bluuebunny/crossref_metadata_2025 huggingface dataset:
"You Can either Blame Technology or Blame a Person..." --- A Conceptual Model of Users' AI-Risk Perception as a Tool for HCI
Authors: Recki Lena , Lawo Dennis , Krauß Veronika , Pins Dominik , Boden Alexander
Published: November 2024

AI-powered systems pose unknown challenges for designers, policymakers, and users, making it more difficult to assess potential harms and outcomes. Although understanding risks is a requirement for building trust in technology, users are often excluded from risk assessments and explanations in policy and design. To address this issue, we conducted three workshops with 18 participants and discussed the EU AI Act, which is the European proposal for a legal framework for AI regulation. Based on results of these workshops, we propose a user-centered conceptual model with five risk dimensions (Design and Development, Operational, Distributive, Individual, and Societal) that includes 17 key risks. We further identify six criteria for categorizing use cases. Our conceptual model (1) contributes to responsible design discourses by connecting the risk assessment theories with user-centered approaches, and (2) supports designers and policymakers in more strongly considering a user perspective that complements their own expert views.
Exploring Patient-Generated Annotations to Digital Clinical Symptom Measures for Patient-Centered Communication
Authors: Jo Eunkyung , Zehrung Rachael , Genuario Katherine , Papoutsaki Alexandra , Epstein Daniel A.
Published: November 2024

Patients' self-reports are crucial for effective care management of clinical conditions involving subjective symptoms. While patients often value the ability to bring in different forms of self-report data to convey their lived experiences, they often struggle to make their data practically usable in clinical settings. To better center patient needs in communicating illness experiences in clinical contexts, we explore the idea of patient annotations to digital clinical self-report measures, specifically in the context of discontinuing antidepressants. Through interviews with 20 patients with AT Annotator, a digital aid to introduce the concept of annotations, we found that participants perceived annotations to digital clinical measures as a means to enrich self-report measures and reduce the cognitive and emotional burden of logging. However, concerns were raised regarding potential disruptions in patient-provider relationships and the sensitive and complex nature of mental health contexts. We discuss opportunities for annotations to promote patient-centered communication by balancing with clinical practicality and incorporating customization support for patients' communication needs.
Family Resilience in Care Coordination Technologies: Designing for Families as Adaptive Systems
Authors: Nikkhah Sarah , Rode Akash Uday , Kulkarni Neha Keshav , Mittal Priyanjali , Mueller Emily L. , Miller Andrew D.
Published: November 2024

When a child is admitted to the hospital with a critical illness, their family must adapt and manage care and stress. CSCW researchers have shown the potential for collaborative technologies to support and augment care collaboration between patients and caregivers. However, as a field CSCW lacks a holistic,
theory-driven
understanding of how collaborative technologies might best augment and support the family caregiving circle as a socio-technical system. In this paper, we report findings from interviews with 14 parents of children with cancer admitted for extended hospitalizations. We use the resilience-based Family Adaptive Systems framework from family therapy as a lens to characterize their challenges and practices across four key subsystems: Emotion, Control, Meaning, and Maintenance. Then, we introduce a fifth system-the Information system-and draw on our empirical findings to suggest theory-driven opportunities for designing future collaborative technology to augment collaborative caregiving and enhance family resilience.
Measuring Epistemic Trust: Towards a New Lens for Democratic Legitimacy, Misinformation, and Echo Chambers
Authors: Jones Dominic Zaun Eu , Chandrasekharan Eshwar
Published: November 2024

Trust is crucial for the functioning of complex societies, and an important concern for CSCW. Our purpose is to use research from philosophy, social science, and CSCW to provide a novel account of trust in the 'post-truth' era. Testimony, from one speaker to another, underlies many social systems. Epistemic trust, or testimonial credibility, is the likelihood to accept a speaker's claim due to beliefs about their competence or sincerity. Epistemic trust is closely related to several 'pathological epistemic phenomena': democratic (il)legitimacy, the spread of misinformation, and echo chambers. To the best of our knowledge, this theoretical contribution is novel in the field of social computing. We further argue that epistemic trust is no philosophical novelty: it is measurable. Weakly supervised text classification approaches achieve F_1 scores of around 80 to 85 per cent on detecting epistemic distrust. This is also, to the best of our knowledge, a novel task in natural language processing. We measure expressions of epistemic distrust across 954 political communities on Reddit. We find that expressions of epistemic distrust are relatively rare, although there are substantial differences between communities. Conspiratorial communities and those focused on controversial political topics tend to express more distrust. Communities with strong epistemic norms enforced by moderation are likely to express low levels. While we find users to be an important potential source of contagion of epistemic distrust, community norms appear to dominate. It is likely that epistemic trust is more useful as an aggregated risk factor. Finally, we argue that policymakers should be aware of epistemic trust considering their reliance on legitimacy underwritten by testimony.
Understanding and Influencing Responsibility Attribution when Experiencing Technical Issues in Video Conferencing
Authors: Yang Chi-Lan , Li Xiaotong , Narumi Takuji , Kuzuoka Hideaki
Published: November 2024

