Generative Artificial Intelligence and higher-paying jobs in an agent-based macroeconomic model

• Grant number: 25/02945-0
• Support Opportunities: Scholarships in Brazil - Master
• Start date: August 01, 2025
• End date: July 31, 2026
• Field of knowledge: Applied Social Sciences - Economics
• Principal Investigator: Lílian Nogueira Rolim
• Grantee: Paulo Henrique Messias
• Host Institution: Instituto de Economia (IE). Universidade Estadual de Campinas (UNICAMP). Campinas , SP, Brazil

Abstract

This research aims to explore the relation between technological progress and employment, considering the intellectual monopoly that characterizes generative artificial intelligence (GenAI). The research addresses a gap in the literature on Agent-Based Models (ABM), which lacks an approach that connects the microeconomic differences between intangible and tangible assets with the distinction between direct and indirect workers. The main hypothesis is that replacing higher-paying jobs with digital intangible assets accelerates technological unemployment and worsens income distribution. To test this, we build upon an ABM with Kaleckian features developed by Rolim, Baltar and Lima (2023), incorporating some elements of other models related to technological change and intangible assets. The literature review shows that this approach has not yet been taken, so this research can contribute to extend existing studies on the subject.