Artificial Intelligence, Income Distribution and Economic Growth

Konferenzbeitrag

The economic impact of Artificial Intelligence (AI) is studied using a (semi) endogenous growth model with two novel features. First, the task approach from labor economics is reformulated and integrated into a growth model. Second, the standard represen- tative household assumption is rejected, so that aggregate demand restrictions can be introduced. With these novel features it is shown that (i) AI automation can decrease the share of labor income no matter the size of the elasticity of substitution between AI and labor, and (ii) when this elasticity is high, AI will unambiguously reduce aggre- gate demand and slow down GDP growth, even in the face of the positive technology shock that AI entails. If the elasticity of substitution is low, then GDP, productivity and wage growth may however still slow down, because the economy will then fail to benefit from the supply-side driven capacity expansion potential that AI can deliver. The model can thus explain why advanced countries tend to experience, despite much AI hype, the simultaneous existence of rather high employment with stagnating wages, productivity, and GDP.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Series: Beiträge zur Jahrestagung des Vereins für Socialpolitik 2020: Gender Economics

Classification and Topics

• Classification: Wirtschaft ; Empirical Studies of Economic Growth; Aggregate Productivity; Cross-Country Output Convergence ; Technological Change: Choices and Consequences; Diffusion Processes ; Human Capital; Skills; Occupational Choice; Labor Productivity ; Macroeconomics: Consumption; Saving; Wealth ; Aggregate Factor Income Distribution
• Subject: Technology ; artificial intelligence ; productivity ; labor demand ; income distribution ; growth theory

Contributors, Location and Time

• Event: Geistige Schöpfung
• (who): Gries, Thomas ; Naude, Wim
• Event: Veröffentlichung
• (who): ZBW - Leibniz Information Centre for Economics
• (where): Kiel, Hamburg
• (when): 2020

Further information

• Handle: http://hdl.handle.net/10419/224623
• Last update: 20.09.2024, 8:21 AM CEST