During video conferencing, technical issues such as network impairments can unexpectedly hinder remote collaboration for distributed teams. However, it remains unclear how such issues affect the impression formation process between unacquainted interlocutors in situations like job interviews or kick-off meetings. Having first encounters online without prior in-person interaction has become prevalent nowadays. Therefore, examining the impact of technical issues on remote unacquainted interlocutors and exploring design solutions to reduce the negative impact of technical issues on the impression is essential in informing the design of future communication systems. With three controlled experiments simulating an online job interview, we discovered that technical issues made people give low credibility ratings to remote job applicants (Study 1). We further examined two intervention approaches to reduce the negative impact of technical issues in video conferencing, including a virtual agent represented in a human-like avatar to actively take responsibility for the technical issues (Study 2), and forewarning messages to inform people about the technical issues in video conferencing (Study 3). Results demonstrated that introducing an agent that represents a communication system to take responsibility for technical issues actively could reduce the responsibility people assign to remote job applicants, but without increasing their positive credibility rating for remote job applicants. Furthermore, showing forewarning messages, which explicitly made people aware the cause of technical issues was unidentifiable and its potential negative impacts on impression formation, enabled people to rate the credibility of the remote counterpart without being influenced by technical issues. We discussed how interventions can be designed to mitigate negative attribution outcomes when encountering uncontrollable technical issues in computer-mediated communication.
Insights from an Experiment Crowdsourcing Data from Thousands of US Amazon Users: The importance of transparency, money, and data use
Authors: Berke Alex , Mahari Robert , Pentland Alex , Larson Kent , Calacci Dana
Published: November 2024

Data generated by users on digital platforms are a crucial resource for advocates and researchers interested in uncovering digital inequities, auditing algorithms, and understanding human behavior. Yet data access is often restricted. How can researchers both effectively and ethically collect user data? This paper shares an innovative approach to crowdsourcing user data to collect otherwise inaccessible Amazon purchase histories, spanning 5 years, from more than 5,000 U.S. users. We developed a data collection tool that prioritizes participant consent and includes an experimental study design. The design allows us to study multiple important aspects of privacy perception and user data sharing behavior, including how socio-demographics, monetary incentives and transparency can impact share rates. Experiment results (N=6,325) reveal both monetary incentives and transparency can significantly increase data sharing. Age, race, education, and gender also played a role, where female and less-educated participants were more likely to share. Our study design enables a unique empirical evaluation of the 'privacy paradox', where users claim to value their privacy more than they do in practice. We set up both real and hypothetical data sharing scenarios and find measurable similarities and differences in share rates across these contexts. For example, increasing monetary incentives had a 6 times higher impact on share rates in real scenarios. In addition, we study participants' opinions on how data should be used by various third parties, again finding that gender, age, education, and race have a significant impact. Notably, the majority of participants disapproved of government agencies using purchase data yet the majority approved of use by researchers. Overall, our findings highlight the critical role that transparency, incentive design, and user demographics play in ethical data collection practices, and provide guidance for future researchers seeking to crowdsource user generated data.
"More Than Just Holding the iPad": Family Members' Perspectives on the Work of Video Calling in Aged Care
Authors: Kelly Ryan M. , Xing Yushan , Baker Steven , Waycott Jenny
Published: November 2024

Video calls are increasingly being adopted to enable older adults living in long-term residential care (aged care homes) to remain socially connected with friends and family. However, care home residents often require extensive support to participate effectively in video calls. Despite growing interest in examining the work involved in facilitating technology use in care homes, the role of caregivers---comprising family members and staff---in facilitating video calls has received limited attention. Drawing on data from a study of family members' experiences in Australia, we analysed the essential work activities required to make video calls function in residential aged care. We show how video calling is underpinned by the development of relationships between families and staff, and how video calling requires considerable work in preparation, facilitation, and troubleshooting. We discuss how video calling systems for care homes might be designed to alleviate unwanted work, lowering the burden of call participation for residents, families, and care staff.
"Come to us first": Centering Community Organizations in Artificial Intelligence for Social Good Partnerships
Authors: Lin Hongjin , Karusala Naveena , Okolo Chinasa T. , D'Ignazio Catherine , Gajos Krzysztof Z.
Published: November 2024

