GENERATIVE AI: THE LIKELY EFFECTS ON PRODUCTIVITY, GROWTH, WAGES AND INEQUALITY

The invited policy session of the 79th Economic Policy panel meeting (4 April 2024) featured Daron Acemoglu of MIT presenting new analysis of claims about the supposedly large macroeconomic implications of advances in generative artificial intelligence. Using a task-based approach to assessing AI’s effects on productivity, his study concludes that the impact on GDP is likely to be modest.
The research then explores the wage and inequality effects of generative AI, concluding that even if generative AI increases productivity in various tasks, these are unlikely to translate into higher wages or lower inequality. Rather, more favorable wage and inequality effects will depend on the creation of new tasks for workers in general and, more specifically, for middle and low-pay workers. Finally, it is important to consider the negative social value of some new AI tasks, such as manipulative advertising, and their potential macroeconomic effects.
Following the presentation, there was a panel discussion featuring Benoît Cœuré, President of l’Autorité de la Concurrence – French competition authority, and David Hémous, Associate Professor at the University of Zurich and Affiliated Professor at UBS Center for Economics in Society. Moderated by Tim Phillips of CEPR.