The idea of “data justice” is of recent academic vintage. It has arisen over the past decade in Anglo-European research institutions as an attempt to bring together a critique of the power dynamics that underlie accelerating trends of datafication with a normative commitment to the principles of social justice—a commitment to the achievement of a society that is equitable, fair, and capable of confronting the root causes of injustice.However, despite the seeming novelty of such a data justice pedigree, this joining up of the critique of the power imbalances that have shaped the digital and “big data” revolutions with a commitment to social equity and constructive societal transformation has a deeper historical, and more geographically diverse, provenance. As the stories of the data justice initiatives, activism, and advocacy contained in this volume well evidence, practices of data justice across the globe have, in fact, largely preceded the elaboration and crystallisation of the idea of data justice in contemporary academic discourse. We have organised the stories contained in this repository into two groups. The first group, ‘Challenges to Data Justice: Stories of Data Discrimination and Inequity”, poses the question: What are the sorts of problems and challenges to which data justice practitioners are responding? This section is intended to orient the reader to the range of empirical problems faced by data justice researchers and practitioners the world over. We have provided examples of data practices that have been criticised as posing risks of moral injury and that have been identified as leading to inequitable or discriminatory outcomes. Case studies include a national ID card that serves as a government payment system in Venezuela, a courier service/digital technology company in Colombia, and a digital registry of ‘rights, tenancy, and crops’ in India. The second group, ‘Transformational Stories of Data Justice: Initiatives, Activism, and Advocacy’, poses the questions: What do responses to the range of challenges posed to data justice look like? What are the kinds of transformation that such responses are trying to bring about? The purpose of this section is to orient the reader to the ‘moral grammar’ intrinsic to boots-on-the-ground struggles for data justice. To be sure, the initiatives and instances of activism and advocacy that are covered are intended to provide insight into the sources of normativity and liberation that inhere pre-reflectively in the actual social and historical practices of resistance that organisations undertake. Case studies relating to these transformative data justice practices include a movement for Indigenous data sovereignty in Aotearoa, social mobilisation against violence done to trans people across Eastern Europe and Central Asia, and legal advocacy for public accountability in data use and algorithmic decision-making in the United Kingdom. Ultimately, by bringing the first and second sets of data justice stories into high relief, we hope to provide the reader with two interdependent tools of data justice thinking: First, we aim to provide the reader with the critical leverage needed to discern those distortions and malformations of data justice that manifest in subtle and explicit forms of power, domination, and coercion. Second, we aim to provide the reader with access to the historically effective forms of normativity and ethical insight that have been marshalled by data justice activists and advocates as tools of societal transformation—so that these forms of normativity and insight can be drawn on, in turn, as constructive resources to spur future transformative data justice practices.

This report was commissioned by the International Centre of Expertise in Montréal in collaboration with GPAI's Data Governance Working Group, and produced by the Alan Turing Institute. The research was supported, in part, by a grant from ESRC (ES/T007354/1), Towards Turing 2.0 under the EPSRC Grant EP/W037211/1, and from the public funds that make the Turing's Public Policy Programme possible.