Intergovernmental

An open call for input from GPAI’s Data Governance Working Group

Data-light-pattern
Photo by Joshua Sortino on Unsplash

The Global Partnership on AI (GPAI) has a mission to “support and guide the responsible adoption of AI that is grounded in human rights, inclusion, diversity, innovation, economic growth and societal benefit, while seeking to address the UN Sustainable Development Goals (UN SDGs)”. This blog updates on the work of its Data Governance Working Group, and is co-authored by the Working Group’s Co-Chairs, Jeni Tennison and Maja Bogataj Jančič, and the Project Lead for the Data Governance Working Group Framework, Christiane Wendehorst.

In our first introduction to GPAI’s work on Data Governance back in August, we introduced two projects that the Working Group would be focusing on delivering for the first GPAI Summit in December:

  1. a Framework for GPAI’s work on Data Governance – this will set the stage for all future Working Group projects, serving as an overview over the most relevant terms and defining the understanding of the Working Group of data governance in the context of AI; and
  2. an investigation into the Role of Data in AI – to complement and dig into topics in the Framework in more depth, this will situate the importance of data to AI development and identify both areas where more data would be useful – such as specific, open, datasets that could be worthy of national support or international collaboration – and where harms arise due to the collection of, use of or access to data

When we announced these two projects, we committed to openness, transparency, diversity and collaboration being at their heart, so in that spirit, we are excited to share with you the ‘beta’ version of the Data Governance Working Group Framework.

We would love you and the wider community to test the Framework and let us know where we can make improvements. Your invaluable feedback will help ensure we don’t miss things and give us a sense of where there is most interest and value in our future work.

The Framework has been led by Christiane Wendehorst, with support from two research assistants Nina Thomic and Yannic Duller, and has been developed with the full collaboration of the wider Working Group over the course of many workshops, surveys, and drafts over the past two months. We are hugely grateful to the commitment of our Working Group experts, listed further below, many of whom have stayed up at some very unusual hours to accommodate the vast time difference from West Coast USA to Waikato in New Zealand. 

At headline level, the Framework covers four areas:

  1. The role of data in the AI context: including data for AI development & deployment and data lifecycle
  2. Why data governance matters: including case studies that illustrate the necessity of good data governance, the role and responsibility of different actors, and principles for Data Governance
  3. Parameters of data governance: including categories of data, data ecosystems, and rights with regard to data
  4. A roadmap for the Working Group’s future work that outlines how the Working Group will focus on three types of approaches to data governance: (1) Technical approaches (e.g. privacy-enhancing technologies, bias detection and correction techniques), (2) Legal approaches (e.g taking into account IP law, data protection law) and (3) Organisational/institutional approaches (e.g data representatives or trusts, common data spaces)

Though we will be making an official presentation at the December Summit, our intention is for the Data Governance Working Group Framework to become a ‘living’ document and evolve as it needs to keep pace with a fast-moving field and a fast-changing world. We intend for this ‘beta’ release consultation to be the first of many opportunities and the start of an ongoing conversation for the wider community to help shape the Working Group’s priorities.

As stated, the Framework is going to be complemented by the investigation into the Role of Data in AI. We are thrilled to be partnering with a consortium led by the University of Edinburgh, combining a breadth of technical and legal expertise made up of the School of Informatics, the Digital Curation Centre and Trilateral Research. The team has been hosting some fascinating workshops to develop their recommendations, opening with a deep dive on the role of data in human language technologies and under-represented languages, and we’ve been delighted to be joined by additional experts from Rwanda and India for these workshops. The consortium was selected from a very competitive set of proposals and we are looking forward to presenting their findings at the Summit.

If you would like to submit your thoughts on the Data Governance Working Group Framework, then the project team will be delighted to hear from you. We would be grateful if you could either share your comments directly within the document to contribute to the wider discussion, or alternatively submit feedback via email by the 17th of November to the International Centre of Expertise in Montréal for the Advancement of Artificial Intelligence (one of GPAI’s two Centres of Expertise and designated lead on support for the Data Governance Working Group) at info@ceimia-icemai.org. This will allow time to update the document and finalise its presentation in time for the Summit in December.

Thank you again to all our Working Group participants, and we are looking forward to hearing from you.

Membership of GPAI’s Data Governance Working Group

Working Group members

Jeni Tennison (Co-Chair) – Open Data Institute (UK)

Maja Bogataj Jančič (Co-Chair) – Intellectual Property Institute (Slovenia)

Alejandro Pisanty Baruch – National Autonomous University (Mexico)

Alison Gillwald – Research ICT Africa (South Africa / UNESCO)

Bertrand Monthubert – Occitanie Data (France)

Carlo Casonato – University of Trento (Italy)

Carole Piovesan – INQ Data Law (Canada)

Christiane Wendehorst – European Law Institute / University of Vienna (EU)

Dewey Murdick  – Center for Security and Emerging Technology (USA)

Hiroshi Mano – Data Trading Alliance (Japan)

Iris Plöger – Federation of German Industries (Germany)

Jeremy Achin – DataRobot (USA)

Josef Drexl – Max Planck Institute (Germany)

Kim McGrail – University of British Columbia (Canada)

Matija Damjan – University of Ljubljana (Slovenia)

Neil Lawrence – University of Cambridge (UK)

Nicolas Miailhe – The Future Society (France)

Oreste Pollicino – University of Bocconi (Italy)

Paola Villerreal – National Council for Science and Technology (Mexico)

Paul Dalby – Australian Institute of Machine Learning (Australia)

P. J. Narayanan– International Institute of Technology, Hyderabad (India)

Shameek Kundu – Standard Chartered Bank (Singapore)

Takashi Kai – Hitachi (Japan)

Teki Akuetteh Falconer – Africa Digital Rights Hub (Ghana / UNESCO)

Te Taka Keegan – University of Waikato (New Zealand)

V. Kamakoti – International Institute of Technology, Madras (India)

Yeong Zee Kin – Infocomm Media Development Authority (Singapore)

Observers

Elettra Ronchi – OECD

Jaco Du Toit – UNESCO


AI Wonk Dog
Sign up for email alerts from the AI Wonk:

Disclaimer :The opinions expressed and arguments employed herein are solely those of the authors and do not necessarily reflect the official views of the OECD or its member countries. The Organisation cannot be held responsible for possible violations of copyright resulting from the posting of any written material on this website/blog.

Sign up for email alerts