UMSI at CHI 2023: Research, workshops, courses
University of Michigan School of Information faculty and PhD students are creating and sharing knowledge that helps build a better world. Here are their publications and the workshops for the April 2023 Conference on Human Factors in Computing Systems (CHI) in Hamburg, Germany.
“Trauma-Informed Social Media: Towards Solutions for Reducing and Healing Online Harm”
Social media platforms exacerbate trauma, and many users experience various forms of trauma unique to them (e.g., doxxing and swatting). Trauma is the psychological and physical response to experiencing a deeply disturbing event. Platforms' failures to address trauma threaten users' well-being globally, especially amongst minoritized groups. Platform policies also expose moderators and designers to trauma through content they must engage with as part of their jobs (e.g., child sexual abuse). We consider how a trauma-informed approach might help address or decrease the likelihood of (re)experiencing trauma online. A trauma-informed approach to social media recognizes that everyone likely has a trauma history and that trauma is experienced at the individual, secondary, collective, and cultural levels. This paper proceeds by detailing trauma and its impacts. We then describe how the six trauma-informed principles can be applied to social media design, content moderation, and companies. We conclude by offering recommendations that balance platform responsibility and accountability with well-being and healing for all.
“Shifting from Surveillance-as-Safety to Safety-through-Noticing: A Photovoice Study with Eastside Detroit Residents”
Safety has been used to justify the expansion of today’s large-scale surveillance infrastructures in American cities. Our work offers empirical and theoretical groundings on why and how the safety surveillance conflation that reproduces harm toward communities of color must be denaturalized. In a photovoice study conducted in collaboration with a Detroit community organization and a university team, we invited 11 Black mid-aged and senior Detroiters to use photography to capture their lived experiences of navigating personal and community safety. Their photographic narratives unveil acts of “everyday noticing” in negotiating and maintaining their intricate and interdependent relations with human, non-human animals, plants, spaces, and material things, through which a multiplicity of meaning and senses of safety are produced and achieved. Everyday noticing, as simultaneously a survival skill and a more-than-human care act, is situated in residents’ lived materialities, while also serving as a site for critiquing the reductive and exclusionary vision embedded in large-scale surveillance infrastructures. By proposing an epistemological shift from surveillance-as-safety to safety-through-noticing, we invite future HCI work to attend to the fluid and relational forms of safety that emerge from local entanglement and sensibilities.
“It’s Like an Educated Guessing Game: Parents’ Strategies for Collaborative Diabetes Management with Their Children”
Children with Type 1 Diabetes (T1D) face many challenges with keeping their blood glucose levels within a healthy range because they cannot manage their illness by themselves. To prevent children’s blood glucose from becoming too high or too low, parents apply different strategies to avoid risky situations. To understand how parents of children with T1D manage these risks, we conducted semi-structured interviews with children with T1D (ages 6-12) and their parents (N=41). We identified four types of strategies used by parents (i.e., educated guessing game, contingency planning, experimentation, and reaching out for help) that can be categorized according to two dimensions: 1) the cause of risk (known or unknown) and 2) the occurrence of risk (predictable or unpredictable). Based on our findings, we provide design implications for collaborative health technologies that support parents in better planning for contingencies and identifying unknown causes of risks together with their children.
“VizProg: Identifying Misunderstandings By Visualizing Students’ Coding Progress”
Programming instructors often conduct in-class exercises to help them identify students that are falling behind and surface students’ misconceptions. However, as we found in interviews with programming instructors, monitoring students’ progress during exercises is difficult, particularly for large classes. We present VizProg, a system that allows instructors to monitor and inspect students’ coding progress in real-time during in-class exercises. VizProg represents students’ statuses as a 2D Euclidean spatial map that encodes the students’ problem-solving approaches and progress in real-time. VizProg allows instructors to navigate the temporal and structural evolution of students’ code, understand relationships between code, and determine when to provide feedback. A comparison experiment showed that VizProg helped to identify more students’ problems than a baseline system. VizProg also provides richer and more comprehensive information for identifying important student behavior. By managing students’ activities at scale, this work presents a new paradigm for improving the quality of live learning.