Artificial Intelligence for Social Good (AI4SG) has emerged as a growing body of research and practice exploring the potential of AI technologies to tackle social issues. This area emphasizes interdisciplinary partnerships with community organizations, such as non-profits and government agencies. However, amidst excitement about new advances in AI and their potential impact, the needs, expectations, and aspirations of these community organizations--and whether they are being met--are not well understood. Understanding these factors is important to ensure that the considerable efforts by AI teams and community organizations can actually achieve the positive social impact they strive for. Drawing on the
Data Feminism
framework, we explored the perspectives of community organization members on their partnerships with AI teams through 16 semi-structured interviews. Our study highlights the pervasive influence of funding agendas and the optimism surrounding AI's potential. Despite the significant intellectual contributions and labor provided by community organization members, their goals were frequently sidelined in favor of other stakeholders, including AI teams. While many community organization members expected tangible project deployment, only two out of 14 projects we studied reached the deployment stage. However, community organization members sustained their belief in the
potential
of the projects, still seeing diminished goals as valuable. To enhance the efficacy of future collaborations, our participants shared their aspirations for success, calling for co-leadership starting from the early stages of projects. We propose
data co-liberation
as a grounding principle for approaching AI4SG moving forward, positing that community organizations' co-leadership is essential for fostering more effective, sustainable, and ethical development of AI.
"I inherently just trust that it works": Investigating Mental Models of Open-Source Libraries for Differential Privacy
Authors: Song Patrick , Sarathy Jayshree , Shoemate Michael , Vadhan Salil
Published: November 2024

Differential privacy (DP) is a promising framework for privacy-preserving data science, but recent studies have exposed challenges in bringing this theoretical framework for privacy into practice. These tensions are particularly salient in the context of open-source software libraries for DP data analysis, which are emerging tools to help data stewards and analysts build privacy-preserving data pipelines for their applications. While there has been significant investment into such libraries, we need further inquiry into the role of these libraries in promoting understanding of and trust in DP, and in turn, the ways in which design of these open-source libraries can shed light on the challenges of creating trustworthy data infrastructures in practice.

In this study, we use qualitative methods and mental models approaches to analyze the differences between conceptual models used to design open-source DP libraries and mental models of DP held by users. Through a two-stage study design involving formative interviews with 5 developers of open-source DP libraries and user studies with 17 data analysts, we find that DP libraries often struggle to bridge the gaps between developer and user mental models. In particular, we highlight the tension DP libraries face in maintaining rigorous DP implementations and facilitating user interaction. We conclude by offering practical recommendations for further development of DP libraries.
"I Upload... All Types of Different Things to Say the World of Blindness Is More Than What They Think It Is": A Study of Blind TikTokers' Identity Work from a Flourishing Perspective
Authors: Lyu Yao , Cai Jie , Dosono Bryan , Yadav Davis , Carroll John M.
Published: November 2024

Identity work in Human-Computer Interaction (HCI) has examined the asset-based design of marginalized groups who use technology to improve their quality of life. Our study illuminates the identity work of people with disabilities, specifically, visual impairments. We interviewed 45
BlindTokers
(blind users on TikTok) from various backgrounds to understand their identity work from a positive design perspective. We found that BlindTokers leverage the affordance of the platform to create positive content, express their identities, and build communities with the desire to
flourish.
We proposed
flourishing labor
to present the work conducted by BlindTokers for their community's flourishing with implications to support the flourishing labor. This work contributes to understanding blind users' experience in short video platforms and highlights that flourishing is not just an activity for any single blind user but also a collective effort that necessitates serious and committed contributions from platforms and the communities they serve.
"I Want to Publicize My Stutter": Community-led Collection and Curation of Chinese Stuttered Speech Data
Authors: Li Qisheng , Wu Shaomei
Published: November 2024

This paper documents the process undertaken by
StammerTalk
, a grassroots community of Chinese-speaking people who stutter, to autonomously collect and curate stuttered speech data for more inclusive speech AI models. While people with disabilities are often excluded or treated merely as the
subjects
of AI data collection, our work introduces a new model for disability data collection in which the disability community exerts agency and control over their personal data and data-driven experiences. Our ethnographic data show that community-led data collection not only produces data needed to represent the community in AI systems, but also empowers the community and its members, by embracing - rather than concealing - stuttering and stutterer identity, and strengthening the social bonds of the community. Recognizing the lack of adequate socio-technical infrastructure for community-led, grassroots data collection, we discuss practical challenges, as well as the strategies and factors for communities to succeed in similar endeavors.
"Like I was There:" A User Evaluation of an Interpersonal Telepresence System Developed through Value Sensitive Design
Authors: Pfeil Kevin , Badillo-Urquiola Karla , LaViola Joseph J. , Wisniewski Pamela J.
Published: November 2024

