人机交互中感知的力量：探究塑造用户信念与行为的心理因素和认知偏差
The Power of Perception in Human-AI Interaction: Investigating Psychological Factors and Cognitive Biases that Shape User Belief and Behavior
AI总结：
本研究通过两项涉及238名参与者的实验，探究了影响用户对AI预测信任的心理因素，揭示了“理性迷信”现象及预测效价对用户感知的强烈影响，为开发能管理用户期望与平衡信任的AI系统提供了见解。
摘要：
本论文调查了影响对AI预测信任的心理因素，将其与对占星术和基于性格的预测的信任进行了比较，并在AI（特别是大型语言模型（LLMs））的背景下考察了“个人验证效应”。通过两项涉及238名参与者的相互关联的研究，第一项研究探讨了认知风格、超自然信仰、AI态度和性格特征如何影响人们对来自不同来源预测的有效性、可靠性、有用性和个性化的感知。研究发现，对AI预测的信任与对占星术和基于性格的预测的信任之间存在正相关，突显了一种“理性迷信”现象，即信任更多受心理启发式和直觉的影响，而非批判性评估。有趣的是，认知风格并未显著影响对预测的信任，而超自然信仰、积极的AI态度和尽责性发挥了显著作用。第二项研究揭示，积极预测被认为在有效性、个性化、可靠性和有用性方面显著高于消极预测，强调了预测效价对用户感知的强烈影响。这凸显了AI系统管理用户期望和培养平衡信任的必要性。论文最后提出未来研究建议，探讨对AI预测的信任如何通过自我实现预言的视角影响实际用户行为。总体而言，本论文增强了对人机交互的理解，并为在各种应用中开发AI系统提供了见解。
英文摘要：
This thesis investigates the psychological factors that influence belief in AI predictions, comparing them to belief in astrology- and personality-based predictions, and examines the "personal validation effect" in the context of AI, particularly with Large Language Models (LLMs). Through two interconnected studies involving 238 participants, the first study explores how cognitive style, paranormal beliefs, AI attitudes, and personality traits impact perceptions of the validity, reliability, usefulness, and personalization of predictions from different sources. The study finds a positive correlation between belief in AI predictions and belief in astrology- and personality-based predictions, highlighting a "rational superstition" phenomenon where belief is more influenced by mental heuristics and intuition than by critical evaluation. Interestingly, cognitive style did not significantly affect belief in predictions, while paranormal beliefs, positive AI attitudes, and conscientiousness played significant roles. The second study reveals that positive predictions are perceived as significantly more valid, personalized, reliable, and useful than negative ones, emphasizing the strong influence of prediction valence on user perceptions. This underscores the need for AI systems to manage user expectations and foster balanced trust. The thesis concludes with a proposal for future research on how belief in AI predictions influences actual user behavior, exploring it through the lens of self-fulfilling prophecy. Overall, this thesis enhances understanding of human-AI interaction and provides insights for developing AI systems across various applications.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