“How Transgender People and Communities Were Involved in Trans Technology Design Processes”
Oliver L. Haimson, Kai Nham, Hibby Thach, Aloe DeGuia
Trans technology – technology created to help address challenges that trans people face – is an important area for innovation that can help improve marginalized people’s lives. We conducted 104 interviews with 115 creators of trans technology to understand how they involved trans people and communities in design processes. We describe projects that used human-centered design processes, as well as design processes that involved trans people in smaller ways, including gathering feedback from users, conducting user testing, or the creators being trans themselves. We show how involving trans people and communities in design is vital for trans technologies to realize their potential for addressing trans needs. Yet we highlight a frequent gap between trans technology design and deployment, and discuss ways to bridge this gap. We argue for the importance of involving community in trans technology design to ensure that transtechnology achieves its promise of helping address trans needs and challenges.
“The Labor of Training Artificial Intelligence: Data Infrastructure, Mobility, and Marginality”
Machine intelligence relies on Al (artificial intelligence) trainers, workers who perform labor such as data annotation and algorithm optimization. However, the promise of Al does not often benefit workers equally; instead, it puts them in precarious situations, e.g. low wages and subordination to machines. This work takes an interdisciplinary approach to draw attention to these pressing issues by exploring the sociotechnical, cultural, and economic dimensions of this emergent technology-mediated labor, in the context of large data infrastructures. Our arguments and proposed concepts (e.g., sociotechnical/algorithmic mobility) respond directly to the under-theorization of mobility research and ecologically unequal exchange theory in HCI. In this position paper, we argue that the Al trainers, who often work in developing regions of western China, are shouldering the burdens of (1) alleviating China’s poverty through Al for development programs, (2) sustaining Eastern China’s platform economy as key participants in large-scale data infrastructure projects, and (3) promoting global Al advancement by providing disembodied labor on products such as high-quality training datasets through repetitive and low-paying work. Using multi-sited ethnography and participatory design methods, this work describes the experiences of under-resourced and under-studied Al trainer communities and the effects of AI on them. This work also offers context-sensitive design recommendations for supporting emergent technology-mediated labor and policy interventions for ethical and sustainable Al training practices.
“‘It can bring you in the right direction’: Episode-Driven Data Narratives to Help Patients Navigate Multidimensional Diabetes Data to Make Care Decisions”
Shriti Raj, Toshi Gupta, Joyce M. Lee, Matthew Kay, Mark W. Newman
Engaging with multiple streams of personal health data to inform self-care of chronic health conditions remains a challenge. Existing informatics tools provide limited support for patients to make data actionable. To design better tools, we conducted two studies with Type 1 diabetes patients and their clinicians. In the first study, we observed data review sessions between patients and clinicians to articulate the tasks involved in assessing different types of data from diabetes devices to make care decisions. Drawing upon these tasks, we designed novel data interfaces called episode-driven data narratives and performed a task-driven evaluation. We found that as compared to the commercially available diabetes data reports, episode-driven data narratives improved engagement and decision-making with data. We discuss implications for designing data interfaces to support interaction with multidimensional health data to inform self-care.
“Organizing Community-based Events in Participatory Action Research: Lessons Learned from a Photovoice Exhibition”
Participatory action research (PAR) approaches center community members’ lived experiences and can spur positive change around pressing challenges faced by communities. Even though PAR and similar approaches have been increasingly adopted in HCI research that focuses on social justice and community empowerment, publicfacing events that are based on this research and center community members’ voices are less common. This case study sheds light on how to initiate and organize events that build on existing PAR efforts, and what practical challenges might exist in this process. Building on a photovoice research project, we—a collaborative team of university researchers and staff members of a community organization in Eastside Detroit—co-organized a community-based publicfacing exhibition that featured community members’ photographic narratives of personal and communal safety and surveillance. In this case study, we reflect on the challenges we experienced in planning and holding the exhibition. We contribute a set of practical guidelines to help researchers facilitate community-based events when conducting participatory action research in HCI.
