| 来源类型 | Working Paper |
| 规范类型 | 报告 |
| DOI | 10.3386/w29996 |
| 来源ID | Working Paper 29996 |
| AI Adoption in a Competitive Market | |
| Joshua S. Gans | |
| 发表日期 | 2022-05-02 |
| 出版年 | 2022 |
| 语种 | 英语 |
| 摘要 | Economists have often viewed the adoption of artificial intelligence (AI) as a standard process innovation where we expect that efficiency will drive adoption in competitive markets. This paper models AI based on recent advances in machine learning that allow firms to engage in better prediction. Using prediction of demand, it is demonstrated that AI adoption is a complement to variable inputs whose levels are directly altered by predictions and use is economised by them (that is, labour). It is shown that, in a competitive market, this increases the short-run elasticity of supply and may or may not increase average equilibrium prices. There are generically externalities in adoption with this reducing the profits of non-adoptees when variable inputs are important and increasing them otherwise. Thus, AI does not operate as a standard process innovation and its adoption may confer positive externalities on non-adopting firms. In the long-run, AI adoption is shown to generally lower prices and raise consumer surplus in competitive markets. |
| 主题 | Microeconomics ; Households and Firms ; Market Structure and Distribution ; Economics of Information ; Development and Growth ; Innovation and R& ; D |
| URL | https://www.nber.org/papers/w29996 |
| 来源智库 | National Bureau of Economic Research (United States) |
| 引用统计 | |
| 资源类型 | 智库出版物 |
| 条目标识符 | http://119.78.100.153/handle/2XGU8XDN/587669 |
| 推荐引用方式 GB/T 7714 | Joshua S. Gans. AI Adoption in a Competitive Market. 2022. |
| 条目包含的文件 | ||||||
| 文件名称/大小 | 资源类型 | 版本类型 | 开放类型 | 使用许可 | ||
| w29996.pdf（280KB） | 智库出版物 | 限制开放 | CC BY-NC-SA | 浏览 | ||
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