Paper Number
ICIS2025-2694
Paper Type
Short
Abstract
Nowadys, generative AI-enabled humanoid robots are deployed for entertainment, assistance, and companionship. However, poorly designed robots may trigger user resistance and privacy-protective behaviors, ultimately undermining user experience. This study proposes two novel design features—gaze responsiveness and multimodal emotion expression consistency (MEEC)—to enhance user experience and examine their effects on self-disclosure and misrepresentation in the human-AI companion context. Using an experimental approach, we will manipulate these features and assess their impact in real-world settings. Drawing on surveillance theory and emotional contagion theory, we propose that both features enhance emotional contagion and perceived surveillance. Through cognitive and emotional mechanisms, these two features will lead to a sophisticated privacy-protective behaviour. By identifying how design features shape user privacy responses, our expected results can help understand privacy dynamics in human-AI interactions and also provide significant implications for the new shape and direction of generative AI-enabled humanoid robot services.
Recommended Citation
Wang, Zhiqi and Xu, David (Jingjun), "Can Gaze Responsiveness and Multimodal Emotion Expression Consistency Mitigate Privacy-Protective Behavior in the Digital Companion Context?" (2025). ICIS 2025 Proceedings. 21.
https://aisel.aisnet.org/icis2025/cyb_security/cyb_security/21
Can Gaze Responsiveness and Multimodal Emotion Expression Consistency Mitigate Privacy-Protective Behavior in the Digital Companion Context?
Nowadys, generative AI-enabled humanoid robots are deployed for entertainment, assistance, and companionship. However, poorly designed robots may trigger user resistance and privacy-protective behaviors, ultimately undermining user experience. This study proposes two novel design features—gaze responsiveness and multimodal emotion expression consistency (MEEC)—to enhance user experience and examine their effects on self-disclosure and misrepresentation in the human-AI companion context. Using an experimental approach, we will manipulate these features and assess their impact in real-world settings. Drawing on surveillance theory and emotional contagion theory, we propose that both features enhance emotional contagion and perceived surveillance. Through cognitive and emotional mechanisms, these two features will lead to a sophisticated privacy-protective behaviour. By identifying how design features shape user privacy responses, our expected results can help understand privacy dynamics in human-AI interactions and also provide significant implications for the new shape and direction of generative AI-enabled humanoid robot services.
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09-Cybersecurity