“Studying the effect of AI Code Generators on Supporting Novice Learners in Introductory Programming”
Majeed Kazemitabaar, Justin Chow, Carl Ka To Ma, Barbara J. Ericson, David Weintrop, Tovi Grossman
AI code generators like OpenAI Codex have the potential to assist novice programmers by generating code from natural language descriptions, however, over-reliance might negatively impact learning and retention. To explore the implications that AI code generators have on introductory programming, we conducted a controlled experiment with 69 novices (ages 10-17). Learners worked on 45 Python code-authoring tasks, for which half of the learners had access to Codex, each followed by a code-modification task. Our results show that using Codex significantly increased code-authoring performance (1.15x increased completion rate and 1.8x higher scores) while not decreasing performance on manual code-modification tasks. Additionally, learners with access to Codex during the training phase performed slightly better on the evaluation post-tests conducted one week later, although this difference did not reach statistical significance. Of interest, learners with higher Scratch pre-test scores performed significantly better on retention post-tests, if they had prior access to Codex.
“Understanding Journalists’ Workflows in News Curation”
With the increasing dominance of internet as a source of news consumption, there has been a rise in the production and popularity of email newsletters compiled by individual journalists. However, there is little research on the processes of aggregation, and how these differ between expert journalists and trained machines. In this paper, we interviewed journalists who curate newsletters from around the world. Through an in-depth understanding of journalists’ workflows, our findings lay out the role of their prior experience in the value they bring into the curation process, their own use of algorithms in finding stories for their newsletter, and their internalization of their readers’ interests and the context they are curating for. While identifying the role of human expertise, we highlight the importance of hybrid curation and provide design insights on how technology can support the work of these experts.
“Hacking, Switching, Combining: Understanding and Supporting DIY Assistive Technology Design by Blind People”
Existing assistive technologies (AT) often fail to support the unique needs of blind and visually impaired (BVI) people. Thus, BVI people have become domain experts in customizing and ‘hacking’ AT, creatively suiting their needs. We aim to understand this behavior in depth, and how BVI people envision creating future DIY personalized AT. We conducted a multi-part qualitative study with 12 blind participants: an interview on unique uses of AT, a two-week diary study to log use cases, and a scenario-based design session to imagine creating future technologies. We found that participants work to design new AT both implicitly through creative use cases, and explicitly through regular ideation and development. Participants envisioned creating a variety of new technologies, and we summarize expected benefits and concerns of using a DIY technology approach. From our results, we present design considerations for future DIY technology systems to support existing customization and ‘hacking’ behaviors.
“VRGit: A Version Control System for Collaborative Content Creation in Virtual Reality”
Immersive authoring tools allow users to intuitively create and manipulate 3D scenes while immersed in Virtual Reality (VR). Collaboratively designing these scenes is a creative process that involves numerous edits, explorations of design alternatives, and frequent communication with collaborators. Version Control Systems (VCSs) help users achieve this by keeping track of the version history and creating a shared hub for communication. However, most VCSs are unsuitable for managing the version history of VR content because their underlying line diferencing mechanism is designed for text and lacks the semantic information of 3D content; and the widely adopted commit model is designed for asynchronous collaboration rather than real-time awareness and communication in VR. We introduce VRGit, a new collaborative VCS that visualizes version history as a directed graph composed of 3D miniatures, and enables users to easily navigate versions, create branches, as well as preview and reuse versions directly in VR. Beyond individual uses, VRGit also facilitates synchronous collaboration in VR by providing awareness of users’ activities and version history through portals and shared history visualizations. In a lab study with 14 participants (seven groups), we demonstrate that VRGit enables users to easily manage version history both individually and collaboratively in VR.
“Emotion AI at Work: Implications for Workplace Surveillance, Emotional Labor, and Emotional Privacy”
Workplaces are increasingly adopting emotion AI, promising benefits to organizations. However, little is known about the perceptions and experiences of workers subject to emotion AI in the workplace. Our interview study with (n=15) US adult workers addresses this gap, finding that (1) participants viewed emotion AI as a deep privacy violation over the privacy of workers’ sensitive emotional information; (2) emotion AI may function to enforce workers’ compliance with emotional labor expectations, and that workers may engage in emotional labor as a mechanism to preserve privacy over their emotions; (3) workers may be exposed to a wide range of harms as a consequence of emotion AI in the workplace. Findings reveal the need to recognize and define an individual right to what we introduce as emotional privacy, as well as raise important research and policy questions on how to protect and preserve emotional privacy within and beyond the workplace.
