人格与观点一致性在人机交互中的影响
Effects of Personality- and Opinion-Alignment in Human-AI Interaction
AI总结：
研究探讨了AI助手的人格和观点一致性如何影响用户交互结果和感知，发现观点一致性的AI更受信任和受欢迎，但人格一致性影响不显著。
摘要：
与AI助手的交互日益个性化。由于AI个性化是动态且由机器学习驱动的，我们对个性化如何影响交互结果和用户感知的理解有限。我们进行了一项大规模受控实验，1000名参与者与被提示采取特定人格特质和观点的AI助手互动。结果显示，参与者倾向于与观点一致的模型互动。参与者发现观点一致的模型更可信、有能力、温暖和有说服力，支持了AI相似性吸引力假说。相反，我们观察到AI人格一致性没有或只有弱影响，内向型模型被内向型参与者评为不那么可信和有能力。这些发现突显了观点一致性作为AI用户偏好的核心维度，同时强调了对AI个性化机制和风险的更深入讨论的必要性。
英文摘要：
Interactions with AI assistants are increasingly personalized to individual users. As AI personalization is dynamic and machine-learning-driven, we have limited understanding of how personalization affects interaction outcomes and user perceptions. We conducted a large-scale controlled experiment in which 1,000 participants interacted with AI assistants prompted to take on specific personality traits and opinions. Our results show that participants consistently preferred to interact with models that shared their opinions. Participants found opinion-aligned models more trustworthy, competent, warm, and persuasive, corroborating an AI-similarity-attraction hypothesis. In contrast, we observed no or only weak effects of AI personality alignment, with introvert models rated as less trustworthy and competent by introvert participants. These findings highlight opinion alignment as a central dimension of AI user preference, while underscoring the need for a more grounded discussion of the mechanisms and risks of AI personalization.
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。
