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Generative AI tools, particularly those utilizing large language models (LLMs), have become increasingly prevalent in both professional and personal contexts, offering powerful capabilities for text generation and communication support. While these tools are widely used to enhance productivity and accessibility, there has been limited exploration of how Deaf and Hard of Hearing (DHH) individuals engage with text-based generative AI tools, as well as the challenges they may encounter. This paper presents a mixed-method survey study investigating how the DHH community uses Text AI tools, such as ChatGPT, to reduce communication barriers, bridge Deaf and hearing cultures, and improve access to information. Through a survey of 80 DHH participants and separate interviews with 11 other participants, we found that while these tools provide significant benefits, including enhanced communication and mental health support, they also introduce barriers, such as a lack of American Sign Language (ASL) support and understanding of Deaf cultural nuances. Our findings highlight unique usage patterns within the DHH community and underscore the need for inclusive design improvements. We conclude by offering practical recommendations to enhance the accessibility of Text AI for the DHH community and suggest directions for future research in AI and accessibility.

With the recent rapid rise in Generative Artificial Intelligence (GAI) tools, it is imperative that we understand their impact on people with disabilities, both positive and negative. However, although we know that AI in general poses both risks and opportunities for people with disabilities, little is known specifically about GAI in particular. To address this, we conducted a three-month autoethnography of our use of GAI to meet personal and professional needs as a team of researchers with and without disabilities. Our findings demonstrate a wide variety of potential accessibility-related uses for GAI while also highlighting concerns around verifiability, training data, ableism, and false promises.

Digital avatars are an important part of identity representation, but there is little work on understanding how to represent disability. We interviewed 18 people with disabilities and related identities about their experiences and preferences in representing their identities with avatars. Participants generally preferred to represent their disability identity if the context felt safe and platforms supported their expression, as it was important for feeling authentically represented. They also utilized avatars in strategic ways: as a means to signal and disclose current abilities, access needs, and to raise awareness. Some participants even found avatars to be a more accessible way to communicate than alternatives. We discuss how avatars can support disability identity representation because of their easily customizable format that is not strictly tied to reality. We conclude with design recommendations for creating platforms that better support people in representing their disability and other minoritized identities.

Many individuals with disabilities and/or chronic conditions (da/cc) experience symptoms that may require intermittent or on-going medical care. However, healthcare is an often-overlooked domain for accessibility work, where access needs associated with temporary and long-term disability must be addressed to increase the utility of physical and digital interactions with healthcare workers and spaces. Our work focuses on a specific domain of healthcare often used by individuals with da/cc: physical therapy (PT). Through a twelve-person interview study, we examined how people's access to PT for their da/cc is hampered by social (e.g., physically visiting a PT clinic) and physiological (e.g., chronic pain) barriers, and how technology could improve PT access. In-person PT is often inaccessible to our participants due to lack of transportation and insufficient insurance coverage. As such, many of our participants relied on at-home PT to manage their da/cc symptoms and work towards PT goals. Participants felt that PT barriers, such as having particularly bad symptoms or feeling short on time, could be addressed with well-designed technology that flexibly adapts to the person's dynamically changing needs while supporting their PT goals. We introduce core design principles (adaptability, movement tracking, community building) and tensions (insurance) to consider when developing technology to support PT access. Rethinking da/cc access to PT from a lens that includes social and physiological barriers presents opportunities to integrate accessibility and adaptability into PT technology., Comment: 22 pages, 2 tables

Accessibility research sits at the junction of several disciplines, drawing influence from HCI, disability studies, psychology, education, and more. To characterize the influences and extensions of accessibility research, we undertake a study of citation trends for accessibility and related HCI communities. We assess the diversity of venues and fields of study represented among the referenced and citing papers of 836 accessibility research papers from ASSETS and CHI, finding that though publications in computer science dominate these citation relationships, the relative proportion of citations from papers on psychology and medicine has grown over time. Though ASSETS is a more niche venue than CHI in terms of citational diversity, both conferences display standard levels of diversity among their incoming and outgoing citations when analyzed in the context of 53K papers from 13 accessibility and HCI conference venues., Comment: 11 pages, 5 figures, 3 tables, 2 appendices; CHI LBW 2021; accessible PDF available at https://makeabilitylab.cs.washington.edu/

The NIH 3D Print Exchange is a public and open source repository for primarily 3D printable medical device designs with contributions from expert-amateur makers, engineers from industry and academia, and clinicians. In response to the COVID-19 pandemic, a collection was formed to foster submissions of low-cost, local manufacture of personal protective equipment (Personal Protective Equipment (PPE)). We systematically evaluated the 623 submissions in this collection to understand: what makers contributed, how they were made, who made them, and key characteristics of their designs. Our analysis reveals an immediate design convergence to derivatives of a few initial designs affiliated with NIH partners (e.g., universities, the Veteran's Health Administration, America Makes) and major for-profit groups (e.g., Prusa). The NIH worked to review safe and effective designs but was quickly overloaded by derivative works. We found that the vast majority were never reviewed (81.3%) while 10.4% of those reviewed were deemed safe for clinical (5.6%) or community use (4.8%). Our work contributes insights into: the outcomes of distributed, community-based, medical making; features the community accepted as "safe" making; and how platforms can support regulated maker activities in high-risk domains (e.g., healthcare).

Accessibility research has grown substantially in the past few decades, yet there has been no literature review of the field. To understand current and historical trends, we created and analyzed a dataset of accessibility papers appearing at CHI and ASSETS since ASSETS' founding in 1994. We qualitatively coded areas of focus and methodological decisions for the past 10 years (2010-2019, N=506 papers), and analyzed paper counts and keywords over the full 26 years (N=836 papers). Our findings highlight areas that have received disproportionate attention and those that are underserved--for example, over 43% of papers in the past 10 years are on accessibility for blind and low vision people. We also capture common study characteristics, such as the roles of disabled and nondisabled participants as well as sample sizes (e.g., a median of 13 for participant groups with disabilities and older adults). We close by critically reflecting on gaps in the literature and offering guidance for future work in the field.

Social media platforms support the sharing of written text, video, and audio. All of these formats may be inaccessible to people who are deaf or hard of hearing (DHH), particularly those who primarily communicate via sign language, people who we call Deaf signers. We study how Deaf signers engage with social platforms, focusing on how they share content and the barriers they face. We employ a mixed-methods approach involving seven in-depth interviews and a survey of a larger population (n = 60). We find that Deaf signers share the most in written English, despite their desire to share in sign language. We further identify key areas of difficulty in consuming content (e.g., lack of captions for spoken content in videos) and producing content (e.g., captioning signed videos, signing into a phone camera) on social media platforms. Our results both provide novel insights into social media use by Deaf signers and reinforce prior findings on DHH communication more generally, while revealing potential ways to make social media platforms more accessible to Deaf signers.

In traditional usability studies, researchers talk to users of tools to understand their needs and challenges. Insights gained via such interviews offer context, detail, and background. Due to costs in time and money, we are beginning to see a new form of tool interrogation that prioritizes scale, cost, and breadth by utilizing existing data from online forums. In this case study, we set out to apply this method of using online forum data to a specific issue---challenges that users face with Excel spreadsheets. Spreadsheets are a versatile and powerful processing tool if used properly. However, with versatility and power come errors, from both users and the software, which make using spreadsheets less effective. By scraping posts from the website Reddit, we collected a dataset of questions and complaints about Excel. Specifically, we explored and characterized the issues users were facing with spreadsheet software in general, and in particular, as resulting from a large amount of data in their spreadsheets. We discuss the implications of our findings on the design of next-generation spreadsheet software.