Working Paper: NBER ID: w23928
Authors: Philippe Aghion; Benjamin F. Jones; Charles I. Jones
Abstract: This paper examines the potential impact of artificial intelligence (A.I.) on economic growth. We model A.I. as the latest form of automation, a broader process dating back more than 200 years. Electricity, internal combustion engines, and semiconductors facilitated automation in the last century, but A.I. now seems poised to automate many tasks once thought to be out of reach, from driving cars to making medical recommendations and beyond. How will this affect economic growth and the division of income between labor and capital? What about the potential emergence of “singularities” and “superintelligence,” concepts that animate many discussions in the machine intelligence community? How will the linkages between A.I. and growth be mediated by firm-level considerations, including organization and market structure? The goal throughout is to refine a set of critical questions about A.I. and economic growth and to contribute to shaping an agenda for the field. One theme that emerges is based on Baumol’s “cost disease” insight: growth may be constrained not by what we are good at but rather by what is essential and yet hard to improve.
Keywords: Artificial Intelligence; Economic Growth; Automation
JEL Codes: O30; O40
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| AI increases the automation of production tasks (L23) | economic growth (O49) |
| AI automates the production of new ideas (O31) | increased growth rates (O40) |
| Automation has historically driven economic growth (O49) | economic growth (O49) |
| Baumol's cost disease constrains growth despite advancements in automation (O49) | economic growth (O49) |
| Constancy of growth rates and capital shares (F62) | disruption by AI (C69) |