From Text to Self: Users' Perceptions of Potential of AI on Interpersonal Communication and Self
CoRR(2023)
摘要
In the rapidly evolving landscape of AI-mediated communication (AIMC), tools
powered by Large Language Models (LLMs) are becoming integral to interpersonal
communication. Employing a mixed-methods approach, we conducted a one-week
diary and interview study to explore users' perceptions of these tools' ability
to: 1) support interpersonal communication in the short-term, and 2) lead to
potential long-term effects. Our findings indicate that participants view AIMC
support favorably, citing benefits such as increased communication confidence,
and finding precise language to express their thoughts, navigating linguistic
and cultural barriers. However, the study also uncovers current limitations of
AIMC tools, including verbosity, unnatural responses, and excessive emotional
intensity. These shortcomings are further exacerbated by user concerns about
inauthenticity and potential overreliance on the technology. Furthermore, we
identified four key communication spaces delineated by communication stakes
(high or low) and relationship dynamics (formal or informal) that
differentially predict users' attitudes toward AIMC tools. Specifically,
participants found the tool is more suitable for communicating in formal
relationships than informal ones and more beneficial in high-stakes than
low-stakes communication.
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