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来源类型 | Report |
规范类型 | 报告 |
DOI | https://doi.org/10.7249/RRA812-1 |
来源ID | RR-A812-1 |
Can Artificial Intelligence Help Improve Air Force Talent Management? An Exploratory Application | |
David Schulker; Nelson Lim; Luke J. Matthews; Geoffrey E. Grimm; Anthony Lawrence; Perry Shameem Firoz | |
发表日期 | 2021-01-19 |
出版年 | 2021 |
语种 | 英语 |
结论 |
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摘要 | Both private and public organizations are increasingly taking advantage of improvements in computing power, data availability, and analytic capabilities to improve business processes. These trends have prompted U.S. Department of Defense policymakers to become more interested in whether adopting data-enabled methods would facilitate more-effective management of department personnel. In this report, RAND researchers explore one such application that would enable the U.S. Air Force to leverage existing data for improved human resource management (HRM) policies and practices. Specifically, the researchers develop a performance-scoring system that uses artificial intelligence (AI) and machine learning, which would enable the expanded use of performance narratives in HRM processes. The main purpose of this report is to serve as a worked example (i.e., a step-by-step solution to a problem) for Air Force policymakers as they consider how to approach the potential ways in which AI can improve HRM processes. |
目录 |
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主题 | Machine Learning ; Military Personnel ; United States Air Force ; Workforce Management |
URL | https://www.rand.org/pubs/research_reports/RRA812-1.html |
来源智库 | RAND Corporation (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/524336 |
推荐引用方式 GB/T 7714 | David Schulker,Nelson Lim,Luke J. Matthews,et al. Can Artificial Intelligence Help Improve Air Force Talent Management? An Exploratory Application. 2021. |
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 | ||
RAND_RRA812-1.pdf(2555KB) | 智库出版物 | 限制开放 | CC BY-NC-SA | 浏览 | ||
x1611062642072.jpg.p(3KB) | 智库出版物 | 限制开放 | CC BY-NC-SA | 浏览 |
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