AI's Macroeconomic Impact: Modest Productivity Gains, Uneven Wage Effects

The paper analyzes the macroeconomic implications of AI, focusing on its effects on productivity, wages, and income inequality. The analysis suggests that AI's impact on total factor productivity (TFP) is likely to be modest, with projected gains of no more than 0.66% over 10 years. This estimate is based on a task-based model that considers both automation and task complementarities. The paper argues that even these modest gains could be exaggerated due to the challenges associated with learning hard-to-learn tasks, where context-dependent factors and the absence of objective outcome measures can hinder successful performance. The analysis also explores AI's potential effects on wages and income inequality. While AI may improve the productivity of low-skill workers in certain tasks, this may not necessarily reduce inequality. In fact, the paper suggests that AI advances are likely to widen the gap between capital and labor income. Finally, the paper acknowledges that some AI applications may have negative social value, such as algorithms for online manipulation, and discusses how to incorporate these effects into macroeconomic assessments.

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