Organizer(s):

Tamra Carpenter, DIMACS

Denizalp Goktas, Brown University

Amy Greenwald, Brown University

David Pennock, DIMACS

Segev Wasserkrug, IBM Research

Description

Foundation models—models trained on large datasets which can easily adapt to many tasks using few-shot or zero-shot learning—are a major paradigm shift in AI. A primary example are Large Language Models (LLMs), such as ChatGPT, which, through natural language prompting and interaction, can already provide significant value in use cases such as document and code generation. The widespread deployment of such models, however, is creating new challenges, both technical and societal.

This workshop aims to initiate work at the intersection of foundation models and game theory. We are interested both in how to use game theory to address some of the issues arising from the use of foundation models, and in how we might advance game theory through the use of foundation models. Our goal, therefore, is to attract researchers who work on foundation models, natural language processing (NLP), and game theory, and to facilitate a structured, academic exchange among them. 

The workshop will focus on:

1. Avenues to improve foundation models and LLMs through the use of game-theoretic models and tools: Leveraging multiagent learning in games to study interactions among foundation models and LLMs, and to improve their training algorithms.

2. Advancing  game theory and algorithmic game theory using foundation models and LLMs: Studying the potential use of foundation models and LLMs to better model human preferences and to solve games, especially those that arise in economic, political, and social contexts.

3. Assessment of the societal impact of foundation models and LLMs using game theory: Investigating methodologies to quantify and predict the effects of LLMs on technology and society using game theory.

The exchange of ideas among researchers from the various communities has the potential to push the frontiers of foundation model development and AI more broadly. This workshop is intended as a platform in which to initiate this exploration.

View video playlist.

Program

Thursday, October 19, 2023

Friday, October 20, 2023

Call For Participation

Presentations at this workshop are by invitation but others are welcome to attend. There is no fee to attend but registration is required. Please register using the button at the bottom of the page. Space is limited, so please register early if you plan to attend.

Update (9/26/2023): This event has reached capacity, so we have removed the registration link. If you would like to join a waiting list to attend please send email to Nicole Clark Johnson.

Poster session: The workshop will feature a poster session. If you would like to present a poster please apply using the form referenced below. 9/26/2023: Submissions are now closed.

Request support: There are limited funds available to support travel by those whose attendance is contingent on support. Please apply by September 23, 2023 and do not book your tickets until you hear from us!

To apply for travel support or to apply to submit a poster: Please complete this form. (It is a single form through which you can apply for support or to present a poster, or both.) We especially encourage diverse and inclusive participation. We will prioritize applications for support from students presenting posters and those from minority or underrepresented groups.9/26/2023: Submissions are now closed.

Presented in association with the SF on Mechanisms & Algorithms to Augment Human Decision Making.

Registration for this event is closed.