As AI becomes more embedded in workplaces, it is shifting from a tool for efficiency to an active force in organizational decision-making. Whether due to anthropomorphism or intentional design choices, people often assign human-like qualities, including gender, to AI systems. However, how AI managers are perceived in comparison to human managers and how gender influences these perceptions remains uncertain. To investigate this, we conducted randomized controlled trials (RCTs) where teams of three participants worked together under a randomly assigned manager. The manager was either a human or an AI and was presented as male, female, or gender-unspecified. The manager's role was to select the best-performing team member for an additional award. Our findings reveal that while participants initially showed no strong preference based on manager type or gender, their perceptions changed notably after experiencing the award process. As expected, those who received awards rated their managers as more trustworthy, competent, and fair, and they were more willing to work with similar managers in the future. In contrast, those who were not selected viewed them less favorably. However, male managers, whether human or AI, were more positively received by awarded participants, whereas female managers, especially female AI managers, faced greater skepticism and negative judgments when they did not give awards. These results suggest that gender bias in leadership extends beyond human managers to include AI-driven decision-makers as well. As AI assumes more managerial responsibilities, understanding and addressing these biases will be crucial for designing fair and effective AI management systems.

翻译：随着人工智能在工作场所的日益普及，其角色正从提升效率的工具转变为组织决策的主动参与者。无论是由于拟人化倾向还是刻意的设计选择，人们常常将包括性别在内的人类特质赋予AI系统。然而，与人类管理者相比，AI管理者如何被感知，以及性别如何影响这些感知，目前仍不明确。为探究此问题，我们开展了一项随机对照试验：由三名参与者组成的团队在随机分配的管理者领导下协作。管理者可能是人类或AI，并被标识为男性、女性或未指定性别。管理者的职责是选出表现最佳的团队成员授予额外奖励。研究发现，尽管参与者最初对管理者类型或性别未表现出明显偏好，但在经历奖励分配过程后，其感知发生了显著变化。如预期所示，获得奖励的参与者认为其管理者更可信、更有能力且更公平，并更愿意在未来与同类管理者共事。相反，未获奖励的参与者对管理者的评价则较为负面。值得注意的是，无论是人类还是AI，男性管理者在获奖参与者中获得更积极的评价；而女性管理者——特别是女性AI管理者——在未授予奖励时面临更多质疑与负面评判。这些结果表明，领导力中的性别偏见已从人类管理者延伸至AI决策者。随着AI承担更多管理职责，理解并应对这些偏见对于设计公平有效的AI管理系统至关重要。