As artificial intelligence (AI) advances, human-AI collaboration has become increasingly prevalent across both professional and everyday settings. In such collaboration, AI can express its confidence level about its performance, serving as a crucial indicator for humans to evaluate AI's suggestions. However, AI may exhibit overconfidence or underconfidence--its expressed confidence is higher or lower than its actual performance--which may lead humans to mistakenly evaluate AI advice. Our study investigates the influences of AI's overconfidence and underconfidence on human trust, their acceptance of AI suggestions, and collaboration outcomes. Our study reveal that disclosing AI confidence levels and performance feedback facilitates better recognition of AI confidence misalignments. However, participants tend to withhold their trust as perceiving such misalignments, leading to a rejection of AI suggestions and subsequently poorer performance in collaborative tasks. Conversely, without such information, participants struggle to identify misalignments, resulting in either the neglect of correct AI advice or the following of incorrect AI suggestions, adversely affecting collaboration. This study offers valuable insights for enhancing human-AI collaboration by underscoring the importance of aligning AI's expressed confidence with its actual performance and the necessity of calibrating human trust towards AI confidence.

翻译：随着人工智能（AI）的进步，人机协作在专业与日常场景中日益普遍。此类协作中，AI可表达其对自身表现的置信水平，这成为人类评估AI建议的关键指标。然而，AI可能表现出过度自信或自信不足——其表达的置信度高于或低于实际表现——这可能导致人类错误评估AI建议。本研究探讨AI过度自信与自信不足对人类信任、建议采纳及协作结果的影响。研究发现，公开AI置信水平与表现反馈有助于人们更好地识别AI置信度的偏差。然而，参与者在感知此类偏差时会克制信任，导致拒绝AI建议，进而使协作任务表现下降。反之，在缺乏此类信息时，参与者难以识别偏差，从而可能忽视正确建议或采纳错误建议，对协作产生负面影响。本研究通过强调对齐AI表达置信度与实际表现的重要性，以及校准人类对AI置信度信任的必要性，为增强人机协作提供了宝贵见解。