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What Do We Mean by “Accessible”

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Lots of people have ideas about what “accessible” means — but they don’t all agree. Maybe we should ask disabled people. We could also learn a lot by asking a wide variety of disabled people, including disabled people who are gender diverse, racially diverse, have multiple disabilities, and have a wide range of disabilities.

We asked 25 disabled people about what accessibility means to them. We learned that it goes beyond typical definitions of addressing an impairment of some kind. We also learned about how people decide what accessibility technologies they want to use. Many people told us that they choose from many possible approaches in each specific situation, weighing all the available options and their priorities in a so-called “consequence calculus”.

Reference: Modeling Accessibility: Characterizing What We Mean by “Accessible” Kelly Avery Mack, Jesse J Martinez, Aaleyah LewisJennifer Mankoff, James Fogarty, Leah Findlater, Heather D. Evans, Cynthia L Bennett, Emma J McDonnell. ASSETS 2025

The Everyday Politics and Power Dynamics of AT Adoption

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Stacy Hsueh, Danielle Van Dusen, Anat Caspi, and Jennifer Mankoff. 2025. Minor Resistance: The Everyday Politics and Power Dynamics of Assistive Technology Adoption. In Proceedings of the 27th International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS ’25), October 26-29, 2025, Denver, CO, USA.

In accessibility research, the choice to adopt or abandon assistive technologies (AT) is often taken as a proxy for functional fit: to adopt is to confirm a good fit between device features and individual needs, whereas to abandon is to signal poor fit. While useful for orienting design, we argue that this framework is ill-equipped to account for the sociopolitical forces that shape AT use in historically underserved communities. In this paper, we propose a power-aware framework that casts adoption not as transparent expression of fit, but as situated negotiation of power. Drawing from an eight- month ethnographic study at a Seattle-based nonprofit, we examine how low-income, racially diverse, and disabled families navigate institutional practices that impose normative expectations around disability and AT use. We introduce the concept of minor resistance to describe the everyday ways people exercise agency in response to power dynamics that make access costly. We argue that this shift in analytical lens reframes the goal of accessibility from optimizing use to lowering the cost of choice. We conclude with implications for how designers can support community-engaged responses to structural barriers by centering self-determination.

MatPlotAlt

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MatplotAlt is an open-source Python package for easily adding alternative text to matplotlib figures. MatplotAlt equips Jupyter notebook authors to automatically generate and surface chart descriptions with a single line of code or command, and supports a range of options that allow users to customize the generation and display of captions based on their preferences and accessibility needs.

Our evaluation indicates that MatplotAlt’s heuristic and LLM-based methods to generate alt text can create accurate long-form descriptions of both simple univariate and complex Matplotlib figures. We find that state-of-the-art LLMs still struggle with factual errors when describing charts, and improve the accuracy of our descriptions by prompting GPT4-turbo with heuristic-based alt text or data tables parsed from the Matplotlib figure.

Here is some example ALT text generated for the pie chart shown below. A variety of examples can be found in the MatPlotAlt documentation.

A pie chart titled ’percentage of annual sunshine’. There are 12 slices: jan (3.19%), feb (4.993%), mar (8.229%), apr (9.57%), may (11.7%), june (12.39%), july (14.42%), aug (12.99%), sep (10.22%), oct (6.565%), nov (3.329%), and dec (2.404%). The data has a standard deviation of x=4.006, an average of x=8.333, a maximum value of x=14.42, and a minimum value of x=2.404. The data strictly increase up to their max at x=14.42, then strictly decrease.

A pie chart titled ’percentage of annual sunshine’. There are 12 slices: jan (3.19%), feb (4.993%), mar (8.229%), apr (9.57%), may (11.7%), june (12.39%), july (14.42%), aug (12.99%), sep (10.22%), oct (6.565%), nov (3.329%), and dec (2.404%). The data has a standard deviation of x=4.006, an average of x=8.333, a maximum value of x=14.42, and a minimum value of x=2.404. The data strictly increase up to their max at x=14.42, then strictly decrease.

