The University at Albany and the Laboratory for Aggregate Economics and Finance (LAEF) at UCSB announce an academic conference highlighting work at the frontier of Artificial Intelligence and the Macroeconomy. The conference seeks to showcase research exploring how the rapid development and adoption of AI technologies are reshaping aggregate economic dynamics. What are the primary channels through which AI influences long-run productivity growth and labor market structures? How does the integration of machine learning into structural models improve our ability to forecast and simulate policy outcomes? These are among the many questions the conference will consider.
We invite submissions from all fields in economics. Primary consideration will be given to work that applies AI and machine learning techniques to enhance macroeconomic modeling or that quantitatively analyzes the aggregate impacts of AI on growth, inequality, and fiscal stability. We also encourage submissions that utilize novel datasets or computational methods to yield new insights into how automation and intelligent systems affect the broader economy.
Conference organizers are Nick Pretnar (LAEF at UCSB), Ben Griffy (SUNY at Albany), and Adrian Masters (SUNY at Albany). Organizers will provide hotel and travel accommodations for all invited participants.