This paper introduces Ethics Pathways, a design activity aimed at understanding HCI and design researchers' ethics engagements and flows during their research process. Despite a strong ethical commitment in these fields, challenges persist in grasping the complexity of researchers' engagement with ethics ---practices conducted to operationalize ethics---in situated institutional contexts. Ethics Pathways, developed through six playtesting sessions, offers a design approach to understanding the complexities of researchers' past ethics engagements in their work. This activity involves four main tasks: recalling ethical incidents; describing stakeholders involved in the situation; recounting their actions or speculative alternatives; and reflection and emotion walk-through. The paper reflects on the role of design decisions and facilitation strategies in achieving these goals. The design activity contributes to the discourse on ethical HCI research by conceptualizing ethics engagement as a part of ongoing research processing, highlighting connections between individual affective experiences, social interactions across power differences, and institutional goals.

DIS 2024

Creating datasets for ML is an inherently human endeavor, as the data's heterogeneity mandates human intervention. However, most data workflows being one-time and hardly transferable leads to a lack of standardization and reusability. There has been a push to impose more structure on the data work process, but little is known about the implicit or "tacit" knowledge of data workers, i.e., "know-how"s that is difficult to transfer to others. Identifying and formalizing this knowledge can help data work improve, leading it from current "exploration" to more systematic "engineering." We interviewed 19 ML practitioners in this study to find "why" they use "what" tacit knowledge. As a result, we identified the following themes: 1) data is context/situation dependent, 2) human workers are inseparable from data, and 3) models must be understood to build data. We finally discuss future systematic supports and research to convert what is implicit to explicit.

CHI 2023 LBW.

Voice-based Conversational Agents (VCA) have served as personal assistants that support individuals with special needs. Adolescents with Autism Spectrum Disorder (ASD) may also benefit from VCAs to deal with their everyday needs and challenges, ranging from self-care to social communications. In this study, we explored how VCAs could encourage adolescents with ASD in navigating various aspects of their daily lives through the two-week use of VCAs and a series of participatory design workshops. Our findings demonstrated that VCAs could be an engaging, empowering, emancipating tool that supports adolescents with ASD to address their needs, personalities, and expectations, such as promoting self-care skills, regulating negative emotions, and practicing conversational skills. We propose implications of using off-the-shelf technologies as a personal assistant to ASD users in Assistive Technology design. We suggest design implications for promoting positive opportunities while mitigating the remaining challenges of VCAs for adolescents with ASD.

CHI 2021.

Inha Cha, Sung-In Kim, Hwajung Hong, Heejeong Yoo, Youn-kyung Lim