On March 10, 2025, the IESE New York Campus will host a discussion on The Economics of AI and the Future of Work, featuring Eduard Talamàs, Assistant Professor of Economics at IESE Business School and Research Fellow at CEPR. Talamàs will join Joan Jané, Dean of IESE's New York Campus, to explore the profound economic implications of modern AI.
This engaging conversation will showcase cutting-edge research by Eduard in collaboration with fellow IESE Professor Enrique Ide. Together, they analyze how AI is fundamentally different from previous automation, and its consequences for organizations and the labor market.
Discussion Highlights:
- AI vs. Previous Waves of Automation
Unlike traditional automation technologies, AI learns by example, uncovering patterns that cannot be easily codified into explicit rules. This unique property enables AI to scale tacit knowledge in ways that were previously impossible, fundamentally altering the structure of firms and labor markets.
AI agents can either operate autonomously (as co-workers or problem-solvers) or non-autonomously (only as assistants). Basic autonomous AI pushes humans toward more complex problem-solving, while advanced autonomous AI reallocates them back to routine knowledge work.
AI benefits different segments of the workforce in distinct ways. Autonomous AI disproportionately advantages highly knowledgeable individuals, while non-autonomous AI primarily benefits less knowledgeable workers by acting as an assistive tool.
- Policy and Regulatory Trade-offs
Regulating AI autonomy presents a key policy dilemma: balancing labor income inequality with overall economic output. Restricting AI autonomy can help protect less knowledgeable workers, but it may come at the cost of efficiency and productivity gains.
