Bhaskar Ray Chaudhury (UIUC)- Towards a Theory of Equilibrium in Data Markets

Abstract: The algorithmic study of market equilibria has been a cornerstone of economics and computation since its inception, with rich theories developed around equilibrium/ stability notions such as Nash, Stackelberg, and Competitive Equilibria. In this talk, I explore how these classical concepts extend—or fail to extend—to a new and increasingly central economy: the data economy.

With the increasing integration of AI and ML technologies in the industry, data has emerged as one of the most valuable assets of the 21st century. However, unlike traditional goods, data is non-rival—it can be freely duplicated and shared without depletion. This fundamental property challenges standard equilibrium frameworks that assume scarcity (limited supply) and exclusivity (no two agents can simultaneously benefit from a resource).

We introduce a formal model of data markets, explicitly capturing (1) the role of data in improving predictive performance as data buyers’ utility functions, and (2) the implications of data’s non-rival nature for equilibrium concepts. Building on this model, we examine the existence, geometry, and computational aspects of various equilibrium notions, highlighting key parallels and departures from traditional markets.

The talk will begin with a brief tutorial on equilibrium concepts—no prior background is required—and conclude with open problems and emerging directions for the theory and design of data markets.