We developed and deployed an interpersonal telepresence prototype aimed at providing a positive one-to-one interaction between a Streamer and a Viewer. Our prototype uses four distributed, wearable cameras hidden from the public eye. It was designed to reduce the risk of Streamer self-consciousness while providing the Viewer with a greater sense of autonomy. We deployed our prototype with sixteen participants in dyads, who worked together to complete a scavenger hunt, and compared it the baseline of Skype. We found how our prototype better supported Streamer social well-being and physical comfort, and it also better supported Viewer autonomy. However, almost all participants desired a change to the design of the prototype, hinting that we need to provide better customization for future iterations of interpersonal telepresence devices.
"They Make Us Old Before We're Old": Designing Ethical Health Technology with and for Older Adults
Authors: So Jianna , Estrada Samantha , Jörke Matthew , Bianchi Eva , Wang Maria , Haghighi Nava , Fessele Kristen L. , Landay James A. , Cuadra Andrea
Published: November 2024

Voice-first ambient interfaces (VFAIs), such as Alexa, can uniquely meet the health needs of older adults. However, inequitable technology may worsen health disparities and decrease independence, calling for participatory methods to increase the agency of older adults in the design processes of these technologies. We adapt and conduct a participatory design workshop to focus on ambient interfaces for home health with 13 diverse older adults in San Francisco's Tenderloin neighborhood. Using the prototypes they made as discussion catalyzers, participants shared different perspectives entailing stigmatized topics that can be difficult to discuss, such as drug use, sex, isolation, and dementia. They deliberated on the negative implications of VFAIs, such as a justified concern for surveillance, in conjunction with their positive implications, such as receiving always-available ''non-judgmental'' support. Similarly, the risk of leaking drug use data was considered alongside the benefits of sharing important medical information with clinicians. We synthesize our findings into design considerations, such as how we might address varying levels of trust in different stakeholders and reduce stigma that may hinder users from fully benefiting from VFAIs' capabilities.
Behaviors and Perceptions of Human-Chatbot Interactions Based on Top Active Users of a Commercial Social Chatbot
Authors: Chin Hyojin , Zhunis Assem , Cha Meeyoung
Published: November 2024

Natural language processing is enabling machines to communicate with humans naturally, yet the dynamics of extended user-chatbot interactions remain much unexplored. This study characterizes the conversational styles, demographics, psychologies, and emotional tendencies of the most active users (i.e., top 1% by message count) of a commercial chatbot platform (SimSimi.com), whom we refer to as
superusers.
We analyzed the linguistic patterns and topics of 1,988,971 messages written by 1,994 superusers over a period of three years. We further surveyed 76 users to observe their emotional dispositions and perceptions towards the chatbot. We find that SimSimi superusers empathize and humanize the chatbot more than less active users, and they show a higher tendency to share personal and negative feelings. Our findings suggest that chatbots require new design considerations for users who are vulnerable due to their high anthropomorphism and openness toward machines. Our work also shows that chatbots should have functions to offer social support when necessary.
Beyond Meditation: Understanding Everyday Mindfulness Practices and Technology Use Among Experienced Practitioners
Authors: Li Jingjin , Cochrane Karen Anne , Leshed Gilly
Published: November 2024

Mindfulness, a practice of bringing attention to the present non-judgmentally, has many mental and physical well-being benefits, especially when practiced consistently. Many technologies, such as mobile apps, live streams, virtual reality environments, and wearables, have been invented to support solo or group mindfulness practice. In this paper, we present findings from an interview study with 20 experienced mindfulness practitioners about their everyday mindfulness practices and technology use. Participants identify the benefits and challenges of developing long-term commitment to mindfulness practice. They employ various strategies, such as brief mindfulness exercises, social accountability, and guidance from teachers, to sustain their practice. While conflicted about technology, they adopt and appropriate a range of technologies in their practice for reminders, emotion tracking, connecting with others, and attending online sessions. They also carefully consider when to use technology, when and how to limit its use, and ways to incorporate technology as an object for mindfulness. Based on our findings, we discuss expanding the definition of mindfulness and the tension between supporting short- and long-term mindfulness practice. We also propose a set of design recommendations to support everyday mindfulness, including through the lens of metaphor, reappropriating non-mindfulness technology, and bringing community support into personal practice.
Blow Your Mind: Exploring the Effects of Scene-Switching and Visualization of Time Constraints on Brainstorming in Virtual Reality
Authors: Bi Nanyi , Chi Yueh-Chi , Lin Yun-Yun , Lee Min-Jui , Chen Bing-Yu
Published: November 2024

Brainstorming, a creative activity that aims to generate ideas, plays a crucial part in problem-solving processes and is widely employed to explore innovative solutions across various contexts. It may suffer from repetitive results, inefficient time management, and stagnation in discussion. Seeing the rich opportunities of virtual reality (VR) in visualizing the environments, we propose to use (1) scene-switching and (2) creative visualization of time constraints to facilitate this process. The current study sought to explore the effects of these two factors on brainstorming performance in VR. By conducting a mixed-method study of 20 three-participant groups, we found that scene-switching and implicit time limitations can stimulate creativity, establish diverse atmospheres, and open up new conversations during brainstorming. Additionally, we provide suggestions for visualizing time constraints and various virtual environments based on research results.
Constructing a Classification Scheme - and its Consequences: A Field Study of Learning to Label Data for Computer Vision in a Hospital Intensive Care Unit
Authors: Valentine Melissa A. , Bohn Roger E. , Pratt Amanda L. , Jain Prachee , Singer Sara J. , Bernstein Michael S.
Published: November 2024

