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Data governance |
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Blogs |
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.
Current projects
The Working Group on Data Governance is pursuing the following projects in 2024:
- Algorithmic transparency in the public sector (jointly with the Working Group on Responsible AI)
- From co-generated data to generative AI: New rights and governance models in digital ecosystems (Co-Gen)
- The role of government as a provider of data for AI
GPAI expert reports
2023
DG Working Group Report (December 2023)
Considering the potential for its misuse, one of the most important challenges in the development of AI is ensuring that data is handled safely and responsibly. The Data Governance Expert Working Group (DG EWG) works to promote its use in ways that align with human rights, inclusion and societal benefit while striving to meet the UN’s Sustainable Development Goals (SDGs).
This report provides an overview of current projects as well as next steps for 2024 to highlight the impact and reach of GPAI’s work in ensuring a responsible and trustworthy approach to data.
Trustworthy Data Institutional Framework - A practical tool to improve trustworthiness in data ecosystems (October 2023)
In an age where data is such an accessible yet valuable resource, what kind of framework is required to ensure data rights? The Trustworthy Data Institutional Framework (TDIF) was established to ensure transparency in this regard. This report examines the methodology behind the initiative, how it represents communities’ ideal vision of trustworthiness, and how it measures organisations’ efforts to achieve it. In doing so, it ensures that data serves the needs of those who provide it and empower them to play an active role in the data value chain.
Overcoming Data Barriers via Trustworthy Privacy-Enhancing Technologies - Demonstration Report (November 2023)
Data is an invaluable resource and requires safeguards to prevent bad actors from gaining access to it. Through collaborating with Singapore’s Infocomm Media Development Authority and Digital Trust Centre, GPAI Experts examined how privacy-enhancing technologies (PETS+) can be used to share data from previous pandemics and improve societal resilience to future outbreaks. This report presents key findings from this project, which highlight the importance of circulating data via confidential and trustworthy channels.
The Role of Government as a Provider of Data for Artificial Intelligence - Interim Report (November 2023)
As AI evolves, governments will play an increasing role in providing AI developers with public information. Although it can encourage equitable access and transparency, this practice raises questions surrounding existing legal frameworks and data processing principles. Through conducting case studies in the UK, Chinese Taipei, Nigeria, and Colombia, GPAI Experts assessed the for data sharing to identify the benefits and risks and provide recommendations for its good practice.
In the face of a changing climate, AI has the potential to facilitate positive environmental action through predicting weather events and their societal impact, particularly regarding displacement and migration. However, those communities affected have little say in the collection or use of such data. As such, data trusts have been developed to enable them to speak on matters by which they are directly affected. This report highlights how perspectives from the Global South can be better included in the development of climate-based AI solutions and proposes a framework to support this practice.
2022
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)
2021
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)
2020
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
- Bertrand Monthubert, Co-Chair, Conseil National de l'Information Géolocalisée
- Shameek Kundu, Co-Chair, Truera
- Alžběta Krausová, Expert, Institute of State and Law, Czech Academy of Sciences
- Ching-Yi Liu, Co-Lead, National Taiwan University
- Christiane Wendehorst, Co-Lead, European Law Institute
- Dani Chorin, Expert, Ministry of Innovation, Science and Technology
- Emmanuel Vincent, Expert, Inria
- Jhalak Mrignayani Kakkar, Co-Lead, Centre for Communication Governance
- Kim McGrail, Co-Lead, University of British Columbia
- Kudakwashe Dandajena, Expert, Program Manager, Community of Scientists-AIMS II
- M. JAE MOON, Expert, Yonsei University
- Marc Rotenberg, Expert, Center on AI and Digital Policy
- Massamba Badiane, Expert, Office of Information Systems Security and Digital Confidence at the ICT Department, at the Ministry of Digital Economy and Telecommunications (Senegal)
- Mikael Jensen, Expert, D-Seal
- Paul Dalby, Expert, Australian Institute for Machine Learning
- Radim Polčák, Expert, Masaryk University in Brno
- Andrea A. Jacob, Expert, Code Caribbean
- Yeong Zee Kin, Expert, Infocomm Media Development Authority of Singapore
- Ulises Cortés, Expert, Universitat Politècnica de Catalunya
- Maja Bogataj Jančič, Expert, Intellectual Property Institute
- Alison Gillwald, Expert, Research ICT Africa
- Josef Drexl, Expert, Max Planck Institute
- Sarah Villeneuve, Expert, Partnership on AI
- Seong Oun Hwang, Expert, Gachon University
- Thierry Warin, Expert, HEC Montréal
- Avik Sarkar, Expert, Indian School of Business
- Andrew Sportle, Expert, iNZight Analytics Ltd
- Sarah Shoker, Expert, OpenAI
- Zümrüt Müftüoğlu, Expert, Yildiz Technical University
- Christian Reimsbach-Kouatze, Observer, OECD
- Jaco Du Toit, Observer, UNESCO