Advancing Data Justice Research and Practice: An Integrated Literature Review

The Advancing Data Justice Research and Practice (ADJRP) project aims to widen the lens of current thinking around data justice and to provide actionable resources that will help policymakers, practitioners, and impacted communities gain a broader understanding of what equitable, freedom-promoting, and rights-sustaining data collection, governance, and use should look like in increasingly dynamic and global data innovation ecosystems. In this integrated literature review and annotated bibliography we hope to lay the conceptual groundwork needed to support this aspiration. The endeavour to broaden current visions of what data justice is (and what it could become) involves not only building on the considerable insights that have accrued since the inception of the field less than a decade ago. It also involves identifying where the study of data justice has—thus far—fallen short of engaging with and integrating the perspectives and wisdom of those significantly impacted by the subject matter it broaches. It involves distinguishing where limited fields of vision in the current academic literature, gaps in disciplinarily anchored understandings, and listening deficits in scholarship and policymaking, have cramped the analytical and normative scope of its concerns, conclusions, and proposed solutions. The introduction motivates the broadening of data justice that is undertaken by the literature review which follows. First, we address how certain limitations of the current study of data justice drive the need for a re-orientation, indeed a re-location, of data justice research and practice. We map out the strengths and shortcomings of the contemporary state of the art and then elaborate on the challenges faced by our own effort to broaden the data justice perspective in the decolonial context. We then lay out three trajectories of re-orientation, what we will term the ‘where,’ the ‘when,’ and the ‘who’ of data justice. Finally, this introductory section addresses the question, what is data justice? Here, we provide a brief history of the data justice literature and outline results collected via our decidim participatory platform survey where we received feedback on what data justice means to different groups. Together, these sections explore current interpretations of the term ‘data justice’ both within academia and beyond. Key to the re-orientation of data justice prioritised throughout this literature review is the idea that data justice is contextually determined. Consequently, rather than answer the question, what is data justice, directly, the next section presents six pillars of data justice research and practice. These guiding priorities of power, equity, access, identity, participation, and knowledge are set out as resources for reflection to be taken up by those working to advance data justice globally and remain central throughout this review. The body of the literature review itself covers seven thematic areas. For each theme, the ADJRP team has systematically collected and analysed key texts in order to tell the critical empirical story of how existing social structures and power dynamics present challenges to data justice and related justice fields. In each case, this critical empirical story is also supplemented by the transformational story of how activists, policymakers, and academics are challenging longstanding structures of inequity to advance social justice in data innovation ecosystems and adjacent areas of technological practice. Throughout, key themes and key gaps are summarised at the top of each section to help key readers into important ideas and areas in need of improvement. Reflection questions for academic researchers, policymakers, developers, and impacted communities are also provided at the end of each theme, offering a means of relating the thematic areas to specific stakeholder perspectives.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