题　目：The Warmth Penalty: Recipient Resistance to Superior Feedback from Human-in-the-Loop Systems

嘉　宾：Mingyu Li, PhD Candidate, Hong Kong University of Science and Technology

主　持：范雪青, 助理教授, 上海交通大学

时　间：2025年10月10日（周五）13:30-15:00

地　点：上海交通大学 徐汇校区安泰楼A305室

内容简介:

Using Artificial Intelligence to give feedback to people raises novel ethical concerns. Potential solutions are to include a human in the process and to explicitly disclose the use of AI, both of which are meant to foster trust with recipients of the feedback. We provide evidence from three pre-registered experiments (N = 3,005) showing that both of these solutions can backfire. While human-in-the-loop (HITL) leads to objectively better feedback, as judged by people blind to the feedback source, disclosing AI involvement significantly diminishes perceived warmth and trust in the sender, suggesting that human oversight does not automatically confer relational benefits. Engineering AI to generate more positive feedback and implementing substantial human engagement can elevate HITL systems’ perceived warmth and trustworthiness to levels comparable with human-only feedback.

演讲人简介：

Mingyu Li is a Ph.D. candidate in Management at the Hong Kong University of Science and Technology. Her research examines how employees perceive and respond to Artificial Intelligence (AI) in managerial roles, and how organizations can design interventions to foster effective Human-AI collaboration using field studies, laboratory experiments, and mixed-methods approaches. Her work has been published in leading journals including the Journal of Applied Psychology.

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