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Computer Science > Human-Computer Interaction

arXiv:2310.12459 (cs)
[Submitted on 19 Oct 2023]

Title:Affective Conversational Agents: Understanding Expectations and Personal Influences

Authors:Javier Hernandez, Jina Suh, Judith Amores, Kael Rowan, Gonzalo Ramos, Mary Czerwinski
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Abstract:The rise of AI conversational agents has broadened opportunities to enhance human capabilities across various domains. As these agents become more prevalent, it is crucial to investigate the impact of different affective abilities on their performance and user experience. In this study, we surveyed 745 respondents to understand the expectations and preferences regarding affective skills in various applications. Specifically, we assessed preferences concerning AI agents that can perceive, respond to, and simulate emotions across 32 distinct scenarios. Our results indicate a preference for scenarios that involve human interaction, emotional support, and creative tasks, with influences from factors such as emotional reappraisal and personality traits. Overall, the desired affective skills in AI agents depend largely on the application's context and nature, emphasizing the need for adaptability and context-awareness in the design of affective AI conversational agents.
Subjects: Human-Computer Interaction (cs.HC); Artificial Intelligence (cs.AI)
Cite as: arXiv:2310.12459 [cs.HC]
  (or arXiv:2310.12459v1 [cs.HC] for this version)
  https://doi.org/10.48550/arXiv.2310.12459

Submission history

From: Javier Hernandez [view email]
[v1] Thu, 19 Oct 2023 04:33:18 UTC (10,382 KB)
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