Virtual collaboration has transformed how people in mixed-ability teams, composed of disabled and non-disabled people, work together by offering greater flexibility. In these settings, accessibility practices, such as accommodations and inclusive norms, are essential for providing access to disabled people. However, we do not yet know how these practices shape broader facets of teamwork, such as productivity, participation, and camaraderie. To address this gap, we interviewed 18 participants (12 disabled, 6 non-disabled) who are part of mixed-ability teams. We found that beyond providing access, accessibility practices shaped how all participants coordinated tasks, sustained rapport, and negotiated responsibilities. Accessibility practices also introduced camaraderie challenges, such as balancing empathy and accountability. Non-disabled participants described allyship as a learning process and skill shaped by their disabled team members and team culture. Based on our findings, we present recommendations for team practices and design opportunities for virtual collaboration tools that reframe accessibility practices as a foundation for strong teamwork.

Multimodal large language models (MLLMs) are changing how Blind and Low Vision (BLV) people access visual information. Unlike traditional visual interpretation tools that only provide descriptions, MLLM-enabled applications offer conversational assistance, where users can ask questions to obtain goal-relevant details. However, evidence about their performance in the real-world and implications for BLV people’s daily lives remains limited. To address this, we conducted a two-week diary study, where we captured 20 BLV participants’ use of an MLLM-enabled visual interpretation application. Although participants rated the visual interpretations of the application as "trustworthy" (mean=3.76 out of 5, max=extremely trustworthy) and "somewhat satisfying" (mean=4.13 out of 5, max=very satisfying), the AI often produced incorrect answers (22.2%) or abstained (10.8%) from responding to users’ requests. Our findings show that while MLLMs can improve visual interpretations’ descriptive accuracy, supporting everyday use also depends on the “visual assistant” skill: behaviors for providing goal-directed, reliable assistance. We conclude by proposing the "visual assistant" skill and guidelines to help MLLM-enabled visual interpretation applications better support BLV people’s access to visual information.

Social VR has increased in popularity due to its affordances for rich, embodied, and nonverbal communication. However, nonverbal communication remains inaccessible for blind and low vision people in social VR. We designed accessible cues with audio and haptics to represent three nonverbal behaviors: eye contact, head shaking, and head nodding. We evaluated these cues in real-time conversation tasks where 16 blind and low vision participants conversed with two other users in VR. We found that the cues were effective in supporting conversations in VR. Participants had statistically significantly higher scores for accuracy and confidence in detecting attention during conversations with the cues than without. We also found that participants had a range of preferences and uses for the cues, such as learning social norms. We present design implications for handling additional cues in the future, such as the challenges of incorporating AI. Through this work, we take a step towards making interpersonal embodied interactions in VR fully accessible for blind and low vision people.

While audio description (AD) is the standard approach for making videos accessible to blind and low vision (BLV) people, existing AD guidelines do not consider BLV users’ varied preferences across viewing scenarios. These scenarios range from how-to videos on YouTube, where users seek to learn new skills, to historical dramas on Netflix, where a user’s goal is entertainment. Additionally, the increase in video watching on mobile devices provides an opportunity to integrate nonverbal output modalities (e.g., audio cues, tactile elements, and visual enhancements). Through a formative survey and 15 semi-structured interviews, we identified BLV people’s video accessibility preferences across diverse scenarios. For example, participants valued action and equipment details for how-to videos, tactile graphics for learning scenarios, and 3D models for fantastical content. We define a six-dimensional video accessibility design space to guide future innovation and discuss how to move from “one-size-fits-all” paradigms to scenario-specific approaches.

As social VR applications grow in popularity, blind and low vision users encounter continued accessibility barriers. Yet social VR, which enables multiple people to engage in the same virtual space, presents a unique opportunity to allow other people to support a user’s access needs. To explore this opportunity, we designed a framework based on physical sighted guidance that enables a guide to support a blind or low vision user with navigation and visual interpretation. A user can virtually hold on to their guide and move with them, while the guide can describe the environment. We studied the use of our framework with 16 blind and low vision participants and found that they had a wide range of preferences. For example, we found that participants wanted to use their guide to support social interactions and establish a human connection with a human-appearing guide. We also highlight opportunities for novel guidance abilities in VR, such as dynamically altering an inaccessible environment. Through this work, we open a novel design space for a versatile approach for making VR fully accessible.

Conversational assistants, an inherently accessible mode of interaction for blind and low vision (BLV) individuals, offer opportunities to support nonvisual access in new ways. In this paper, we explore whether and how human-like conversations can support access to interfaces, advancing the impersonal linear access provided by screen readers today. We first interviewed 10 BLV participants about this approach, but found it difficult to situate conversations around a future technology. So we turned to a speculative design approach and created four audio fictions: pre-recorded dialogues between users and their hypothetical screen reader assistants wherein assistants assumed distinct roles: a friend, butler, expert, and caregiver. We presented the audio fictions to 14 BLV participants and found that personable conversations can meaningfully extend the screen reader experience. We observed a tension between AI adaptation and screen reader customization. Participants further expressed a need to maintain control at three distinct levels: granular cursor movement, screen representation, and task assistance. Through the lens of assistant roles, we address fundamental questions about anthropomorphizing CAs and assistive technology broadly.

The data table is a basic but versatile representation to communicate data. From government reports to bank statements, tables effectively carry essential data-driven information by visually organizing data using rows, columns, and other arrangements (e.g., merged cells). However, many tables online neglect the accessibility requirements for people who rely on screen readers, such as people who are blind or have low vision (BLV). First, we consolidated guidelines to understand what makes a table inaccessible for BLV people. We conducted an interview study to understand the importance of tables and identify further design requirements for an accessible table. We built a tool that automatically detects HTML formatted tables online and transforms them into accessible tables. Our evaluative study demonstrates how our tool can help participants understand the table’s structure and layout and support smooth navigation when the table is large and complex.

Abstract Sonification can be an effective medium for people with visual impairments to understand data in visualizations. However, there are no universal design principles that apply to various charts that encode different data types. Towards generalizable principles, we conducted an exploratory experiment to assess how different auditory channels (e.g., pitch, volume) impact the data and visualization perception among people with visual impairments. In our experiment, participants evaluated the intuitiveness and accuracy of the mapping of auditory channels on different data and chart types. We found that participants rated pitch to be the most intuitive, while the number of tappings and the length of sounds yielded the most accurate perception in decoding data. We study how audio channels can intuitively represent different charts and demonstrate that data‐level perception might not directly transfer to chart‐level perception as participants reflect on visual aspects of the charts while listening to audio. We conclude by how future experiments can be designed to establish a robust ranking for creating audio charts.

Alternative text is critical in communicating graphics to people who are blind or have low vision. Especially for graphics that contain rich information, such as visualizations, poorly written or an absence of alternative texts can worsen the information access inequality for people with visual impairments. In this work, we consolidate existing guidelines and survey current practices to inspect to what extent current practices and recommendations are aligned. Then, to gain more insight into what people want in visualization alternative texts, we interviewed 22 people with visual impairments regarding their experience with visualizations and their information needs in alternative texts. The study findings suggest that participants actively try to construct an image of visualizations in their head while listening to alternative texts and wish to carry out visualization tasks (e.g., retrieve specific values) as sighted viewers would. The study also provides ample support for the need to reference the underlying data instead of visual elements to reduce users' cognitive burden. Informed by the study, we provide a set of recommendations to compose an informative alternative text.