“Studying Exploration & Long-Term Use of Voice Assistants by Older Adults”
Pooja Upadhyay, Sharon Heung, Shiri Azenkot, Robin Brewer
While past research has examined older adults’ voice assistant (VA) use, it is unclear whether VAs provide enough value to sustain use when compared to technologies such as smartphones. Research also
suggests that barriers around structured command input may limit use. In order to investigate these gaps in adoption, we conducted interviews with ten older adults in a long-term care community who have adopted Alexa devices for at least one year. Participants learned to use Alexa through a training program that encouraged exploration. They used Alexa to complement their daily routines, improve their mood, engage in cognitively stimulating activities, and support socialization with others. We discuss our findings in the context of prior work, describe strategies to promote VA learning and adoption, and present design recommendations to support aging.
“Infrastructuring Care: How Trans and Non-Binary People Meet Health and Well-Being Needs through Technology”
Lauren Wilcox, Renee Shelby, Rajesh Veeraraghavan, Oliver Haimson, Gabi Erickson, Michael Turken, Beka Gulotta
We present a cross-cultural diary study with 64 transgender (trans) and non-binary adults in Mexico, the U.S., and India, to understand experiences keeping track of and managing aspects of personal health and well-being. Based on a reflexive thematic analysis of diary data, we highlight sociotechnical interactions that shape how trans and non-binary people track and manage aspects of their health and well-being. Specifically, we surface the ways in which trans and non-binary people infrastructure forms of care, by assembling together elements of informal social ecologies, formalized knowledge sources, and self-reflective media. We examine the forms of precarity that interact with care infrastructure and shape management of health and well-being, including management of gender identity transitions. We discuss the ways in which our findings extend knowledge at the intersection of technology and marginalized health needs, and conclude by arguing for the importance of a research agenda to move toward TGNB-inclusive design.
“Eliciting Security & Privacy-Informed Sharing Techniques for Multi-User Augmented Reality”
The HCI community has explored new interaction designs for collaborative AR interfaces in terms of usability and feasibility; however,security & privacy (S&P) are often not considered in the design process and left to S&P professionals. To produce interaction proposals with S&P in mind, we extend the user-driven elicitation method with a scenario-based approach that incorporates a threat model involving access control in multi-user AR. We conducted an elicitation study in two conditions, pairing AR/AR experts in one condition and AR/S&P experts in the other, to investigate the impact of each pairing. We contribute a set of expert-elicited interactions for sharing AR content enhanced with access control provisions, analyze the benefts and tradeofs of pairing AR and S&P experts, and present recommendations for designing future multi-user AR interactions that better balance competing design goals of usability, feasibility, and S&P in collaborative AR.
“Old Logics, New Technologies: Producing a Managed Workforce on On-Demand Service Platforms”
We examine how two prominent food delivery platforms in India, Swiggy and Zomato, produce a managed digital workforce using a combination of algorithmic control and traditional labor management strategies. Our findings draw from interviews conducted with 13 food delivery workers and a critical discourse analysis of news media coverage. We found that the two platforms combine piece wage restructuring, granular datafication practices, and the use of benevolent language as neoliberal social control mechanisms. We find that this combination of technological governance and strategic managerial practices is a mutually constitutive method of control that restructures labor processes, extracts workers’ compliance and consent, and prevents work disruption. We show that contemporary platform companies draw from strategies that have historically been deployed in industrial labor management. By examining how older and newer regimes of social control and exploitation are strategically intertwined in contemporary platform design, we contribute a historically situated understanding of platform labor that moves beyond dualistic interpretations of “traditional” labor management practices and more recent algorithmic modes of control. Our findings contribute to recent debates in tech labor and algorithmic control by examining how contemporary conditions of precarious work reactivate certain past forms of control and in doing so normalize extreme overwork, exhaustion, speedups, and injuries.
