G2TT
来源类型Discussion paper
规范类型论文
来源IDDP17221
DP17221 Artificial Intelligence as Self-Learning Capital
Hans Gersbach; Evgenij Komarov; Richard von Maydell
发表日期2022-04-14
出版年2022
语种英语
摘要We model Artificial Intelligence (AI) as self-learning capital: Its productivity rises by its use and by training with data. In a three-sector model, an AI sector and an applied research (AR) sector produce intermediates for a final good firm and compete for high-skilled workers. AR development benefits from inter-temporal spillovers and knowledge spillovers of agents working in AI, and AI benefits from application gains through its use in AR. The economy converges to a steady state and displays a sequence of four tipping points in the transition: First, entrepreneurs and second, high-skilled workers drive the accumulation of self-learning AI, which will later be re-balanced by reverse movements to the AR sector (third and fourth). In the steady state, AI accumulates autonomously due to application gains from AR. We show that suitable tax policies induce socially optimal movements of workers between sectors. In particular, we provide a macroeconomic rationale for an AI-tax on AI-producing firms, once the accumulation of AI has sufficiently progressed.
主题Industrial Organization ; Macroeconomics and Growth ; Organizational Economics ; Public Economics
关键词Applied research Artificial intelligence Growth Labor market transitions Learning capital Tech giants
URLhttps://cepr.org/publications/dp17221
来源智库Centre for Economic Policy Research (United Kingdom)
资源类型智库出版物
条目标识符http://119.78.100.153/handle/2XGU8XDN/546220
推荐引用方式
GB/T 7714
Hans Gersbach,Evgenij Komarov,Richard von Maydell. DP17221 Artificial Intelligence as Self-Learning Capital. 2022.
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