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HCDE at CHI 2024

Leah Pistorius
May 1, 2024

Faculty and students from the University of Washington’s Department of Human Centered Design & Engineering will again have a strong presence at the 2024 Conference on Human Factors in Computing Systems (CHI), the premier international conference on Human-Computer Interaction.

CHI 2024 logoHCDE researchers are contributing 20 papers to the 2024 CHI conference, including one selected for the Best Paper Award recognition (given to the top 1% of submissions) and two selected for Best Paper Honorable Mention recognition (given to the top 5% of submissions). In addition, HCDE professors Julie Kientz and Kate Starbird will receive notable awards at this year's conference: Kientz will be named to the SIGCHI Academy and Starbird will receive a 2024 SIGCHI Social Impact Award.

Researchers from the UW community overall contributed to 66 papers. These publications draw from 16 different UW departments and programs, demonstrating the exceptional power of interdisciplinary research that is at the heart of the UW DUB community. Read the full list of UW contributions on the DUB website.

CHI 2024 will be held from May 11-16 in Honolulu, Hawaii. Find information about contributions of HCDE researchers below. Names of HCDE students and faculty are in bold.



MigraineTracker: Examining Patient Experiences With Goal-Directed Self-Tracking for a Chronic Health Condition

Yasaman S Sefidgar, UW Computer Science & Engineering; Carla L Castillo, UW Human Centered Design & Engineering; Shaan Chopra, UW Computer Science & Engineering; Liwei Jiang, UW Computer Science & Engineering; Tae Jones, UW Computer Science & Engineering; Anant Mittal, UW Computer Science & Engineering; Hyeyoung Ryu, UW Information School; Jessica Schroeder, UW Computer Science & Engineering; Allison Cole, UW Family Medicine; Natalia Murinova, UW Neurology; Sean A Munson, UW Human Centered Design & Engineering; James Fogarty, UW Computer Science & Engineering

Self-tracking and personal informatics offer important potential in chronic condition management, but such potential is often undermined by difficulty in aligning self-tracking tools to an individual's goals. Informed by prior proposals of goal-directed tracking, we designed and developed MigraineTracker, a prototype app that emphasizes explicit expression of goals for migraine-related self-tracking. We then examined migraine patient experiences in a deployment study for an average of 12+ months, including a total of 50 interview sessions with 10 patients working with 3 different clinicians. Patients were able to express multiple types of goals, evolve their goals over time, align tracking to their goals, personalize their tracking, reflect in the context of their goals, and gain insights that enabled understanding, communication, and action. We discuss how these results highlight the importance of accounting for distinct and concurrent goals in personal informatics together with implications for the design of future goal-directed personal informatics tools.


HCI Contributions in Mental Health: A Modular Framework to Guide Psychosocial Intervention Design

Petr Slovak, King's College London; Sean A Munson, UW Human Centered Design & Engineering

Many people prefer psychosocial interventions for mental health care or other concerns, but these interventions are often complex and unavailable in settings where people seek care. Intervention designers use technology to improve user experience or reach of interventions, and HCI researchers have made many contributions toward this goal. Both HCI and mental health researchers must navigate tensions between innovating on and adhering to the theories of change that guide intervention design. In this paper, we propose a framework that describes design briefs and evaluation approaches for HCI contributions at the scopes of capabilities, components, intervention systems, and intervention implementations. We show how theories of change (from mental health) can be translated into design briefs (in HCI), and that these translations can bridge and coordinate efforts across fields. It is our hope that this framework can support researchers in motivating, planning, conducting, and communicating work that advances psychosocial intervention design.


"I Want It to Talk Like Darth Vader": Helping Children Construct Creative Self-Efficacy With Generative AI

Michele Newman, UW Information School; Kaiwen Sun, University of Michigan; Ilena B Dalla Gasperina, UW Human Centered Design & Engineering; Grace Y Shin, UW Information School; Matthew Kyle Pedraja, UW Human Centered Design & Engineering; Ritesh Kanchi, UW Computer Science & Engineering: Maia B. Song, UW Human Centered Design & Engineering; Rannie Li, UW Art + Art History + Design; Jin Ha Lee, UW Information School; Jason Yip, UW Information School

The emergence of generative artificial intelligence (GenAI) has ignited discussions surrounding its potential to enhance creative pursuits. However, distinctions between children's and adult's creative needs exist, which is important when considering the possibility of GenAI for children's creative usage. Building upon work in Human-Computer Interaction (HCI), fostering children's computational thinking skills, this study explores interactions between children (aged 7-13) and GenAI tools through methods of participatory design. We seek to answer two questions: (1) How do children in co-design workshops perceive GenAI tools and their usage for creative works? and (2) How do children navigate the creative process while using GenAI tools? How might these interactions support their confidence in their ability to create? Our findings contribute a model that describes the potential contexts underpinning child-GenAI creative interactions and explores implications of this model for theories of creativity, design, and use of GenAI as a constructionist tool for creative self-efficacy.

