Knowledge Transfer between Humans and Conversational Agents: A Review, Organizing Framework, and Future Directions
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Date
2023-01-03
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4556
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Conversational agents (CAs) that use natural language to interact with humans are becoming ubiquitous in our daily lives. For CAs to perform effectively, knowledge transfer between human users and CAs is vital to complete tasks and to build common understanding with humans. While such knowledge transfer is important, relatively less research attention has been paid to it. Overall, we lack a systematic overview of how knowledge transfer can be facilitated between humans and CAs. Motivated thus, this article presents a literature review of empirical IS, HCI and Communications studies on the knowledge transfer between humans and CAs. We analyzed papers on this topic, synthesized the studies based on the antecedents, directions, processes, and outcomes of knowledge transfer. We contribute by providing a systematic understanding of research on knowledge transfer in human-CA interactions, proposing an organizing framework, identifying gaps in prior work, and outlining key future research directions.
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Design and Appropriation of Knowledge and AI Systems, conversational agent, human-ai interaction, knowledge transfer, literature review, organizing framework
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10
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Proceedings of the 56th Hawaii International Conference on System Sciences
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Attribution-NonCommercial-NoDerivatives 4.0 International
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