Data Justice in Practice: A Guide for Policymakers

Abstract

The Advancing Data Justice Research and Practice project aims to broaden understanding of the social, historical, cultural, political, and economic forces that contribute to discrimination and inequity in contemporary ecologies of data collection, governance, and use. This is the consultation draft of a guide for policymakers. It provides actionable information for policymakers who wish to implement the principles and priorities of data justice in their policymaking activities. In the first section, we introduce the nascent field of data justice, from its early discussions to more recent proposals to relocate understandings of what data justice means. This section includes an account of the outreach we conducted with stakeholders throughout the world in developing a nuanced and pluralistic conception of data justice and concludes with a description of the six pillars of data justice around which this guidance revolves. 

Depending on their contexts, potential impacts, and scale, data policymaking activities may be carried out in a way that involves stakeholder engagement. To facilitate this process, the next section provides an explainer of the Stakeholder Engagement Process and the steps it includes—preliminary horizon scanning, policy scoping and stakeholder analysis, positionality reflection, and establishing stakeholder engagement objectives and methods. Finally, the last section presents the guiding questions that will help policymakers address issues of data, digital infrastructures, and affected areas of civic, public, and private life, throughout the policy lifecycle and in accordance with the six pillars of data justice.

Citation information

Leslie, David, Katell, Michael, Aitken, Mhairi, Singh, Jatinder, Briggs, Morgan, Powell, Rosamund, Rincón, Cami, Perini, Antonella, & Jayadeva, Smera. (2022). Data Justice in Practice: A Guide for Policymakers. The Alan Turing Institute in collaboration with The Global Partnership on AI. https://doi.org/10.5281/zenodo.6429475

Additional information

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.

Turing affiliated authors