| 来源类型 | Discussion paper |
| 规范类型 | 论文 |
| 来源ID | DP17221 |
| 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 |
| URL | https://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. |
| 条目包含的文件 | 条目无相关文件。 | |||||
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