While the rise of AI has benefited professionals, it also induces technostress that threatens their expertise and jobs. To ensure the human-centered advancement of technology, a deep understanding of users technostress and how to cope with it is essential. Despite technostress having long been discussed, the growing integration of AI tools into professionals’ everyday work amplifies these challenges and calls for further exploration. Accordingly, this is a timely moment to examine their real-world experiences and voices. Thus, our study aims to investigate AI-induced technostress experienced by professionals, and the coping strategies they employ. Through focus group interviews with 19 professionals from diverse fields, we identified seven AI-induced technostressors and examined their coping strategies along two dimensions: stress Coping Style (problem-focused and emotion-focused) and Value Orientation (AI-oriented and humanness-oriented). Drawing on professionals’ coping strategies, we suggest practical implications to support users in coping with AI-induced technostress.

Visually impaired individuals face barriers in online shopping because product details are often conveyed through images, and alternative text is frequently insufficient. The recent advent of Computer-Using Agents (CUA) based on Large Multimodal Models, which can directly manipulate graphical user interfaces, offers new opportunities for such accessibility. However, there is a lack of research that considers how voice-based systems should be designed to support visually impaired users in complex online shopping contexts. Thus, our study qualitatively explores the experiences and needs of visually impaired users as they shop online through voice interaction with a CUA We conducted a Semi-Automatic Wizard-of-Oz study with 12 visually impaired participants, in which they performed shopping tasks with a voice-based CUA system, followed by debriefing interviews. This paper proposes design implications for creating a more inclusive and disability-centered online shopping environment with voice-based CUA for visually impaired users.

With the advent of neural networks, it has become possible to generate synthetic voices that are nearly indistinguishable from real human speech (i.e., human-sounding voice).In contrast, earlier voice assistants used voices that were instantly recognizable as machine-generated, owing to their standardized, consistent, and highly intelligible qualities (i.e., artificial-sounding voice).Although people tend to prefer human-like voices, adopting human-sounding voices in voice assistants raises ethical concerns related to confusion or unintentional deception, particularly in voice-only contexts, even when their identity as systems is explicitly disclosed.To explore the voice design direction for future voice assistants, we examined how participants perceived and interacted when they were unexpectedly confronted with either an artificial-sounding or a human-sounding voice, both of which clearly identified themselves as voice assistants during an everyday phone call.Our findings reveal participants' experiences and conversational behaviors in each voice condition.Furthermore, we discuss how the voices of voice assistants should be designed and propose design implications that emphasize transparency and responsiveness in voice design.

Geometric motion-based visual feedback widely used in existing voice assistants (VAs) plays a significant role in voice interactions. It enables a realtime and simultaneous depiction of VAs' conversational states, thereby mitigating the verbosity of speech and reducing unnecessary turn-taking. However, the study on VA visual feedback, which focuses on geometric motion graphics for different conversational states, has not been extensively explored. In this study, we systematically designed `Voicon', shape-based visual feedback, and explored the expandability of its visual language. To achieve this, we determined 3 conversational states through a literature review. We then conducted a conjoint analysis using the visual attributes extracted from a participatory design workshop. Based on the results, we proposed the Voicon system and created video prototypes for qualitative evaluation. Our findings demonstrated that our Voicon system is intuitively understandable and perceived as useful by users. We believe this pictorial enriches and expands the design space of visual feedback for VAs, which facilitates voice interaction.

Proactive voice assistants (VAs) in smart homes predict users’ needs and autonomously take action by controlling smart devices and initiating voice-based features to support users’ various activities. Previous studies on proactive systems have primarily focused on determining action based on contextual information, such as user activities, physiological state, or mobile usage. However, there is a lack of research that considers user agency in VAs’ proactive actions, which empowers users to express their dynamic needs and preferences and promotes a sense of control. Thus, our study aims to explore verbal communication through which VAs can proactively take action while respecting user agency. To delve into communication between a proactive VA and a user, we used the Wizard of Oz method to set up a smart home environment, allowing controllable devices and unrestrained communication. This paper proposes design implications for the communication strategies of proactive VAs that respect user agency.