact of citizens’ interactions and cooperation on the smart city vendors’ activities (‘positive externalities’).
This talk addresses the issue of data-driven value generation and redistribution in the smart city. It argues that data governance encompasses matters of both use and value that need to be jointly addressed. Therefore, it explores some recommendations that can help to incorporate matters of value from data-driven activities. Specifically, it investigates the ways to remunerate municipalities in cases where smart city vendors harness positive externalities. In doing so, I circumscribe my analysis to two solutions that have distributional implications for the governance of UDC, ie Fritz Schumacher’s proposal of (large-scale) ownership in his classic Small is beautiful: Economics as if people mattered, and the (IP) benefit-sharing principle as applied to indigenous communities.
Participants are welcome to ask questions and take part in the open discussion after the presentations.