Paper Type
Short
Paper Number
1319
Description
With advancements in artificial intelligence technology, chatbots have the potential to emulate memory-like functionality akin to that of humans. Memory plays a crucial role in relationship-building and social-related behaviors. However, limited research has explored how the memory function of chatbots affects human-chatbot relationships. Drawing on social exchange theory, this study investigates how memory-enabled chatbots impact user self-disclosure through two essential mechanisms: perceived closeness and privacy concerns. In addition, we propose that information transparency can moderate the effects of memory on privacy concerns. We propose an experimental study with a longitudinal design. This paper introduces novel perspectives for research on social chatbots by informing the development of socially adept chatbots that foster meaningful human-chatbot relationships while safeguarding user privacy.
Recommended Citation
Xing, Yan; Peng, Xixian; Choi, Ben; and Wang, Qiuzhen, "Memory in the Chatbot: An Integrated Perspective of Human-Chatbot Relationship and Privacy Concerns" (2024). PACIS 2024 Proceedings. 6.
https://aisel.aisnet.org/pacis2024/track13_hcinteract/track13_hcinteract/6
Memory in the Chatbot: An Integrated Perspective of Human-Chatbot Relationship and Privacy Concerns
With advancements in artificial intelligence technology, chatbots have the potential to emulate memory-like functionality akin to that of humans. Memory plays a crucial role in relationship-building and social-related behaviors. However, limited research has explored how the memory function of chatbots affects human-chatbot relationships. Drawing on social exchange theory, this study investigates how memory-enabled chatbots impact user self-disclosure through two essential mechanisms: perceived closeness and privacy concerns. In addition, we propose that information transparency can moderate the effects of memory on privacy concerns. We propose an experimental study with a longitudinal design. This paper introduces novel perspectives for research on social chatbots by informing the development of socially adept chatbots that foster meaningful human-chatbot relationships while safeguarding user privacy.
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