Youjin Hwang

Sora Kang, Youjin Hwang, Joonhwan Lee

Intergenerational linguistic differences pose challenges to effective and intimate family communication. This paper presents GenSync, a chat-based interface that supports intergenerational understanding through different forms of translation visibility. We conducted a controlled within-subjects study with 16 family dyads (32 participants), comparing three conditions: no translation, black-box translation, and transparent translation that displays both original and interpreted messages. The results show that translation visibility plays a critical role in shaping conversational experiences. Transparent translation supported conversational quality, intimacy, and usability, while black-box translation often disrupted conversational flow. These findings position intergenerational language support as a form of interpretive mediation and contribute design implications for AI-mediated communication in socially sensitive contexts.

Hyeok Kim, Youjin Hwang, Jieun Lee et al.

The lack of reliable, personalized information often complicates sexual violence survivors' support-seeking. Recently, there is an emerging approach to conversational information systems for support-seeking of sexual violence survivors, featuring personalization with wide availability and anonymity. However, a single best solution might not exist as sexual violence survivors have different needs and purposes in seeking support channels. To better envision conversational support-seeking systems for sexual violence survivors, we explore personalization trade-offs in designing such information systems. We implement a high-fidelity prototype dialogue-based information system through four design workshop sessions with three professional caregivers and interviewed with four self-identified survivors using our prototype. We then identify two forms of personalization trade-offs for conversational support-seeking systems: (1) specificity and sensitivity in understanding users and (2) relevancy and inclusiveness in providing information. To handle these trade-offs, we propose a reversed approach that starts from designing information and inclusive tailoring that considers unspecified needs, respectively.

Youjin Hwang, Donghoon Shin, Sion Baek et al.

Conversational agents have been showing lots of opportunities in healthcare by taking over a lot of tasks that used to be done by a human. One of the major functions of conversational healthcare agent is intervening users' daily behaviors. In this case, forming an intimate and trustful relationship with users is one of the major issues. Factors affecting human-agent relationship should be deeply explored to improve long-term acceptance of healthcare agent. Even though a bunch of ideas and researches have been suggested to increase the acceptance of conversational agents in healthcare, challenges still remain. From the preliminary work we conducted, we suggest an idea of applying the personas of users' family members and the doctor who are in the relationship with users in the real world as a solution for forming the rigid relationship between humans and the chatbot.