Saving face: Leveraging artificial intelligence‐based negative feedback to enhance employee job performance
研究基于调节焦点理论，发现对于害怕丢脸的员工，AI提供的负面反馈能激发学习动机、减少人际反刍，从而提升工作绩效。
Abstract Negative performance feedback is vital for stimulating employees to enhance their performance despite resulting in stress and adverse work outcomes. Fortunately, artificial intelligence (AI)‐enabled automated agents have gradually assumed certain functions led by human leaders, such as providing feedback. Drawing from regulatory focus theory, we propose that AI‐based feedback systems can serve as a “remediation” tool, effectively mitigating employees' apprehensions about receiving negative feedback. In two studies, we found that for employees who fear losing face, AI‐based negative feedback motivates promotion‐focused cognition—motivation to learn—representing a learning mechanism to promote job performance and impedes their prevention‐focused cognition—interpersonal rumination—reducing the depletion needed for job performance. These findings present novel perspectives on using AI in performance feedback.