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Working Group on Data Governance

The mandate of the Working Group of Data Governance aligns closely with GPAI’s overall mission. The Working Group aims to collate evidence, shape research, undertake applied AI projects and provide expertise on data governance, to promote data for AI being collected, used, shared, archived and deleted in ways that are consistent with human rights, inclusion, diversity, innovation, economic growth, and societal benefit, while seeking to address the UN Sustainable Development Goals.

The Working Group on Data Governance applies a horizontal lens to its work and projects. This reflects the foundational nature of data governance and suits the group’s expertise, alongside maintaining the flexibility and broader use of its work. The Working Group collaborates with other Working Groups to advise on the data governance aspects of GPAI’s wider project portfolio, with experts having volunteered to provide specialist input on a responsible AI strategy for the environment, social media governance, AI for public domain drug discovery, and intellectual property. The goal is to ensure that the outputs are widely useful amongst those researching, thinking about and implementing data governance practices in AI.

GPAI expert reports


 DG Working Group Report (December 2023)

 Trustworthy Data Institutional Framework - A practical tool to improve trustworthiness in data ecosystems (October 2023) 

 Overcoming Data Barriers via Trustworthy Privacy-Enhancing Technologies - Demonstration Report (November 2023)

 The Role of Government as a Provider of Data for Artificial Intelligence - Interim Report (November 2023)

 Designing Trustworthy Data Institutions - Scanning the Local Data Ecosystem in Climate-Induced Migration in Lake Chad Basin - Pilot Study in Cameroon (October 2023)



A Framework Paper for GPAI’s Work on Data Governance 2.0 (November 2022)

Data Governance Working Group Report (November 2022)

 Data Justice Policy Brief: Putting Data Justice into Practice (November 2022)

 A Primer on Data and Social Justice (November 2022)

 A Primer on Data and Economic Justice (November 2022)

Enabling Data Sharing for Social Benefit through Data Trusts: Data Trusts in Climate (March 2022)

Data Justice in Practice: A Guide for Policymakers (March 2022)

 Data Justice in Practice: A Guide for Impacted Communities (March 2022)

Data Justice in Practice: A Guide for Developers (March 2022)

Advancing Data Justice: Research and Practice - An Integrated Literature Review (March 2022)

Advancing Data Justice: Research and Practice - Data Justice Stories: A Repository of Case Studies (March 2022)

Advancing Data Justice Research and Practice: An Interim Annotated Bibliography and Table of Organisations for the 2022 AI UK event (March 2022)



 Data Governance Working Group Report (November 2021)

Enabling Data Sharing for Social Benefit through Data Trusts (November 2021)

Advancing Data Justice Research and Practice (November 2021)



Data Governance Working Group Report (November 2020)

Framework paper for GPAI's work on data governance (November 2020)

 The Role of Data in AI (November 2020)

Our experts

Group contact point: GPAI Montreal Centre of Expertise

Group participants

  • Maja Bogataj Jančič, Intellectual Property Institute, Slovenia (co-chair)
  • Jeni Tennison, Connected by data, UK (co-chair)
  • Aleksandra Przegalińska , Kozminski University
  • Asunción Gomez, University of Madrid
  • Robert Kroplewski, Plenipotentiary of the Minister of Digitization for the Information Society
  • Alžběta Krausová, Institute of State and Law, Czech Academy of Sciences
  • "Ching-Yi Liu", National Taiwan University
  • Dani Chorin, Ministry of Innovation, Science and Technology
  • Jhalak Mrignayani Kakkar, Centre for Communication Governance
  • Marc Rotenberg, Center on AI and Digital Policy
  • Mikael Jensen, D-Seal
  • Radim Polčák, Masaryk University in Brno
  • Bertrand Monthubert, Conseil National de l'Information Géographique
  • Christiane Wendehorst, European Law Institute
  • Kim McGrail, University of British Columbia
  • Paul Dalby, Australian Institute for Machine Learning
  • Shameek Kundu, Truera
  • Ulises Cortés, Universitat Politècnica de Catalunya
  • Massamba BADIANE, "Office of Information Systems Security and Digital Confidence at the ICT Department, at the Ministry of Digital Economy andTelecommunications (Senegal)"
  • M. Jae Moon, Yonsei University
  • Sarah Shoker, OpenAI and University of Waterloo
  • Yeong Zee Kin, Infocomm Media Development Authority of Singapore


  • Christian Reimsbach-Kounatze, OECD