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IACM 2023

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How Perceived Lack of Benevolence Harms Trust of Algorithmic Management

Across four pre-registered experiments, we demonstrate that benevolence is an important, but previously neglected, predictor of trust in algorithmic management. We demonstrate that perceived benevolence of algorithmic managers is significantly lower than that of human managers, which harms trust in algorithmic management, and that these effects are robust when we control for perceived ability and integrity. Although individuals frequently attribute abusive working conditions to algorithmic management, we disentangle the effects of abusive management and algorithmic management. We find that algorithmic and human managers are equally distrusted in abusive work environments, but in supportive work environments, algorithmic managers are seen as lower in benevolence and trusted less than human managers. Combined, these findings deepen our understanding of trust and provide practical advice on the adoption of algorithmic management.

Mingyu Li
The Hong Kong University of Science and Technology

T. Bradford Bitterly
The Hong Kong University of Science and Technology
Hong Kong


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