The Economic Benefits and Costs of AI and Policies to Mitigate AI’s Impact on Inequality
创建于 更新于
摘要
We develop a two-sector, three-labor-type model where AI is produced by labor and used in final goods production, yielding endogenous labor reallocation as AI productivity rises [page::2][page::3]. AI adoption creates a transition in which substitutable labor incomes fall in absolute and relative terms while complementary labor wages rise faster than GDP, and final goods labor tracks GDP one-for-one [page::2][page::3]. The model identifies threshold productivity levels that separate pre-AI, transition, and post-AI regimes; the wage ratio between complementary and substitutable labor depends only on AI productivity and AI-production intensity, not on relative labor supplies [page::3][page::10]. We analyze Pareto-improving tax and regulatory policies that share AI gains across workers, and show how outcomes differ under competitive AI production versus monopoly AI production [page::4][page::21]. The paper also extends to AI-in-AI production and to CES-type AI technologies, confirming robustness of the main qualitative results and highlighting how policy design must adapt as AI productivity evolves [page::30][page::31].