AI-Assisted Causal Pathway Diagram for Human-Centered Design

Ruican Zhong, UW Human Centered Design & Engineering; Donghoon Shin, UW Human Centered Design & Engineering; Rosemary Meza, Kaiser Permanente; Predrag Klasnja, University of Michigan; Lucas Colusso, Microsoft; Gary Hsieh, UW Human Centered Design & Engineering

This paper explores the integration of causal pathway diagrams (CPD) into human-centered design (HCD), investigating how these diagrams can enhance the early stages of the design process. A dedicated CPD plugin for the online collaborative whiteboard platform Miro was developed to streamline diagram creation and offer real-time AI-driven guidance. Through a user study with designers ($N=20$), we found that CPD's branching and its emphasis on causal connections supported both divergent and convergent processes during design. CPD can also facilitate communication among stakeholders. Additionally, we found our plugin significantly reduces designers' cognitive workload and increases their creativity during brainstorming, highlighting the implications of AI-assisted tools in supporting creative work and evidence-based designs.

Better Little People Pictures: Generative Creation of Demographically Diverse Anthropographics

Priya Dhawka, UW Human Centered Design & Engineering / University of Calgary; Lauren Perera, University of Calgary; Wesley Willett, University of Calgary

We explore the potential of generative AI text-to-image models to help designers efficiently craft unique, representative, and demographically diverse anthropographics that visualize data about people. Currently, creating data-driven iconic images to represent individuals in a dataset often requires considerable design effort. Generative text-to-image models can streamline the process of creating these images, but risk perpetuating designer biases in addition to stereotypes latent in the models. In response, we outline a conceptual workflow for crafting anthropographic assets for visualizations, highlighting possible sources of risk and bias as well as opportunities for reflection and refinement by a human designer. Using an implementation of this workflow with Stable Diffusion and Google Colab, we illustrate a variety of new anthropographic designs that showcase the visual expressiveness and scalability of these generative approaches. Based on our experiments, we also identify challenges and research opportunities for new AI-enabled anthropographic visualization tools.

"Caption It in an Accessible Way That Is Also Enjoyable": Characterizing User-Driven Captioning Practices on TikTok

Emma J McDonnell, UW Human Centered Design & Engineering; Tessa Eagle, University of California, Santa Cruz; Pitch Sinlapanuntakul, UW Human Centered Design & Engineering; Soo Hyun Moon, UW Human Centered Design & Engineering; Jon E Froehlich, UW Computer Science & Engineering; Kathryn E Ringland, University of California, Santa Cruz; Leah Findlater, UW Human Centered Design & Engineering

As user-generated video dominates media landscapes, it poses an accessibility challenge. While disability advocacy groups globally have secured hard-won accessibility regulations for broadcast media, no such regulation of user-generated content exists. Yet, one major player in this shift, TikTok, has a culture of user-generated, creative captioning. We sought to understand how TikTok videos are captioned and the impact current practices have on those who need captions to access audio content. Therefore, we conducted a content analysis of 300 open-captioned TikToks and contextualized these findings by interviewing nine caption users. We found that the current state of TikTok captioning does facilitate access to the platform but that a user-generated, social video-specific standard for captioning could improve caption quality and expand access. We contribute an empirical account of the state of TikTok captioning and outline steps toward a standard for user-generated captioning.

Co-Designing Situated Displays for Family Co-Regulation With ADHD Children

Lucas M Silva, University of California, Irvine; Franceli L Cibrian, Chapman University; Clarisse Bonang, University of California, Irvine; Arpita, UW Human Centered Design & Engineering; Aehong Min, University of California, Irvine; Elissa M MonteiroUniversity of California, Riverside; Jesus Armando Beltran, University of California, Irvine; Sabrina Schuck, University of California, Irvine; Kimberley D Lakes, University of California, Riverside; Gillian R Hayes, University of California, Irvine; Daniel A Epstein, University of California, Irvine

Family informatics often uses shared data dashboards to promote awareness of each other's health-related behaviors. However, these interfaces often stop short of providing families with needed guidance around how to improve family functioning and health behaviors. We consider the needs of family co-regulation with ADHD children to understand how in-home displays can support family well-being. We conducted three co-design sessions with each of eight families with ADHD children who had used a smartwatch for self-tracking. Results indicate that situated displays could nudge families to jointly use their data for learning and skill-building. Accommodating individual needs and preferences when family members are alone is also important, particularly to support parents exploring their co-regulation role, and assisting children with data interpretation and guidance on self and co-regulation. We discuss opportunities for displays to nurture multiple intents of use, such as joint or independent use, while potentially connecting with external expertise.