Kai Nylund, Jennifer Mankoff, Venkatesh Potluri: MatplotAlt: A Python Library for Adding Alt Text to Matplotlib Figures in Computational Notebooks. Comput. Graph. Forum 44(3) (2025)

Telehealth and Digital Health Innovations

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Telehealth and digital health innovations: A mixed landscape of access Phuong J, Ordóñez P, Cao J, Moukheiber M, Moukheiber L, et al. (2023) Telehealth and digital health innovations: A mixed landscape of access. PLOS Digital Health 2(12): e0000401. https://doi.org/10.1371/journal.pdig.0000401

In the wake of emergent natural and anthropogenic disasters, telehealth presents opportunities to improve access to healthcare when physical access is not possible. Yet, since the beginning of the COVID pandemic, lessons learned reveal that various populations in the United States do not or cannot adopt telehealth due to inequitable access. We explored the Digital Determinants of Health (DDoHs) for telehealth, characterizing the role of accessibility, broadband connectivity and electrical grids, and patient intersectionality. In addition to its role as an existing Social Determinant of Health, Policies and Laws directly and indirectly affect these DDoHs, making access more complex for marginalized populations. Digital systems lack the flexibility, accessibility, and usability to inclusively provide the essential services patients need in telehealth. We propose the following recommendations: (1) design technology and systems using accessibility and value sensitive design principles; (2) support a range of technologies and settings; (3) support multiple and diverse users; and (4) support clear paths for repair when technical systems fail to meet users’ needs. Addressing these requires change not only from providers but also from the institutions providing these systems.

“A Tool for Freedom”

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Jerry Cao, Krish Jain, Julie Zhang, Yuecheng Peng, Shwetak Patel, and Jennifer Mankof. 2025. “A Tool for Freedom”: Co-Designing Mobility Aid Improvements Using Personal Fabrication and Physical Interface Modules with Primarily Young Adults. In CHI Conference on Human Factors in Computing Systems (CHI ’25), April 26–May 01, 2025, Yokohama, Japan. ACM, New York, NY, USA, 16 pages. https://doi.org/10.1145/3706598.3713366

Mobility aids (e.g., canes, crutches, and wheelchairs) are crucial for people with mobility disabilities; however, pervasive dissatisfaction with these aids keeps usage rates low. Through semi-structured interviews with 17 mobility aid users, mostly under the age of 30, we identified specific sources of dissatisfaction among younger users of mobility aids, uncovered community-based solutions for these dissatisfactions, and explored ways these younger users wanted to improve mobility aids. We found that users sought customizable, reconfigurable, multifunctional, and more aesthetically pleasing mobility aids. Participants’ feedback guided our prototyping of tools/accessories, such as laser cut decorative sleeves, hot-swappable physical interface modules, and modular canes with custom 3D-printed handles. These prototypes were then the focus of additional co-design sessions where six returning participants offered suggestions for improvements and provided feedback on their usefulness and usability. Our findings highlight that many mobility aid users have the desire, ability, and need to customize and improve their aids in different ways compared to older adults. We propose various solutions and design guidelines to facilitate the modifications of mobility aids.

Autoethnographic Insights from Neurodivergent GAI “Power Users”

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Kate Glazko, JunHyeok Cha, Aaleyah Lewis, Ben Kosa, Brianna Wimer, Andrew Zheng, Yiwei Zheng, and Jennifer Mankoff. 2025. Autoethnographic Insights from Neurodivergent GAI “Power Users”. In CHI Conference on Human Factors in Computing Systems (CHI ’25), April 26-May 1, 2025, Yokohama, Japan. ACM, New York, NY, USA, 20 pages. https://doi.org/10.1145/ 3706598.3713670

Generative AI has become ubiquitous in both daily and professional life, with emerging research demonstrating its potential as a tool for accessibility. Neurodivergent people, often left out by existing accessibility technologies, develop their own ways of navigating normative expectations. GAI offers new opportunities for access, but it is important to understand how neurodivergent “power users”—successful early adopters—engage with it and the challenges they face. Further, we must understand how marginalization and intersectional identities influence their interactions with GAI. Our autoethnography, enhanced by privacy-preserving GAI-based diaries and interviews, reveals the intricacies of using GAI to navigate normative environments and expectations. Our findings demonstrate how GAI can both support and complicate tasks like code-switching, emotional regulation, and accessing information. We show that GAI can help neurodivergent users to reclaim their agency in systems that diminish their autonomy and self-determination. However, challenges such as balancing authentic self-expression with societal conformity, alongside other risks, create barriers to realizing GAI’s full potential for accessibility.

