Along with the Fourth industrial revolution, the artificial intelligence (AI) technology is rapidly expanding and integrating into our daily lives. The interaction between human being and AI device is expected to have effects not only on psychological aspects such as subjective well-being and stress...
Along with the Fourth industrial revolution, the artificial intelligence (AI) technology is rapidly expanding and integrating into our daily lives. The interaction between human being and AI device is expected to have effects not only on psychological aspects such as subjective well-being and stress-level, but also on cognitive and behavioral aspects. This study aims to improve overall understandings of the 'human-AI device interaction' through both qualitative and quantitative research methods.
In study 1, in-depth interviews were conducted with those using AI speakers in order to explore the factors, which influence on the interactions from multiple perspectives (user-perspective, device- perspective, and contextual perspective). In study 2, 3, and 4, it is investigated if the identified factors of each perspective impact on user experiences of AI device.
By the study 1, forty-six factors were identified to affect interactions between user and AI device. Those factors were categorized into three perspectives (user-perspective, device- perspective, and contextual perspective).
In study 2, the research focused on the major factors from the user-perspective (e.g. demographics, emotional states, personality traits) investigating the effects on user experiences (e.g. satisfaction) out of using AI device. The results indicated that the user experienced higher satisfaction when the users are female and when the age
increases. The study also revealed that the overall satisfaction from using AI device significantly was augmented when the levels of loneliness, self-efficacy, and innovativeness (technological and hedonic) increase. Finally, the satisfaction of the user was positively associated with continuous intention to use AI device.
In study 3, the research concentrated on the factors from the device-perspective (e.g. AI’s self-disclosure, role of device, perceived intimacy). The study examined the effect of those factors on users’ cognitive and behavioral experiences under the lab-situated social interacting experiment. It proved that the intention of user’s self- disclosure was higher when AI device discloses more, and the effect was extended to the actual disclosing behavior. Moreover, the study also discovered a full mediation role of intimacy between user experiences and AI’s disclosure.
In study 4, the research conducted an experiment in the context of consuming AI’s curation service. The experiment was designed to explore the effect of AI’s self-disclosure, trustworthiness, and autonomy of users on the user experiences. The results explained that the dependence on AI was increased when AI device discloses more, and it also resulted in higher intention to accept AI’s recommendation.
The present research is expected to provide a comprehensive theoretical framework on the research of human-AI device interaction. As an incipient progress suggested by applying multiple research methods, it is also expected give a foundation to diversify the directions of AI research for future works. Last but not least, the results of the research would contribute not only to the practitioners of the AI industry, but to the users’ psychological well-beings (e.g. loneliness, stress).
Along with the Fourth industrial revolution, the artificial intelligence (AI) technology is rapidly expanding and integrating into our daily lives. The interaction between human being and AI device is expected to have effects not only on psychological aspects such as subjective well-being and stress-level, but also on cognitive and behavioral aspects. This study aims to improve overall understandings of the 'human-AI device interaction' through both qualitative and quantitative research methods.
In study 1, in-depth interviews were conducted with those using AI speakers in order to explore the factors, which influence on the interactions from multiple perspectives (user-perspective, device- perspective, and contextual perspective). In study 2, 3, and 4, it is investigated if the identified factors of each perspective impact on user experiences of AI device.
By the study 1, forty-six factors were identified to affect interactions between user and AI device. Those factors were categorized into three perspectives (user-perspective, device- perspective, and contextual perspective).
In study 2, the research focused on the major factors from the user-perspective (e.g. demographics, emotional states, personality traits) investigating the effects on user experiences (e.g. satisfaction) out of using AI device. The results indicated that the user experienced higher satisfaction when the users are female and when the age
increases. The study also revealed that the overall satisfaction from using AI device significantly was augmented when the levels of loneliness, self-efficacy, and innovativeness (technological and hedonic) increase. Finally, the satisfaction of the user was positively associated with continuous intention to use AI device.
In study 3, the research concentrated on the factors from the device-perspective (e.g. AI’s self-disclosure, role of device, perceived intimacy). The study examined the effect of those factors on users’ cognitive and behavioral experiences under the lab-situated social interacting experiment. It proved that the intention of user’s self- disclosure was higher when AI device discloses more, and the effect was extended to the actual disclosing behavior. Moreover, the study also discovered a full mediation role of intimacy between user experiences and AI’s disclosure.
In study 4, the research conducted an experiment in the context of consuming AI’s curation service. The experiment was designed to explore the effect of AI’s self-disclosure, trustworthiness, and autonomy of users on the user experiences. The results explained that the dependence on AI was increased when AI device discloses more, and it also resulted in higher intention to accept AI’s recommendation.
The present research is expected to provide a comprehensive theoretical framework on the research of human-AI device interaction. As an incipient progress suggested by applying multiple research methods, it is also expected give a foundation to diversify the directions of AI research for future works. Last but not least, the results of the research would contribute not only to the practitioners of the AI industry, but to the users’ psychological well-beings (e.g. loneliness, stress).
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