Data Probes as Boundary Objects for Technology Policy Design: Demystifying Technology for Policymakers and Aligning Stakeholder Objectives in Rideshare Gig Work

Angie Zhang, The University of Texas at Austin; Rocita Rana, The University of Texas at Austin; Alexander Boltz, UW Human Centered Design & Engineering / The University of Texas at Austin; Veena Dubal, University of California, Irvine; Min Kyung Lee, The University of Texas at Austin

Despite the evidence of harm that technology can inflict, commensurate policymaking to hold tech platforms accountable still lags. This is pertinent to app-based gig workers, where unregulated algorithms continue to dictate their work, often with little human recourse. While past HCI literature has investigated workers’ experiences under algorithmic management and how to design interventions, rarely are the perspectives of stakeholders who inform or craft policy sought. To bridge this, we propose using data probes---interactive visualizations of workers’ data that show the impact of technology practices on people---exploring them in 12 semi-structured interviews with policy informers, (driver-)organizers, litigators, and a lawmaker in the rideshare space. We show how data probes act as boundary objects to assist stakeholder interactions, demystify technology for policymakers, and support worker collective action. We discuss the potential for data probes as training tools for policymakers, and considerations around data access and worker risks when using data probes.

Designing Accessible Obfuscation Support for Blind Individuals' Visual Privacy Management

Lotus Zhang, UW Human Centered Design & Engineering; Abigale Stangl, UW Human Centered Design & Engineering; Tanusree Sharma, University of Illinois Urbana-Champaign; Yu-Yun Tseng, University of Colorado; Inan Xu, University of California, Santa Cruz; Danna Gurari, University of Colorado; Yang Wang, University of Illinois Urbana-Champaign; Leah Findlater, UW Human Centered Design & Engineering

Blind individuals commonly share photos in everyday life. Despite substantial interest from the blind community in being able to independently obfuscate private information in photos, existing tools are designed without their inputs. In this study, we prototyped a preliminary screen reader-accessible obfuscation interface to probe for feedback and design insights. We implemented a version of the prototype through off-the-shelf AI models (e.g., SAM, BLIP2, ChatGPT) and a Wizard-of-Oz version that provides human-authored guidance. Through a user study with 12 blind participants who obfuscated diverse private photos using the prototype, we uncovered how they understood and approached visual private content manipulation, how they reacted to frictions such as inaccuracy with existing AI models and cognitive load, and how they envisioned such tools to be better designed to support their needs (e.g., guidelines for describing visual obfuscation effects, co-creative interaction design that respects blind users’ agency).

DiaryMate: Understanding User Perceptions and Experience in Human-AI Collaboration for Personal Journaling

Taewan Kim, KAIST; Donghoon Shin, UW Human Centered Design & Engineering; Young-Ho Kim, Naver; Hwajung Hong, KAIST

With their generative capabilities, large language models (LLMs) have transformed the role of technological writing assistants from simple editors to writing collaborators. Such a transition emphasizes the need for understanding user perception and experience, such as balancing user intent and the involvement of LLMs across various writing domains in designing writing assistants. In this study, we delve into the less explored domain of personal writing, focusing on the use of LLMs in introspective activities. Specifically, we designed DiaryMate, a system that assists users in journal writing with LLM. Through a 10-day field study (N=24), we observed that participants used the diverse sentences generated by the LLM to reflect on their past experiences from multiple perspectives. However, we also observed that they are over-relying on the LLM, often prioritizing its emotional expressions over their own. Drawing from these findings, we discuss design considerations when leveraging LLMs in a personal writing practice.

From Concept to Community: Unpacking the Work of Designing Educational and Activist Toolkits

Tamar Wilner, The University of Texas at Austin; Krishna Akhil Kumar Adavi, The University of Texas at Austin; Sreehana Mandava, The University of Texas at Austin; Ayesha Bhimdiwala, The University of Texas at Austin; Hana Frluckaj, The University of Texas at Austin; Jennifer Turns, UW Human Centered Design & Engineering; Ahmer Arif, The University of Texas at Austin

Toolkits are an important means of sharing expertise and influencing practice. However, the work of making and sustaining toolkits is not well understood. We address this gap by conducting 20 semi-structured interviews with toolkit designers, focusing on toolkits intended to help practitioners such as librarians, teachers, and community workers. We analyze these interviews to surface key aspects of participants’ design journeys: (1) how their projects began; (2) how they conceptualized use; (3) how they collaborated with users; (4) and what happened once their toolkit was released. We illustrate these aspects through three narratives, and discuss our findings to provide considerations for designers and scholars. We highlight how designers co-construct communities alongside their toolkits, helping us form a more nuanced understanding of the social aspects underpinning toolkit projects. Collectively, these contributions can help us identify challenges and opportunities in this design space, laying the groundwork to increase toolkits' social impact.