“Cultural Differences in Friendship Network Behaviors: A Snapchat Case Study”
Agrima Seth, Jiyin Cao, Xiaolin Shi, Ron Dotsch, Yozen Liu, Maarten W. Bos
Culture shapes people's behavior, both online and offline. Surprisingly, there is sparse research on how cultural context affects network formation and content consumption on social media. We analyzed the friendship networks and dyadic relations between content producers and consumers across 73 countries through a cultural lens in a closed-network setting. Closed networks allow for intimate bonds and self-expression, providing a natural setting to study cultural differences in behavior. We studied three theoretical frameworks of culture - individualism, relational mobility, and tightness. We found that friendship networks formed across different cultures differ in egocentricity, meaning the connectedness between a user's friends. Individualism, mobility, and looseness also significantly negatively impact how tie strength affects content consumption. Our findings show how culture affects social media behavior, and we outline how researchers can incorporate this in their work. Our work has implications for content recommendations and can improve content engagement.
“Colaroid: A Literate Programming Approach for Authoring Explorable Multi-Stage Tutorials”
Multi-stage programming tutorials are key learning resources for programmers, using progressive incremental steps to teach them how to build larger software systems. A good multi-stage tutorial describes the code clearly, explains the rationale and code changes for each step, and allows readers to experiment as they work through the tutorial. In practice, it is time-consuming for authors to create tutorials with these attributes. In this paper, we introduce Colaroid, an interactive authoring tool for creating high quality multi-stage tutorials. Colaroid tutorials are augmented computational notebooks, where snippets and outputs represent a snapshot of a project, with source code differences highlighted, complete source code context for each snippet, and the ability to load and tinker with any stage of the project in a linked IDE. In two laboratory studies, we found Colaroid makes it easy to create multi-stage tutorials, while offering advantages to readers compared to video and web-based tutorials.
“Less is Not More: Improving Findability and Actionability of Privacy Controls for Online Behavioral Advertising”
Tech companies that rely on ads for business argue that users have control over their data via ad privacy settings. However, these ad settings are often hidden. This work aims to inform the design of findable ad controls and study their impact on users’ behavior and sentiment. We iteratively designed ad control interfaces that varied in the setting’s (1) entry point (within ads, at the feed’s top) and (2) level of actionability, with high actionability directly surfacing links to specific advertisement settings, and low actionability pointing to general settings pages (which is reminiscent of companies’ current approach to ad controls). We built a Chrome extension that augments Facebook with our experimental ad control interfaces and conducted a between-subjects online experiment with 110 participants. Results showed that entry points within ads or at the feed’s top, and high actionability interfaces, both increased Facebook ad settings’ findability and discoverability, as well as participants’ perceived usability of them. High actionability also reduced users’ effort in finding ad settings. Participants perceived high and low actionability as equally usable, which shows it is possible to design more actionable ad controls without overwhelming users. We conclude by emphasizing the importance of regulation to provide specific and research-informed requirements to companies on how to design usable ad controls
“Conceptualizing Algorithmic Stigmatization”
Algorithmic systems have in!ltrated many aspects of our society, mundane to high-stakes, and can lead to algorithmic harms known as representational and allocative. In this paper, we consider what stigma theory illuminates about mechanisms leading to algorithmic harms in algorithmic assemblages. We apply the four stigma elements (i.e., labeling, stereotyping, separation, status loss/discrimination) outlined in sociological stigma theories to algorithmic assemblages in two contexts : 1) "risk prediction" algorithms in higher education, and 2) suicidal expression and ideation detection on social media. We contribute the novel theoretical conceptualization of algorithmic stigmatization as a sociotechnical mechanism that leads to a unique kind of algorithmic harm: algorithmic stigma. Theorizing algorithmic stigmatization aids in identifying theoretically-driven points of intervention to mitigate and/or repair algorithmic stigma. While prior theorizations reveal how stigma governs socially and spatially, this work illustrates how stigma governs sociotechnically.
