论文标题
迁移的AI：调查用户对对话AI代理的身份和信息迁移的影响
Migratable AI : Investigating users' affect on identity and information migration of a conversational AI agent
论文作者
论文摘要
会话AI代理人无处不在，并在我们的日常活动中为我们提供帮助。近年来，研究人员探索了这些代理在不同实施方案中的迁移，以保持任务的连续性并改善用户体验。在本文中，我们在迁移参数的不同配置中调查了用户的情感响应。我们使用信息迁移和身份迁移作为参数，在基于任务的方案中提出了2x2个受试者之间的研究。我们概述了研究期间收集的视频录像的影响处理管道，并在每种情况下报告用户的响应。我们的结果表明，当信息和身份迁移时，用户报告了最高的欢乐，并且最令人惊讶。并报道了当信息未经其代理人身份迁移而迁移时最多的愤怒。
Conversational AI agents are becoming ubiquitous and provide assistance to us in our everyday activities. In recent years, researchers have explored the migration of these agents across different embodiments in order to maintain the continuity of the task and improve user experience. In this paper, we investigate user's affective responses in different configurations of the migration parameters. We present a 2x2 between-subjects study in a task-based scenario using information migration and identity migration as parameters. We outline the affect processing pipeline from the video footage collected during the study and report user's responses in each condition. Our results show that users reported highest joy and were most surprised when both the information and identity was migrated; and reported most anger when the information was migrated without the identity of their agent.
