Paper Type
Short
Paper Number
PACIS2026-1596
Description
As conversational AI becomes increasingly integrated into everyday digital environments, designing effective voice-based interactions has become an important challenge in human–AI interaction. In particular, the way conversational agents proactively guide users and structure interactions may strongly influence users’ perceived control and experience. These challenges may become especially important for users with attentional vulnerabilities, who may experience difficulties maintaining focus during digital interactions. This study investigates how AI proactivity and interaction structure influence user experience in voice-based conversational interactions. A mixed-design experiment with 24 participants examined the effects of three levels of AI proactivity (low, medium, high) and two interaction structures (step-by-step vs. freeform) on perceived intrusiveness, task effectiveness, and emotional support. The results suggest that step-by-step interaction structures may help reduce perceived intrusiveness while maintaining the benefits of proactive guidance. These findings provide practical implications for designing more manageable and supportive voice-based conversational systems.
Recommended Citation
Kim, Subin; Cui, Tingru; and Goncalves, Jorge, "Designing AI Voice Agents for Users with Attentional Vulnerabilities: The Role of Proactivity and Interaction Structure" (2026). PACIS 2026 Proceedings. 5.
https://aisel.aisnet.org/pacis2026/hci_robotic/hci_robotic/5
Designing AI Voice Agents for Users with Attentional Vulnerabilities: The Role of Proactivity and Interaction Structure
As conversational AI becomes increasingly integrated into everyday digital environments, designing effective voice-based interactions has become an important challenge in human–AI interaction. In particular, the way conversational agents proactively guide users and structure interactions may strongly influence users’ perceived control and experience. These challenges may become especially important for users with attentional vulnerabilities, who may experience difficulties maintaining focus during digital interactions. This study investigates how AI proactivity and interaction structure influence user experience in voice-based conversational interactions. A mixed-design experiment with 24 participants examined the effects of three levels of AI proactivity (low, medium, high) and two interaction structures (step-by-step vs. freeform) on perceived intrusiveness, task effectiveness, and emotional support. The results suggest that step-by-step interaction structures may help reduce perceived intrusiveness while maintaining the benefits of proactive guidance. These findings provide practical implications for designing more manageable and supportive voice-based conversational systems.
Comments
12-HCI