  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.