From Paper to Card: Transforming Design Implications With Generative AI

Donghoon Shin, UW Human Centered Design & Engineering; Lucy Lu Wang, UW Information School / Allen Institute for Artificial Intelligence; Gary Hsieh, UW Human Centered Design & Engineering

Communicating design implications is common within the HCI community when publishing academic papers, yet these papers are rarely read and used by designers. One solution is to use design cards as a form of translational resource that communicates valuable insights from papers in a more digestible and accessible format to assist in design processes. However, creating design cards can be time-consuming, and authors may lack the resources/know-how to produce cards. Through an iterative design process, we built a system that helps create design cards from academic papers using an LLM and text-to-image model. Our evaluation with designers (N=21) and authors of selected papers (N=12) revealed that designers perceived the design implications from our design cards as more inspiring and generative, compared to reading original paper texts, and the authors viewed our system as an effective way of communicating their design implications. We also propose future enhancements for AI-generated design cards.

How Do Analysts Understand and Verify AI-Assisted Data Analyses?

Ken Gu, UW Computer Science & Engineering; Ruoxi Shang, UW Human Centered Design & Engineering; Tim Althoff, UW Computer Science & Engineering; Chenglong Wang, Microsoft; Steven M Drucker, Microsoft

Data analysis is challenging as analysts must navigate nuanced decisions that may yield divergent conclusions. AI assistants have the potential to support analysts in planning their analyses, enabling more robust decision making. Though AI-based assistants that target code execution (e.g., Github Copilot) have received significant attention, limited research addresses assistance for both analysis execution and planning. In this work, we characterize helpful planning suggestions and their impacts on analysts’ workflows. We first review the analysis planning literature and crowd-sourced analysis studies to categorize suggestion content. We then conduct a Wizard-of-Oz study (n=13) to observe analysts’ preferences and reactions to planning assistance in a realistic scenario. Our findings highlight subtleties in contextual factors that impact suggestion helpfulness, emphasizing design implications for supporting different abstractions of assistance, forms of initiative, increased engagement, and alignment of goals between analysts and assistants.

"I Never Realized Sidewalks Were a Big Deal": A Case Study of a Community-Driven Sidewalk Accessibility Assessment Using Project Sidewalk

Chu Li, UW Computer Science & Engineering; Katrina Oi Yau Ma, UW Human Centered Design & Engineering; Michael Saugstad, UW Computer Science & Engineering; Kie Fujii, Hackensack Meridian School of Medicine; Molly Delaney, University of Illinois Chicago; Yochai Eisenberg, University of Illinois Chicago; Delphine Labbé, University of Illinois Chicago; Judy L Shanley, Easterseals; Devon Snyder, University of Illinois Chicago; Florian P Thomas, Hackensack Meridian School of Medicine; Jon E Froehlich, UW Computer Science & Engineering

Despite decades of effort, pedestrian infrastructure in cities continues to be unsafe or inaccessible to people with disabilities. In this paper, we examine the potential of community-driven digital civics to assess sidewalk accessibility through a deployment study of an open-source crowdsourcing tool called Project Sidewalk. We explore Project Sidewalk's potential as a platform for civic learning and service. Specifically, we assess its effectiveness as a tool for community members to learn about human mobility, urban planning, and accessibility advocacy. Our findings demonstrate that community-driven digital civics can support accessibility advocacy and education, raise community awareness, and drive pro-social behavioral change. We also outline key considerations for deploying digital civic tools in future community-led accessibility initiatives.

KnitScape: Computational Design and Yarn-Level Simulation of Slip and Tuck Colorwork Knitting Patterns

Hannah Twigg-Smith, UW Human Centered Design & Engineering; Emily Whiting, Boston University; Nadya Peek, UW Human Centered Design & Engineering

Slipped and tucked stitches introduce small areas of deformation that compound and result in emergent textures on knitted fabrics. When used together with color changes and ladders, these can also produce dramatic colorwork and openwork effects. However, designing slip and tuck colorwork patterns is challenging due to the complex interactions between operations, yarns, and deformations. We present KnitScape, a browser-based tool for design and simulation of stitch patterns for knitting. KnitScape provides a design interface to specify 1) operation repeats, 2) color changes, and 3) needle positions. These inputs are used to build a graph of yarn topology and run a yarn-level spring simulation. This enables visualization of the deformation that arises from slip and tuck operations. Through its design tool and simulation, KnitScape enables rapid exploration of a complex colorwork design space. We demonstrate KnitScape with a series of example swatches.

