Abstract
The application of AI systems in Human Resource Management promises increasing objectivity of personnel decisions, decreasing administrative tasks for HR managers and automating HR decisions. Especially the application of algorithmic HRM, i.e. automating certain HRM practices by using algorithms, has been discussed as a way to fulfill HRM’s strategic potential. The behavioral response of workers to algorithmic HRM and its relationship to performance has not been investigated. We close this research gap by providing empirical evidence from a mixed-methods study conducting a lab experiment on an algorithmic personnel evaluation system. We find (a) experimental evidence for behavioral responses changing the underlying statistical relationships of algorithmic HRM with consequential effects on performance, (b) low acceptance of algorithmic HRM as well as attribution to human actors and (c) no relationship between attitudinal and behavioral responses to algorithmic HRM.
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