“Disability Activism on Social Media: Sociotechnical Challenges in the Pursuit of Visibility”
Shruti Sannon, Jordyn Young, Erica Shusas, Andrea Forte
Activism efforts have played a central role in advancing the rights of disabled people in the United States. Social media offers new opportunities for people with disabilities to engage in activism while bypassing the accessibility issues involved in traditional activism. At the same time, disabled people face various forms of social and technical exclusion that may also complicate their use of social media for disability activism. To understand how disabled activists advocate for social change online, we interviewed 20 disabled content creators about their goals, strategies, and challenges around posting activism content on social media. We find that visibility is essential for successful online activism, but that the pursuit of visibility requires disabled content creators to navigate additional challenges including social stigma, algorithmic suppression, accessibility issues, and a heightened risk of harassment. We identify three main types of disability-related harassment faced by disabled activists, along with six ways in which they respond to such harassment. We examine the sociotechnical nature of the strategies disabled activists use to gain visibility, and identify key trade-offs involved in mitigating harassment while engaging in activism on social media.
“ReadingQuizMaker: A Human-NLP Collaborative System that Supports Instructors to Design High-Quality Reading Quiz Questions”
Xinyi Lu, Simin Fan, Jessica Houghton, Lu Wang, Xu Wang
Despite that reading assignments are prevalent, methods to encourage students to actively read are limited. We propose a system ReadingQuizMaker that supports instructors to conveniently design high-quality questions to help students comprehend readings. ReadingQuizMaker adapts to instructors’ natural workflows of creating questions, while providing NLP-based process-oriented support. ReadingQuizMaker enables instructors to decide when and which NLP models to use, select the input to the models, and edit the outcomes. In an evaluation study, instructors found the resulting questions to be comparable to their previously designed quizzes. Instructors praised ReadingQuizMaker for its ease of use, and considered the NLP suggestions to be satisfying and helpful. We compared ReadingQuizMaker with a control condition where instructors were given automatically generated questions to edit. Instructors showed a strong preference for the human-AI teaming approach provided by ReadingQuizMaker. Our findings suggest the importance of giving users control and showing an immediate preview of AI outcomes when providing AI support.
“Lettersmith: Scaffolding Written Professional Communication Among College Students”
Julie Hui, Michelle Sprouse
Professional writing is critical for job search and performance, but many – especially those without work experience – struggle to write well. We introduce an instructional approach called ‘scaffolded annotation’ as a way to guide students in creating initial drafts of professional writing, like client emails and cover letters. We studied the implementation of scaffolded annotation in a digital platform called Lettersmith. First, we performed a quasi-experimental study and found that students applying scaffolded annotation in
Lettersmith were more likely to include key components of professional writing. We also interviewed instructors and students who used Lettersmith and found that scaffolded annotation helped students in guiding structure, content, and tone. Instructors found the approach useful for articulating writing task expectations, pinpointing student gaps in understanding, and scaling instructional support for early-stage drafting. We provide implications for writing instruction and HCI researchers developing writing support tools.
“High Risk, High Reward: Social Networking Online in Under-resourced Communities”
Julie Hui, Jesse King, Cynthia McLeod, Amy Gonzales
Expanding one’s social network has been associated with greater access to resources and social support. However, little is known about how under-resourced populations decide to make new connections online and under what circumstances. We interviewed 36 under-resourced individuals in the U.S. to understand these decisions and found that people make new connections in order to seek advice and exchange support, particularly around coping with challenges more prevalent in under-resourced settings. However,
participants were sometimes dissuaded from making new connections online due to fear of being scammed and hesitance around the social norms of reaching out to people outside their network. We
discuss how people in under-resourced contexts grapple with ‘high risk yet high reward’ social networking and outline implications for supporting safe and purposeful network development among
under-resourced SNS users.
“Online Harassment in Majority Contexts: Examining Harms and Remedies across Countries”
Online harassment is a global problem. This article examines perceptions of harm and preferences for remedies associated with online harassment with nearly 4000 participants in 14 countries around the world. The countries in this work reflect a range of identities and values, with a focus on those outside of North American and European contexts. Results show that perceptions of harm are higher among participants from all countries studied compared to the United States. Non-consensual sharing of sexual photos is consistently rated as harmful in all countries, while insults and rumors are perceived as more harmful in non-U.S. countries, especially harm to family reputation. Lower trust in other people and lower trust in sense of safety in one’s neighborhood correlate with increased perceptions of harm of online harassment. In terms of remedies, participants in most countries prefer monetary compensation, apologies, and publicly revealing offender’s identities compared to the U.S. Social media platform design and policy must consider regional values and norms, which may depart from U.S. centric-approaches.