Mapping the Design Space of Teachable Social Media Feed Experiences

K J Kevin Feng, UW Human Centered Design & Engineering; Xander Koo, Georgia Institute of Technology; Lawrence Tan, UW Computer Science & Engineering; Amy Bruckman, Georgia Institute of Technology; David W McDonald, UW Human Centered Design & Engineering; Amy X Zhang, UW Computer Science & Engineering

Social media feeds are deeply personal spaces that reflect individual values and preferences. However, top-down, platform-wide content algorithms can reduce users' sense of agency and fail to account for nuanced experiences and values. Drawing on the paradigm of interactive machine teaching (IMT), an interaction framework for non-expert algorithmic adaptation, we map out a design space for \textit{teachable social media feed experiences} to empower agential, personalized feed curation. To do so, we conducted a think-aloud study (N=24) featuring four social media platforms---Instagram, Mastodon, TikTok, and Twitter---to understand key signals users leveraged to determine the value of a post in their feed. We synthesized users' signals into taxonomies that, when combined with user interviews, inform five design principles that extend IMT into the social media setting. We finally embodied our principles into three feed designs that we present as sensitizing concepts for teachable feed experiences moving forward.

Nothing Like Compilation: How Professional Digital Fabrication Workflows Go Beyond Extruding, Milling, and Machines

Mare Hirsch, University of California, Santa Barbara; Gabrielle Benabdallah, UW Human Centered Design & Engineering; Jennifer Jacobs, University of California, Santa Barbara; Nadya Peek, UW Human Centered Design & Engineering

Understanding how professionals use digital fabrication in production workflows is critical for future research in digital fabrication technologies. We interviewed thirteen professionals who use digital fabrication for the low-volume manufacturing of commercial products. From these interviews, we describe the workflows used for nine products created with a variety of materials and manufacturing methods. We show how digital fabrication professionals use software development to support physical production, how they rely on multiple partial representations in development, how they develop manufacturing processes, and how machine control is its own design space. We build from these findings to argue that future digital fabrication systems should support the exploration of material and machine behavior alongside geometry, that simulation is insufficient for understanding the design space, and that material constraints and resource management are meaningful design dimensions to support. By observing how professionals learn, we suggest ways digital fabrication systems can scaffold the mastery of new fabrication techniques.

Tandem: Reproducible Digital Fabrication Workflows as Multimodal Programs

Jasper Tran O'Leary, UW Computer Science & Engineering; Thrisha Ramesh, UW Computer Science & Engineering; Octi Zhang, UW Computer Science & Engineering; Nadya Peek, UW Human Centered Design & Engineering

Experimental digital fabrication workflows are increasingly common in human-computer interaction research, but are difficult to reproduce. We present Tandem, a software library that lets a fabricator implement an end-to-end fabrication workflow as a computational notebook program that others can run to physically reproduce the workflow. Tandem notebook programs read and write to CAD and CAM software, project augmented reality interfaces onto machines for manual interventions, and directly control fabrication machines. Fabricators can also denote potential mismatches between the physical and the digital as explicit assertions in code. Using two-sided CNC milling as an example, we demonstrate how to implement a complex workflow as a single program that can be re-run by others while supporting quality control and improving reproducibility.

Technical Mentality: Principles for HCI Research and Practice

Gabrielle Benabdallah, UW Human Centered Design & Engineering; Nadya Peek, UW Human Centered Design & Engineering

This paper presents a reflection on the role of ontological inquiry in HCI research and practice. Specifically, we introduce philosopher Gilbert Simondon's proposal of technical mentality, an onto-epistemology based on direct knowledge of technical objects and systems. This paper makes the following contributions: an analysis of Simondon's ontological critique and its connection to technical mentality; a reflection on the ethical and practical implications of Simondon's proposal for systems research; an example of technical mentality in practice; and a discussion of how technical mentality might be extended into a design program for HCI through four principles: extension, integration, legibility, and expression.

What to the Muslim Is Internet Search: Digital Borders as Barriers to Information

Lubna Razaq, UW Human Centered Design & Engineering; Sucheta Ghoshal, UW Human Centered Design & Engineering