FSS Seminar Series (UM Distinguished Visiting Scholar): Artificial Intelligence and Technological Unemployment

Speaker: Ping WANG, Professor, Department of Economics, Washington University in St. Louis, USA

Date: 10/12/2025 (Thu)

Time: 14:00-15:15

Venue: E21-G002

Language: English

Abstract: How large are the effects of artificial intelligence (AI) on labor productivity and unemployment? We develop a labor-search model of technological unemployment where AI learns from workers, raises productivity, and displaces them if renegotiation fails. The model admits three steady states: no AI; some AI with limited capability, more job creation but higher unemployment; unbounded AI with endogenous growth and employment gains. Calibrated to U.S. data, the some-AI state implies a threefold productivity gain but a 23% employment loss, half within five years. For plausible parameter values, the model generates global and local indeterminacy with endogenous cycles in productivity and unemployment, underscoring the uncertainty of AI’s impacts in line with a wide range of empirical findings. In the unbounded-AI state, employment rises modestly. Equilibria are inefficient despite the Hosios condition. Subsidizing jobs at risk of AI displacement is constrained optimal, raising welfare by 26.6% in the short run and more than 50% in the long run.