Research on data annotation for artificial intelligence (AI) has demonstrated that biases, power, and culture impact the ways that annotators apply labels to data and subsequently affect downstream AI systems. However, annotators can only apply labels that are available to them in the annotation classification scheme. Drawing on a 3-year ethnographic study of an R&D collaboration between medical and AI researchers, we argue that the construction of the classification schema itself -- decisions about what kinds of data can and cannot be collected, what activities can and cannot be detected in the data, what the possible annotation classes ought to be, and the rules by which an item ought to be classified into each class -- dramatically shape the annotation process, and through it, the AI. We draw on Bowker and Star's [9] classification theory to detail how the creation of a training data codebook for a computer vision algorithm in hospital intensive care units (ICUs) evolved from its original, clinically-driven goal of classifying complex clinical activities into a narrower goal of identifying physical objects and simpler activities in the ICU. This work reinforces how trade-offs and decisions made long before annotators begin labeling data are highly consequential to the resulting AI system.
Designing for Researcher Access in the U.S. Mortality Data Ecosystem
Authors: Doyle Dylan Thomas , Fiesler Casey , Pater Jessica , Brubaker Jed R.
Published: November 2024

Access to mortality data is critical for researchers for various reasons, including the development of life-saving medical interventions. However, high-quality mortality data is typically unavailable for researchers to access in a timely manner due to bottlenecks and inefficiencies in the coordination of managing mortality data across a vast information ecosystem. To identify opportunities to improve access to mortality data, we conducted a qualitative interview study with 20 experts with direct knowledge and experience with mortality data systems. From these interviews, we mapped the mortality data ecosystem and found that policy constraints are the main underlying cause of bottlenecks and inefficiencies. We argue that policy intervention is required to optimize the coordination of mortality data between databases and between organizations. To support researcher access to mortality data, we present guiding principles for designers seeking to improve the mortality data ecosystem. These principles contribute to CSCW scholarship focused on the challenges of coordination across large information ecosystems and the tradeoffs between technology and policy when designing such systems.
Exploring Parent's Needs for Children-Centered AI to Support Preschoolers' Interactive Storytelling and Reading Activities
Authors: Sun Yuling , Chen Jiaju , Yao Bingsheng , Liu Jiali , Wang Dakuo , Ma Xiaojuan , Lu Yuxuan , Xu Ying , He Liang
Published: November 2024

Interactive storytelling is vital for preschooler development. While children's interactive partners have traditionally been their parents and teachers, recent advances in artificial intelligence (AI) have sparked a surge of AI-based storytelling and reading technologies. As these technologies become increasingly ubiquitous in preschoolers' lives, questions arise regarding how they function in practical storytelling and reading scenarios and, how parents, the most critical stakeholders, experience and perceive these technologies. This paper investigates these questions through a qualitative study with 17 parents of children aged 3-6. Our findings suggest that even though AI-based storytelling and reading technologies provide more immersive and engaging interaction, they still cannot meet parents' expectations due to a series of interactive and algorithmic challenges. We elaborate on these challenges and discuss the possible implications of future AI-based interactive storytelling technologies for preschoolers.
Guiding Students in Using LLMs in Supported Learning Environments: Effects on Interaction Dynamics, Learner Performance, Confidence, and Trust
Authors: Kumar Harsh , Musabirov Ilya , Reza Mohi , Shi Jiakai , Wang Xinyuan , Williams Joseph Jay , Kuzminykh Anastasia , Liut Michael
Published: November 2024

Personalized chatbot-based teaching assistants can be crucial in addressing increasing classroom sizes, especially where direct teacher presence is limited. Large language models (LLMs) offer a promising avenue, with increasing research exploring their educational utility. However, the challenge lies not only in establishing the efficacy of LLMs but also in discerning the nuances of interaction between learners and these models, which impact learners' engagement and results. We conducted a formative study in an undergraduate computer science classroom (N=145) and a controlled experiment on Prolific (N=356) to explore the impact of four pedagogically informed guidance strategies on the learners' performance, confidence and trust in LLMs. Direct LLM answers marginally improved performance, while refining student solutions fostered trust. Structured guidance reduced random queries as well as instances of students copy-pasting assignment questions to the LLM. Our work highlights the role that teachers can play in shaping LLM-supported learning environments.
Hybridge: Bridging Spatiality for Inclusive and Equitable Hybrid Meetings
Authors: Panda Payod , Tankelevitch Lev , Spittle Becky , Inkpen Kori , Tang John , Junuzovic Sasa , Qi Qianqian , Sweeney Pat , Wilson Andrew D. , Buxton William A.S. , Sellen Abigail , Rintel Sean
Published: November 2024

