The global popularity and use of large language models (LLMs) for generative AI have revealed enforcement problems as well as gaps in the governance of data at the national and international levels. George Washington University’s (GWU’s) Digital Trade and Data Governance Hub and the National Institute of Standards and Technology-National Science Foundation Institute for Trustworthy AI in Law & Society, along with several partners, are hosting a two-day conference to discuss these issues. At this free, hybrid event, speakers and participants will:
- identify data governance gaps for LLMs;
- propose and discuss solutions for these gaps; and
- promote understanding of data governance as a key component of AI governance.
The conference will feature two days of panel discussions, focusing on how firms acquire data; whether firms choose to make their LLMs open, partially open or closed to outside review; and the implications of these choices for democracy, human rights and trust. We will explore new ideas for how to govern the data underpinning generative AI while promoting broader understanding and engagement in the governance of data. Additionally, we will examine the actions governments are taking to bridge data governance gaps. The conference will include consensus-building exercises to attempt to arrive at common policy proposals.
Register now to stay updated on the schedule and discussions.
To learn more about the discussion topics, please check out our reading list.
Audience and Format
The event is free and open to anyone interested in discussing the data that is used to build generative AI systems. The program will consist of five panels, two keynotes and a fireside chat, each of which is designed to encourage audience questions and suggestions. Lunch and snacks will be provided. The conference will be live-streamed (link to be provided after registering) and posted on our YouTube page after the event has ended.
The conference will include computer and data scientists from companies such as Microsoft, Hugging Face, IBM and EleutherAI; researchers from the University of Maryland, Stanford University, Princeton University, the Distributed AI Research Institute, and the American Federation of Labor and Congress of Industrial Organizations; and policy makers from Germany, the European Union, the United Kingdom and the United States.
Panels will focus on:
- “The Sources of LLM Data”;
- “The Continuum of Closed and Open LLMs and Their Implications for Data Governance”;
- “Data Openness and Society”;
- “What Are Governments Doing to Close the Data Governance Gaps”; and
- “New Ideas for Shared Data Governance.”
Conference Contributors
- Omidyar Network
- National Science Foundation
- Indiana University
- Centre for International Governance Innovation
- Bertelsmann Stiftung
