| 来源类型 | Working Paper |
| 规范类型 | 报告 |
| DOI | 10.3386/w25619 |
| 来源ID | Working Paper 25619 |
| Artificial Intelligence: The Ambiguous Labor Market Impact of Automating Prediction | |
| Ajay Agrawal; Joshua S. Gans; Avi Goldfarb | |
| 发表日期 | 2019-03-04 |
| 出版年 | 2019 |
| 语种 | 英语 |
| 摘要 | Recent advances in artificial intelligence are primarily driven by machine learning, a prediction technology. Prediction is useful because it is an input into decision-making. In order to appreciate the impact of artificial intelligence on jobs, it is important to understand the relative roles of prediction and decision tasks. We describe and provide examples of how artificial intelligence will affect labor, emphasizing differences between when automating prediction leads to automating decisions versus enhancing decision-making by humans. |
| 主题 | Labor Economics ; Labor Supply and Demand ; Development and Growth ; Innovation and R& ; D |
| URL | https://www.nber.org/papers/w25619 |
| 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/583293 |
| 推荐引用方式 GB/T 7714 | Ajay Agrawal,Joshua S. Gans,Avi Goldfarb. Artificial Intelligence: The Ambiguous Labor Market Impact of Automating Prediction. 2019. |
| 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 | ||
| w25619.pdf（273KB） | 智库出版物 | 限制开放 | CC BY-NC-SA | 浏览 | ||
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