Evaluating human resources management literacy: A performance analysis of ChatGPT and bard

被引:4
|
作者
Raman, Raghu [1 ,2 ]
Venugopalan, Murale [1 ]
Kamal, Anju [1 ]
机构
[1] Amrita Vishwa Vidyapeetham, Amrita Sch Business, Amritapuri, India
[2] Amrita Sch Business, Amritapuri, India
关键词
Human resource management; LLM; Generative AI; Text mining; HR policy; Hiring; Ethics; Managerial decisions; ARTIFICIAL-INTELLIGENCE;
D O I
10.1016/j.heliyon.2024.e27026
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
This study presents a comprehensive analysis comparing the literacy levels of two Generative Artificial Intelligence (GAI) tools, ChatGPT and Bard, using a dataset of 134 questions from the Human Resources (HR) domain. The generated responses are evaluated for accuracy, relevance, and clarity. We find that ChatGPT outperforms Bard in overall accuracy (84.3% vs. 82.8%). This difference in performance suggests that ChatGPT could serve as a robotic advisor in transactional HR roles. In contrast, Bard may possess additional safeguards against misuse in the HR function, making it less capable of generating responses to certain types of questions. Statistical tests reveal that although the two systems differ in their mean accuracy, relevance, and clarity of the responses, the observed differences are not always statistically significant, implying that both tools may be more complementary than competitive. The Pearson correlation coefficients further support this by showing weak to non-existent relationships in performance metrics between the two tools. Confirmation queries don't improve ChatGPT or Bard's response accuracy. The study thus contributes to emerging research on the utility of GAI tools in Human Resources Management and suggests that involving certified HR professionals in the design phase could enhance underlying language model performance.
引用
收藏
页数:26
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