Hybrid meetings limit inclusion for remote participants. The Hybridge experimental system provides different interfaces for remote and room endpoints, focusing on improving inclusion via shared spatiality and remote agency. In-room participants see remotes on displays around a table, and remotes see video integrated into a digital twin. Remotes can choose where to appear and from where they view the room. We tested Hybridge in a within-subjects study of group survival tasks. An in-person condition was followed by a counterbalanced order of hybrid traditional videoconferencing ("Gallery") and Hybridge. We found that co-presence and agency differences between in-room and remotes were alleviated in Hybridge but remained in Gallery. Physical presence for remotes was higher in Hybridge than Gallery. Conversation flow was better in Hybridge than Gallery, but ease of awareness was not different. We argue that asymmetry should be embraced when designing hybrid meeting systems, with inclusivity achieved by tailoring features for the needs of different endpoints.
Investigating Characteristics of Media Recommendation Solicitation in r/ifyoulikeblank
Authors: Bhuiyan Md Momen , Hu Donghan , Jelson Andrew , Mitra Tanushree , Lee Sang Won
Published: November 2024

Despite the existence of search-based recommender systems like Google, Netflix, and Spotify, online users sometimes may turn to crowdsourced recommendations in places like the r/ifyoulikeblank subreddit. In this exploratory study, we probe why users go to r/ifyoulikeblank, how they look for recommendation, and how the subreddit users respond to recommendation requests. To answer, we collected sample posts from r/ifyoulikeblank and analyzed them using a qualitative approach. Our analysis reveals that users come to this subreddit for various reasons, such as exhausting popular search systems, not knowing what or how to search for an item, and thinking crowd have better knowledge than search systems. Examining users query and their description, we found novel information users provide during recommendation seeking using r/ifyoulikeblank. For example, sometimes they ask for artifacts recommendation based on the tools used to create them. Or, sometimes indicating a recommendation seeker's time constraints can help better suit recommendations to their needs. Finally, recommendation responses and interactions revealed patterns of how requesters and responders refine queries and recommendations. Our work informs future intelligent recommender systems design.
Journeying Through Sense of Place with Mental Maps: Characterizing Changing Spatial Understanding and Sense of Place During Migration for Work
Authors: Gao Zihan , Cranshaw Justin , Thebault-Spieker Jacob
Published: November 2024

Millions of people move for work yearly, but this labor migration risks social and cultural challenges, hindering migrants' integration into new communities. Software tools could support this transition, but the design space around, and the mechanisms behind, how individuals develop spatial understanding and 'sense of place' is unclear. In our study, we leverage mental maps to explore migrants' 'sense of place'. We conduct a mixed- methods study with 12 participants, spanning two sessions - one before and one after their relocation, totaling 24 data sessions. We discover that post-relocation, mental maps not only widen coverage and generalization but also decrease in cartographic complexity and accuracy, reflecting a nuanced blend of personal narratives and spatial awareness. We also find that strategies for rebuilding and reshaping 'sense of place' span a complex set of dimensions spanning personal, social and environmental challenges, post-move. Our findings lay the groundwork, and underscore the need, for 'platial' (versus spatial) understanding and tools to rebuild sense of place, and foster better community cohesion. We highlight design opportunities for creating tools, especially those capturing personal nuances, to help migrants reestablish themselves and their sense of place.
Limitations of Using Mobile Phones for Managing Type 1 Diabetes (T1D) Among Youth in Low and Middle-Income Countries: Implications for mHealth
Authors: Wyche Susan , Olson Dr. Jennifer , Karanu Mary , Omondi Eric , Olonyo Mike Endovo
Published: November 2024

The prevalence of Type 1 Diabetes (T1D) among youth is increasing worldwide. Mobile phones, particularly mHealth applications, can potentially improve youth's management of this chronic condition. However, the design of these services rarely accounts for users in low and middle-income countries (LMICs). In this paper, we investigate factors that influence the use of mobile phones for managing T1D among youth in rural and urban Kenya. Our analysis draws from 58 interviews conducted with T1D youth (between the ages of 11 and 18 years old), their caregivers, and other significant stakeholders, including doctors and schoolteachers. Our findings draw attention to a significant mismatch between the mobile phone features prioritized in mHealth apps and participants' usage practices. We discuss the practical implications of these findings for mHealth design and user research.
Paradoxes of Openness: Trans Experiences in Open Source Software
Authors: Frluckaj Hana , Stevens Nikki , Howison James , Dabbish Laura
Published: November 2024