“A Case Study Exploring Users’ Perceptions and Expectations of Shapes for Dialog Designs”
Xinghui Yan, Julia Feldman, Frank Bentley, Mohammed Khwaja, Michael Dean Gilbert
Shape is a fundamental visual characteristic in the design of common UI components like buttons, switches, and dialogs. It has commonly been used to enhance the visual aesthetic of a UI, or to express a distinct perspective in style or brand. However, it remains understudied how the shape of UI components convey semantic meaning and impact user perception of the information displayed in those UI components. As a first step to address this gap, we chose to study the dialog UI component. We first explored the shape of a dialog and created 6 different designs (e.g., dialogs with rounded corners, circle, and wiggly-circle) for an online survey study with 200 participants. We examined whether different dialog designs alter user perceptions and expectations of different messages displayed within them. This work serves as a practical study to explore the opportunity for shapes to be used intentionally in UI design.
“Accessibility Barriers, Conflicts, and Repairs: Understanding the Experience of Professionals with Disabilities in Hybrid Meetings”
Rahaf Alharbi, John Tang, Karl Henderson
Workplaces around the globe are beginning to rapidly adopt hybrid meetings to conduct, plan, and organize their work. While previous literature explores the benefits and drawbacks of hybrid meetings, the experiences of professionals with disabilities are largely missing. With an orientation towards an accessible future of work, we interviewed 21 professionals with disabilities to unpack the accessibility barriers, opportunities, and conflicts of hybrid meetings. We highlight the creative ways professionals with disabilities developed workarounds and repairs to these accessibility tensions. Our paper expands the understanding of accessibility in hybrid meetings by identifying how the visibility of access labor may be affected by being in the room together with other colleagues or joining remotely. We also observed how hybrid configurations can require navigating accessibility conflicts specific to the location site of each participant. Building from our analysis, we offer practical suggestions and design directions to make hybrid meetings accessible.
“Maintainers of Stability: The Labor of China’s Data-Driven Governance and Dynamic Zero-COVID”
Yuchen Chen, Yuling Sun, Silvia Lindtner
This paper examines the social, technological, and emotional labor of maintaining China’s data-driven governance broadly, and dynamic zero-COVID management in particular. Drawing on ethnographic research in China, we examine the sociotechnical work of maintenance during the 2022 Shanghai lockdown. This labor included coordinating mass testing, quarantine, and lockdown procedures as well as implementing ad-hoc technological workarounds and managing public sentiments. We demonstrate that, far from being effected from the top down, China’s data-driven governance relies on the circumscribed participation of citizens. During Shanghai’s lockdown, citizens with relevant expertise helped to maintain
technological stability by fixing or programming data systems, but also to ensure the ongoing production of “positive feelings” about social stability through data-driven governance. In so doing, such citizens simultaneously enacted an ambivalent and circumscribed form of agency, and maintained social and by extension political stability. This article sheds light on data-driven governance and political processes of maintenance.
“Understanding Food Planning Strategies of Food Insecure Populations: Implications for Food-Agentic Technologies”
Tawanna R. Dillahunt, Michelle Sawwan, Danielle Wood, Brianna L. Wimer, Ann-Marie Conrado, Heather Eicher-Miller, Alisa Zornig Gura, Ronald Metoyer
To identify technological opportunities to better support nutrition security and equality among those living in low-socioeconomic situations, we conducted 33 semi-structured interviews and seven in-home visits of lower- to middle-income households from a mid-sized city in northern Indiana. Inspired by assets-based approaches to public health, we investigated technology’s role in supporting how participants selected and purchased food, planned meals, and worked through logistical barriers to obtain food. Technology
helped participants identify sales and coupons, search for recipes and health-related insights to address diet and health concerns, and share information. We contribute design implications (e.g., amplifying optimization behaviors and social engagement, leveraging substitutions) in support of food agency. We further contribute three emergent archetypes to convey central shopping tendencies (i.e.,
inventory shoppers, menu planners, and adaptive shoppers) and identify corresponding design implications. We situate our results into nutrition decision-making and education, social psychology, food consumer studies, and HCI literature.
