Conversational AI (CAI) systems which encompass voice- and text-based assistants are on the rise and have been largely integrated into people's everyday lives. Despite their widespread adoption, users voice concerns regarding privacy, security and trust in these systems. However, the composition of these perceptions, their impact on technology adoption and usage and the relationship between privacy, security and trust perceptions in the CAI context remain open research challenges. This study contributes to the field by conducting a Systematic Literature Review and offers insights into the current state of research on privacy, security and trust perceptions in the context of CAI systems. The review covers application fields and user groups and sheds light on empirical methods and tools used for assessment. Moreover, it provides insights into the reliability and validity of privacy, security and trust scales, as well as extensively investigating the subconstructs of each item as well as additional concepts which are concurrently collected. We point out that the perceptions of trust, privacy and security overlap based on the subconstructs we identified. While the majority of studies investigate one of these concepts, only a few studies were found exploring privacy, security and trust perceptions jointly. Our research aims to inform on directions to develop and use reliable scales for users' privacy, security and trust perceptions and contribute to the development of trustworthy CAI systems.

翻译：对话式AI（CAI）系统——涵盖语音和文本交互的智能助手——正日益普及并深度融入人们的日常生活。尽管应用广泛，用户仍对这类系统的隐私、安全与信任问题表达关切。然而，这些感知的构成要素、其对技术采纳与使用行为的影响，以及隐私、安全与信任感知在CAI语境下的相互关系，仍是未解决的研究挑战。本研究通过系统文献综述方法，揭示了CAI系统情境下隐私、安全与信任感知研究的当前进展。综述覆盖了应用领域与用户群体，梳理了评估所采用的实证方法及工具。此外，研究深入剖析了隐私、安全与信任量表的信度与效度，详细考察了各构念的子维度及同步采集的相关概念。基于识别的子维度，我们发现信任、隐私与安全感知存在重叠。尽管多数研究聚焦单一概念，仅有少数研究联合探讨了隐私、安全与信任感知。本研究旨在为开发可靠测量用户隐私、安全与信任感知的量表提供方向指引，并助力可信CAI系统的建设。