In recent years, concerns have increased over the lack of contributor diversity in open source software (OSS), despite its status as a paragon of open collaboration. OSS is an important form of digital infrastructure and part of a career path for many developers. While there exists a growing body of literature on cisgender women's under-representation in OSS, the experiences of contributors from other marginalized groups are comparatively absent from the literature. Such is the case for trans contributors, a historically influential group in OSS. In this study, we interviewed 21 trans participants to understand and represent their experiences in the OSS literature. From their experiences, we theorize two related paradoxes of openness in OSS: the paradox of openness and display and the paradox of openness and governance. In an increasingly violent world for trans people, we draw on our theorizing to build recommendations for more inclusive and safer OSS projects for contributors.
Research-Education Partnerships: A Co-Design Classroom for College Students with Intellectual and Developmental Disabilities
Authors: Lowy Rachel , Magiawala Khushi , Mittal Shravika , Hall Kaely , Roberts Jessica , Kim Jennifer G
Published: November 2024

Co-design of technology encourages participation and decision-making input of end-users. In the case of technologies for individuals with Intellectual and Developmental Disabilities (IDD), the end-users are historically left out of the design process. Further deepening the disconnect between this group and technology, they are also excluded from formal technology design knowledge sharing, such as college courses. To address this, our study investigates the efficacy of a formal classroom adaptation of co-design activities to encourage learning and participation. Through collaboration between educators and designers, we adopted user-centered co-design activities to facilitate knowledge and application of technological design methods within a class of 13 students with IDD. Findings uncovered factors contributing to co-teaching collaboration planning and reflection between educators and designers, and ways that activities can provide accessible collaborative learning environments for students with IDD by supporting collaboration, cognitive engagement, and meta-cognition. We discuss how these factors can support successful co-teacher collaborations that promote student empowerment. Finally, we contribute collaborative co-teaching strategies for educational co-design activities for individuals with IDD.
Situating Empathy in HCI/CSCW: A Scoping Review
Authors: Genç Uğur , Verma Himanshu
Published: November 2024

Empathy is considered a crucial construct within HCI and CSCW, yet our understanding of this complex concept remains fragmented and lacks consensus in existing research. In this scoping review of 121 articles from the ACM Digital Library, we synthesize the diverse perspectives on empathy and scrutinize its current conceptualization and operationalization. In particular, we examine the various interpretations and definitions of empathy, its applications, and the methodologies, findings, and trends in the field. Our analysis reveals a lack of consensus on the definitions and theoretical underpinnings of empathy, with interpretations ranging from understanding the experiences of others to an affective response to the other's situation. We observed that despite the variety of methods used to gauge empathy, the predominant approach remains self-assessed instruments, highlighting the lack of novel and rigorously established and validated measures and methods to capture the multifaceted manifestations of empathy. Furthermore, our analysis shows that previous studies have used a variety of approaches to elicit empathy, such as experiential methods and situational awareness. These approaches have demonstrated that shared stressful experiences promote community support and relief, while situational awareness promotes empathy through increased helping behavior. Finally, we discuss
a)
the potential and drawbacks of leveraging empathy to shape interactions and guide design practices,
b)
the need to find a balance between the collective focus of empathy and the (existing and dominant) focus on the individual, and
c)
the careful testing of empathic designs and technologies with real-world applications.
StyleWe: Towards Style Fusion in Generative Fashion Design with Efficient Federated AI
Authors: Wu Di , Wu Mingzhu , Li Yeye , Jiang Jianan , Li Xinglin , Deng Hanhui , Liu Can , Li Yi
Published: November 2024

Collaboration can amalgamate diverse ideas, styles, and visual elements, fostering creativity and innovation among different designers. In collaborative design, sketches play a pivotal role as a means of expressing design creativity. However, designers often tend to not openly share these meticulously crafted sketches. This phenomenon of data island in the design area hinders its digital transformation under the third wave of AI. In this paper, we introduce a Federated Generative Artificial Intelligence Clothing system, namely StyleWe, employing federated learning to aid in sketch design. StyleWe is committed to establishing an ecosystem wherein designers can exchange sketch styles among themselves. Through StyleWe, designers can generate sketches that incorporate various designers' styles from their peers, drawing inspiration from collaboration without the need for data disclosure or upload. Extensive performance evaluations and user studies indicate that our StyleWe system can produce multi-styled sketches of comparable quality to human-designed ones while significantly enhancing efficiency compared to hand-drawn sketches.
Definitions of Fairness Differ Across Socioeconomic Groups & Shape Perceptions of Algorithmic Decisions
Authors: Nguyen Tonya , Alam Sabriya , Hu Cathy , Albiston Catherine , Salehi Niloufar
Published: November 2024

