Paper Number
ICIS2025-1924
Paper Type
Complete
Abstract
This study investigates how voice tone and visual instructions in augmented reality (AR) influence AI-guided diagnosis. Drawing on the instructional design literature and dual-coding theory, two experiments examined the effects of dominant versus submissive-toned AI verbalizations, and schematic versus structural AR. The results revealed that dominance-toned AI instructions generally improved diagnostic completion, particularly when paired with structural AR. Experiment 2 identified cognitive effort and confused emotions as mediating mechanisms, with user attitudes toward AI moderating these effects. This study contributes to HCI and IS by highlighting the importance of processing consistency across verbal and visual modalities and by integrating physical and digital interaction design. It offers novel insights into AR design and multimodal communication, emphasizing the cognitive-emotional dynamics of AI-guided diagnosis.
Recommended Citation
Hong, Zeyuan (Stephen); Choi, Ben; and Boh, Waifong, "Command or Collaborate in Augmented Reality? Investigating Voice Tone and Visual Instruction in Augmented Reality Human-AI Diagnosis" (2025). ICIS 2025 Proceedings. 6.
https://aisel.aisnet.org/icis2025/imm_tech/imm_tech/6
Command or Collaborate in Augmented Reality? Investigating Voice Tone and Visual Instruction in Augmented Reality Human-AI Diagnosis
This study investigates how voice tone and visual instructions in augmented reality (AR) influence AI-guided diagnosis. Drawing on the instructional design literature and dual-coding theory, two experiments examined the effects of dominant versus submissive-toned AI verbalizations, and schematic versus structural AR. The results revealed that dominance-toned AI instructions generally improved diagnostic completion, particularly when paired with structural AR. Experiment 2 identified cognitive effort and confused emotions as mediating mechanisms, with user attitudes toward AI moderating these effects. This study contributes to HCI and IS by highlighting the importance of processing consistency across verbal and visual modalities and by integrating physical and digital interaction design. It offers novel insights into AR design and multimodal communication, emphasizing the cognitive-emotional dynamics of AI-guided diagnosis.
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