User-centered design necessitates researchers deeply understanding target users throughout the design process. However, during early-stage user interviews, researchers may misinterpret users due to time constraints, incorrect assumptions, and communication barriers. To address this challenge, we introduce InsightBridge, a tool that supports real-time, AI-assisted information synthesis and visual-based verification. InsightBridge automatically organizes relevant information from ongoing interview conversations into an empathy map. It further allows researchers to specify elements to generate visual abstracts depicting the selected information, and then review these visuals with users to refine the visuals as needed. We evaluated the effectiveness of InsightBridge through a within-subject study (N=32) from both the researchers’ and users’ perspectives. Our findings indicate that InsightBridge can assist researchers in note-taking and organization, as well as in-time visual checking, thereby enhancing mutual understanding with users. Additionally, users’ discussions of visuals prompt them to recall overlooked details and scenarios, leading to more insightful ideas.
https://dl.acm.org/doi/10.1145/3706598.3713640
Social movement organizations, such as mutual aid groups, rely on technology to increase their influence, meet immediate needs, and address systemic inequalities. In this paper, we examine the role of technology in moments of crisis and the tensions mutual aid groups face when relying on tools designed with values that may be antithetical to their own. Through a qualitative study with mutual aid volunteers in the United States, we found that mutual aid groups’ values, such as solidarity, security, and co-production, are prioritized as they navigate adopting technology. However, while technology can streamline logistics and enhance visibility for mutual aid groups, we argue that the adoption of existing technologies and conventions of practice can erode opportunities for building solidarity, present challenges for accountability, and exacerbate pre-existing social exclusions. We argue that these tensions emerge not simply as a mismatch between values and technical design, but as systematic outcomes of adopting tools that embed different political assumptions and points of access. Our findings contribute to understanding how values shape --- and are shaped by --- technological infrastructure in mutual aid work.
https://dl.acm.org/doi/10.1145/3706598.3714192
While peer review enhances writing and research quality, harsh feedback can frustrate and demotivate authors. Hence, it is essential to explore how critiques should be delivered to motivate authors and enable them to keep iterating their work. In this study, we explored the impact of appending an automatically generated positive summary to the peer reviews of a writing task, alongside varying levels of overall evaluations (high vs. low), on authors’ feedback reception, revision outcomes, and motivation to revise. Through a 2x2 online experiment with 137 participants, we found that adding an AI-reframed positive summary to otherwise harsh feedback increased authors’ critique acceptance, whereas low overall evaluations of their work led to increased revision efforts. We discuss the implications of using AI in peer feedback, focusing on how AI-driven critiques can influence critique acceptance and support research communities in fostering productive and friendly peer feedback practices.
https://dl.acm.org/doi/10.1145/3706598.3713219
Accelerated globalization has made migration commonplace, creating significant cultural adaptation challenges, particularly for young migrants. While HCI research has explored the role of technology in migrants' cultural adaptation, there is a need to address the diverse cultural backgrounds and needs of young migrants specifically. Recognizing the potential of conversational AI to adapt to diverse cultural contexts, we investigate how young migrants could use this technology in their adaptation journey and explore its societal implementation. Through individual workshops with young migrants and stakeholder interviews—including AI practitioners, public sector workers, policy experts, and social scientist—we found that both groups of participants expect conversational AI to support young migrants in connecting with the host culture before migration, exploring the home culture, and aligning identities across home and host cultures. However, challenges such as expectation gaps and cultural bias may hinder cultural adaptation. We discuss design considerations for culturally sensitive AI that empower young migrants and propose strategies to enhance societal readiness for AI-driven cultural adaptation.
https://dl.acm.org/doi/10.1145/3706598.3713091
Household collaboration among cohabiting couples presents unique challenges due to the intimate nature of the relationships and the lack of external rewards. Current efficiency-oriented technologies neglect these distinct dynamics. Our study aims to examine the real-world context and underlying needs of couples in their collaborative homemaking. We conducted a 10-day empirical investigation involving six Korean couples, supplemented by a probe approach to facilitate reflection on their current homemaking practices. We identified the requirement for ideal household collaboration as a 'shared ritual for celebratory interaction' and pinpointed the challenges in achieving this goal. We propose three design opportunities for domestic technology to address this gap: strengthening the meaning of housework around family values, supporting recognition of the partner's efforts through visualization, and initiating negotiation through defamiliarization. These insights extend the design considerations for domestic technologies, advocating for a broader understanding of the values contributing to satisfactory homemaking activities within the household.
https://dl.acm.org/doi/10.1145/3706598.3713383
Interpersonal motor synchronization (IMS) occurs when people move together, in temporal alignment. Being in IMS can result in prosocial effects: increased liking, similarity and trust. We address the possibility of remote IMS (rIMS) between people who are not co-located, through mobile phone interactions. A threat to rIMS is the temporal noise inherent to communication networks. We created a mobile phone application in which a human participant tries to tap in synchrony with a remote participant, that is in fact a responsive computer algorithm. We introduced three levels of synthetic network noise to the joint tapping. We show that pro-sociality can be created in rIMS, but that as network noise increases the prosocial effects decrease. Participants' textual answers are analyzed thematically to learn about the effects of remote synchronization. Our findings motivate the creation of remote interactions with elements of IMS as well as inform the network requirements for successful rIMS.
https://dl.acm.org/doi/10.1145/3706598.3713562