Understanding how people perceive algorithmic decision-making is remains critical, as these systems are increasingly integrated into areas such as education, healthcare, and criminal justice. These perceptions can shape trust in, compliance with, and the perceived legitimacy of automated systems. Focusing on San Francisco's decade-long policy of algorithmic school assignments, we draw on procedural and distributive justice theory to investigate parents' fairness perceptions of San Francisco's school assignment system. We find that key differences in parents' definitions of fairness shape their preferences for what constitutes a fair school assignment system, while also controlling for parents' school assignment outcomes. Moreover, parents' definitions and perceptions of fairness differ across socioeconomic and racial groups. For instance, among white respondents, the most used definition of fairness was "proximity'' to their assigned school, whereas, among Hispanic or Latino parents, the most popular definition of fairness was that the "same rules'' are applied to everyone. It is crucial for computational system designers and policymakers to consider these differences when deciding on the goals and values embedded in decision-making systems and who those goals and values reflect.
Understanding the Evolvement of Trust Over Time within Human-AI Teams
Authors: Duan Wen , Zhou Shiwen , Scalia Matthew J , Yin Xiaoyun , Weng Nan , Zhang Ruihao , Freeman Guo , McNeese Nathan , Gorman Jamie , Tolston Michael
Published: November 2024

The success of human-AI teams (HATs) requires humans to work with AI teammates in trustful ways over a certain time period. However, how trust evolves and changes dynamically in response to human-AI team interactions is generally understudied. This work explores the evolvement of trust in HATs over time by analyzing 45 participants' experiences of trust or distrust in an AI teammate prior to, during, and after collaborating with AI in a three-member HAT. Our findings highlight that humans' expectations of AI's ability, integrity, benevolence, and adaptability influence their initial trust in AI before collaboration. However, this initial trust can be maintained or revised through the development of situational trust during collaboration in response to the AI teammate's communication behaviors. Further, the trust developed through collaboration can impact individuals' subsequent expectations of AI's ability and their collaborations with AI. Our findings also reveal the similarities and differences in the temporal dimensions of trust for AI and human teammates. We contribute to CSCW community by offering one of the first empirical investigations into the dynamic and temporal dimension of trust evolvement in HATs. Our work yields insights into the pathways to expanding the methodological toolkit for investigating the development of trust in HATs, formulating theories of trust for the HAT context. These insights further inform the effective design of AI teammates and provide guidance on the timing, content, and methods for calibrating trust in future human-AI collaboration contexts.
Whose Knowledge is Valued? Epistemic Injustice in CSCW Applications
Authors: Ajmani Leah Hope , Foriest Jasmine C. , Taylor Jordan , Pittman Kyle , Gilbert Sarah , DeVito Michael Ann
Published: November 2024

Social computing scholars have long known that people do not interact with knowledge in straightforward ways, especially in digital environments. While policies around knowledge are essential for targeting misinformation, they are value-laden; in choosing how to present information, we undermine non-traditional, often non-Western, ways of knowing. Epistemic injustice is the systemic exclusion of certain people and methods from the knowledge canon. Epistemic injustice chips away at one's testimony and vocabulary until they are stripped of their due right to know and understand. In this paper, we articulate how epistemic injustice in sociotechnical applications leads to material harm. Inspired by a hybrid collaborative autoethnography of 14 CSCW practitioners, we present three cases of epistemic injustice in sociotechnical applications: online transgender healthcare, identity sensemaking on r/bisexual, and Indigenous ways of knowing on r/AskHistorians. We further explore signature tensions across our autoethnographic materials and relate them to previous CSCW research areas and personal non-technological experiences. We argue that epistemic injustice can serve as a unifying and intersectional lens for CSCW research by surfacing dimensions of epistemic community and power. Finally, we present a call to action of three changes the CSCW community should make to move toward its own goals of research justice. We call for CSCW researchers to center individual experiences, bolster communities, and remediate issues of epistemic power as a means towards epistemic justice. In sum, we recount, synthesize, and propose solutions for the various forms of epistemic injustice that CSCW sites of study---including CSCW itself---propagate.
Why I Choose This Sticker When Chatting with You: Exploring Design Considerations for Sticker Recommendation Services in Mobile Instant Messengers
Authors: Bae Gahyeon , Kwak Daehyun , Lim Youn-kyung
Published: November 2024

Nowadays, many mobile instant messenger (MIM) users employ stickers to express their emotions. Due to the increase in the variety of stickers, many MIM platforms have begun to offer sticker recommendation services, which suggest appropriate stickers based on the context of conversations. Although sticker recommendation services need to consider users' subtle social and psychological needs from the perspective that stickers are an alternative communication language, few attempts have been made to explore this area. Consequently, we investigated sticker usage practices through a qualitative study with 18 KakaoTalk users in South Korea. Based on the results of this study, we revealed user's three common considerations in sticker usage experiences and discussed the design implications for sticker recommendation services in MIM.