ΑΙhub.org
 

Advancing data justice research and practice project


by
31 March 2023



share this:

black, white and grey hands with text in the backgroundScreenshot from the data justice video.

Advancing data justice research and practice is a collaboration between the Global Partnership on AI (GPAI), The Alan Turing Institute, 12 policy pilot partners, and participants and communities across the globe. The project aims to augment the current thinking around data justice and to provide actionable resources that will help policymakers, practitioners, and impacted communities.

As part of the project, a short series of documentaries tracks the work of the participants. The first instalment was published last year and discusses how data-driven technologies can be deployed in a way which is compatible with values of social justice.

The second episode of this series has recently been released, and you can watch it below. It defines data injustice and explores some case studies of the human consequences of such injustice.

A major contributions of the project has been the production of a series of three practical guides for policymakers, impacted communities, and developers. The guides consist of background content on data justice and how this relates to AI, as well as practical questions for stakeholder groups to consider in their practice, use, and experience of AI/ML systems.

You can find links to all of the guides here. The pdf versions are at these links:
Data Justice in Practice: A Guide for Policymakers
Data Justice in Practice: A Guide for Impacted Communities
Data Justice in Practice: A Guide for Developers

Find out more about the project here.




Lucy Smith is Senior Managing Editor for AIhub.
Lucy Smith is Senior Managing Editor for AIhub.

            AUAI is supported by:



Subscribe to AIhub newsletter on substack



Related posts :

Pre-training isn’t bitter enough

  10 Jul 2026
Given an unlabeled data stream, and a small set of verifiable downstream examples, can we use those examples during continued pre-training?

Interview with Thi Kieu Khanh Ho: Time-series anomaly detection

  09 Jul 2026
How can we teach AI systems to recognize when something unusual or abnormal is happening in complex, real-world data streams, without relying on large amounts of labeled examples?

#RoboCup2026 social media round-up

  08 Jul 2026
Find out what the teams got up to at this year's RoboCup extravaganza in Incheon.

#RoboCup2026 – humanoid league knockout stages

  06 Jul 2026
Find out who won the small, middle and large divisions in Incheon.

#RoboCup2026 – humanoid league day 2

  03 Jul 2026
Find out the latest from day two of the competition.

#RoboCup2026 – humanoid league day 1

  02 Jul 2026
In the first of our round-ups from the humanoid league we introduce the competition, and report some preliminary results.

Adaptive parallel reasoning: the next paradigm in efficient inference scaling

  02 Jul 2026
A detailed analysis of recent progress in the field of parallel reasoning.



AUAI is supported by:







Subscribe to AIhub newsletter on substack




 















©2026.05 - Association for the Understanding of Artificial Intelligence