Journal of Management Information Systems

Volume 40 Number 4 2023 pp. 1039-1070

Perceived Fairness of Human Managers Compared with Artificial Intelligence in Employee Performance Evaluation

Qin, Shaojun (Marco), Jia, Nan, Luo, Xueming, Liao, Chengcheng, and Huang, Ziyao


Human managers are increasingly challenged by artificial intelligence (AI) technologies in performing managerial functions. We undertook a field experiment that used AI vis-à-vis human managers to perform structured, data-intensive evaluations of employee performance. We generate two sets of insights. First, employees considered AI to be both fairer and more accurate in evaluating their performance than the average human manager. Second, to catch up with AI, human managers’ fairness perceived by employees played a first-order role by (a) helping human managers, to a greater extent than those managers’ evaluation accuracy, to close the performance gap of the employees evaluated by them compared with that of those evaluated by AI, and (b) constraining the effect of human managers’ perceived accuracy of evaluations on employees’ performance. Thus, facing the competition from AI, it is all the more important for human managers to treat employees fairly and build positive interpersonal relationships with employees.

Key words and phrases: Artificial intelligence, employee performance, field experiments, performance evaluation