Toward Language Justice

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Aashaka Desai, Rahaf Alharbi, Stacy Hsueh, Richard E. Ladner, and Jennifer Mankoff. 2025. Toward Language Justice: Exploring Multilingual Captioning for Accessibility. In CHI Conference on Human Factors in Computing Systems (CHI ’25), April 26–May 01, 2025, Yokohama, Japan. ACM, New York, NY, USA, 18 pages. https://doi.org/10.1145/3706598.3713622

A growing body of research investigates how to make captioning experiences more accessible and enjoyable to disabled people. However, prior work has focused largely on English captioning, neglecting the majority of people who are multilingual (i.e., understand or express themselves in more than one language). To address this gap, we conducted semi-structured interviews and diary logs with 13 participants who used multilingual captions for accessibility. Our findings highlight the linguistic and cultural dimensions of captioning, detailing how language features (scripts and orthography) and the inclusion/negation of cultural context shape the accessibility of captions. Despite lack of quality and availability, participants emphasized the importance of multilingual captioning to learn a new language, build community, and preserve cultural heritage. Moving toward a future where all ways of communicating are celebrated, we present ways to orient captioning research to a language justice agenda that decenters English and engages with varied levels of fluency.

Shaping Lace

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Glazko, K., Portnova-Fahreeva, A., Mankoff-Dey, A., Psarra, A., & Mankoff, J. (2024, July). Shaping Lace: Machine embroidered metamaterials. In Proceedings of the 9th ACM Symposium on Computational Fabrication (pp. 1-12).

The ability to easily create embroidered lace textile objects that can be manipulated in structured ways, i.e., metamaterials, could enable a variety of applications from interactive tactile graphics to physical therapy devices. However, while machine embroidery has been used to create sensors and digitally enhanced fabrics, its use for creating metamaterials is an understudied area. This article reviews recent advances in metamaterial textiles and conducts a design space exploration of metamaterial freestanding lace embroidery. We demonstrate that freestanding lace embroidery can be used to create out-of-plane kirigami and auxetic effects. We provide examples of applications of these effects to create a variety of prototypes and demonstrations.

Identifying and improving disability bias in GPT-based resume screening

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Glazko, K., Mohammed, Y., Kosa, B., Potluri, V., & Mankoff, J. (2024, June). Identifying and improving disability bias in GPT-based resume screening. In Proceedings of the 2024 ACM Conference on Fairness, Accountability, and Transparency (pp. 687-700).

As Generative AI rises in adoption, its use has expanded to include domains such as hiring and recruiting. However, without examining the potential of bias, this may negatively impact marginalized populations, including people with disabilities. To address this important concern, we present a resume audit study, in which we ask ChatGPT (specifically, GPT-4) to rank a resume against the same resume enhanced with an additional leadership award, scholarship, panel presentation, and membership that are disability-related. We find that GPT-4 exhibits prejudice towards these enhanced CVs. Further, we show that this prejudice can be quantifiably reduced by training a custom GPTs on principles of DEI and disability justice. Our study also includes a unique qualitative analysis of the types of direct and indirect ableism GPT-4 uses to justify its biased decisions and suggest directions for additional bias mitigation work. Additionally, since these justifications are presumably drawn from training data containing real-world biased statements made by humans, our analysis suggests additional avenues for understanding and addressing human bias.

FabHacks with Everyday Objects

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Yuxuan Mei, Benjamin T. Jones, Dan Cascaval, Jennifer Mankoff, Etienne Vouga, Adriana Schulz: FabHacks: Transform Everyday Objects into Home Hacks Leveraging a Solver-aided DSL. SCF 2024: 4

Storing, organizing, and decorating are key parts of making a home nice. Buying new things for these tasks can be expensive, and reuse is better for the planet. One way to do this is with a “home hack.” This is when you use things you already have at home to solve a problem. But creating these hacks can be hard, especially if they are big, need to be nailed or screwed to the wall.

We have a system called FabHacks to help make these home hacks easier to create. It uses a new, hack-specific language we made called FabHaL to help you build these hacks. We looked at home hacks people share online and found ways to connect household items using specific methods. We also have a simple app to help you design such hacks. FabHacks, is based on a solver-aided domain-specific language (S-DSL). It leverages a physics-based solver that finds the expected physical configuration of a hack. We tested FabHacks by having people use our system, and they could easily make and try different designs.