Late Breaking Work
Late Breaking Work: A Collective Approach to Providing Digital Skills Training Among U.S. Public Housing Residents
Addressing the digital divide would support access to essential activities such as healthcare, employment, and education among under-resourced communities in the United States (U.S.). However, half of the adults in the U.S. lack confidence and preparedness to use digital tools for learning. We developed and piloted an intervention to train public housing residents as intermediaries to provide digital support to their community members to address this gap. Collaborating with community partners, we developed a cohort-based basic digital skills training program consisting of online courses and offline social learning support. We trained nine public housing residents and present best practices of collective training and the challenges the trainees faced. Preliminary results suggest an increase in trainees’ self-efficacy in basic digital skills. Our approach aims to increase digital literacy and minimize barriers to online learning among traditionally-excluded populations. Our work extends prior interventions that only provide device and Internet access.
Late Breaking Work: How Pairing by Code Similarity Influences Discussions in Peer Learning
Peer learning, as a form of collaborative learning, has been widely used in programming courses as a means of promoting active learning and enhancing students' programming skills. However, it is challenging for instructors to group students effectively so that they can have fruitful conversations. We conducted a study with 15 students from an introductory programming course to investigate whether and how grouping students with similar or different solutions affects the discussions that take place within groups. The findings indicate that pairing students by the similarity of their code might influence students' learning and coding skills. Specifically, students who were paired with people that had different solutions had, on average, more engaging conversations and were more likely to write more diverse solutions in the future. The results also highlight the need for tools to facilitate the pairing process in programming courses in order to optimize the learning outcomes for students.
Workshop: Inclusive Design of CUIs Across Modalities and Mobilities
Jaisie Sin, Heloisa Candello, Leigh Clark, Benjamin R. Cowan, Minha Lee, Cosmin Munteanu, Martin Porcheron, Sarah Theres Volkel, Stacy Branham, Robin N. Brewer, Ana Paula Chaves, Razan Jaber, Amanda Lazar
Workshop: Combating Toxicity, Harassment, and Abuse in Online Social Spaces
Regan L Mandryk, Julian Frommel, Nitesh Goyal, Guo Freeman, Cliff Lampe, Sarah Vieweg, Donghee Yvette, Wohn
Workshop: Child-Centered AI Design: Definition, Operation, and Considerations
Ge Wang, Kaiwen Sun, Ayca Atabey, Kruakae Pothong, Grace C. Lin, Jun Zhao, Jason Yip
Journal: #ActuallyAutistic Twitter as a Site for Epistemic Resistance and Crip Futurity
The Internet has, for several decades, played a critical role in autistic self-advocacy and community building. This semi-autoethnographic, interpretivist study turns to #ActuallyAutistic Twitter to examine autistic concerns about autism research, how these concerns differ from those of autism researchers, and how autistics interact with autism research and researchers. I find that #ActuallyAutistic Twitter discourses align with the neurodiversity paradigm, while dominant autism discourses in the academy align with the medical model of disability. Though both orientations towards autism research sometimes share research priorities, they represent fundamentally irreconcilable approaches to these priorities and autism, more broadly. I explore how autistics on Twitter interact with non-autistic researchers and how the tenor of these interactions varies according to which research paradigm a particular researcher subscribes. I conclude with a discussion of how HCI researchers interested in autism can operationalize these findings by approaching their work through the framework of crip technoscience.
Journals: Uncovering Personal Histories: A Technology-Mediated Approach to Eliciting Reflection on Identity Transitions
Oliver L. Haimson, Megh Marathe
When studying identity transitions, interview participants can find it difficult to reflect on their transitions and recall specific details related to past experiences. We present a new approach to enable participant reflection on past identity transitions, and a means to fill in blanks by eliciting data that may not otherwise come up: showing participants sentiment visualizations of their social media data. After detailing our methods of constructing sentiment visualizations, we discuss our experiences using them in a study on gender transition. For most participants, the visualizations elicited substantial reflection, and enabled recalling forgotten data and new interpretations of transition experiences. We guide researchers on how to use this method when studying other identity transitions; this may be especially powerful for marginalized people who undergo substantial identity changes. This paper proposes a way to uncover participants' personal histories, which can help HCI researchers to better understand and support marginalized people's experiences.