| 来源类型 | Working Paper |
| 规范类型 | 报告 |
| DOI | 10.3386/w27736 |
| 来源ID | Working Paper 27736 |
| Hiring as Exploration | |
| Danielle Li; Lindsey R. Raymond; Peter Bergman | |
| 发表日期 | 2020-08-31 |
| 出版年 | 2020 |
| 语种 | 英语 |
| 摘要 | This paper views hiring as a contextual bandit problem: to find the best workers over time, firms must balance “exploitation” (selecting from groups with proven track records) with “exploration” (selecting from under-represented groups to learn about quality). Yet modern hiring algorithms, based on “supervised learning” approaches, are designed solely for exploitation. Instead, we build a resume screening algorithm that values exploration by evaluating candidates according to their statistical upside potential. Using data from professional services recruiting within a Fortune 500 firm, we show that this approach improves the quality (as measured by eventual hiring rates) of candidates selected for an interview, while also increasing demographic diversity, relative to the firm's existing practices. The same is not true for traditional supervised learning based algorithms, which improve hiring rates but select far fewer Black and Hispanic applicants. In an extension, we show that exploration-based algorithms are also able to learn more effectively about simulated changes in applicant hiring potential over time. Together, our results highlight the importance of incorporating exploration in developing decision-making algorithms that are potentially both more efficient and equitable. |
| 主题 | Microeconomics ; Economics of Information ; Labor Economics ; Labor Supply and Demand ; Other ; Accounting, Marketing, and Personnel ; Development and Growth ; Innovation and R& ; D |
| URL | https://www.nber.org/papers/w27736 |
| 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/585408 |
| 推荐引用方式 GB/T 7714 | Danielle Li,Lindsey R. Raymond,Peter Bergman. Hiring as Exploration. 2020. |
| 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 | ||
| w27736.pdf（953KB） | 智库出版物 | 限制开放 | CC BY-NC-SA | 浏览 | ||
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