Is AI Better Than Human in Identifying High-Potential Talents? A Quasi-Field Experiment Emergent Research Forum (ERF)

被引:0
|
作者
Cheng, Yihang [1 ]
Zhang, Xi [1 ]
Tang, Xinlin [2 ]
Zhu, Hengshu [3 ]
机构
[1] Tianjin Univ, Tianjin, Peoples R China
[2] Florida State Univ, Tallahassee, FL 32306 USA
[3] Baidu Inc, Beijing, Peoples R China
基金
中国国家自然科学基金; 国家重点研发计划;
关键词
AI effectiveness; high-potential talent identification; quasi-field experiment; difference-in-difference; ANALYTICS;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
With the advent of HR 3.0, Artificial Intelligence (AI) has been increasingly used in human resource (HR) management, including high-potential talent identification. Despite the increased adoption of AI in HR management, empirical evidence about the effectiveness of AI in talent assessment and identification is still scant. Our research represents an initial attempt to address this research void. With empirical data collected from a leading high-tech company in China, we conduct a quasi-field experiment to explore how effective AI is in identifying high-potential talents. Our preliminary results indicate that AI can slightly outperform human managers in the initial screening of high-potential talents. However, the performance of the AI-identified employees is suboptimal to that of the final short-listed employees. These results provide support for AI's effectiveness in initial talent screening but raise concerns on using AI alone in talent identification. We wrap the paper up with discussions on the potential contribution and the planned extension.
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页数:5
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