On the Design of and Interaction with Conversational Agents: An Organizing and Assessing Review of Human-Computer Interaction Research
Conversational agents (CAs), described as software with which humans interact through natural language, have increasingly attracted interest in both academia and practice, due to improved capabilities driven by advances in artificial intelligence and, specifically, natural language processing. CAs are used in contexts like people’s private life, education, and healthcare, as well as in organizations, to innovate and automate tasks, for example in marketing and sales or customer service. In addition to these application contexts, such agents take on different forms concerning their embodiment, the communication mode, and their (often human-like) design. Despite their popularity, many CAs are not able to fulfill expectations and to foster a positive user experience is a challenging endeavor. To better understand how CAs can be designed to fulfill their intended purpose, and how humans interact with them, a multitudes of studies focusing on human-computer interaction have been carried out. These have contributed to our understanding of this technology. However, currently a structured overview of this research is missing, which impedes the systematic identification of research gaps and knowledge on which to build on in future studies. To address this issue, we have conducted an organizing and assessing review of 262 studies, applying a socio-technical lens to analyze CA research regarding theuser interaction, context, agent design, as well as perception and outcome. We contribute an overview of the status quo of CA research, identify four research streams through a cluster analysis, and propose a research agenda comprising six avenues and sixteen directions to move the field forward.