人力资源管理
计算机科学
路径(计算)
人类智力
问责
人力资源
资源配置
知识管理
管理科学
人工智能
经济
管理
政治学
计算机网络
程序设计语言
法学
作者
Prasanna Tambe,Peter Cappelli,Valery Yakubovich
标识
DOI:10.1177/0008125619867910
摘要
There is a substantial gap between the promise and reality of artificial intelligence in human resource (HR) management. This article identifies four challenges in using data science techniques for HR tasks: complexity of HR phenomena, constraints imposed by small data sets, accountability questions associated with fairness and other ethical and legal constraints, and possible adverse employee reactions to management decisions via data-based algorithms. It then proposes practical responses to these challenges based on three overlapping principles—causal reasoning, randomization and experiments, and employee contribution—that would be both economically efficient and socially appropriate for using data science in the management of employees.
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