In accessibility research, the choice to adopt or abandon assistive technologies (AT) is often treated as a stable proxy for functional fit: to adopt is to confirm a good fit between device features and individual needs, and to abandon is to signal poor fit. While useful for design, we argue that the 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 recasts adoption not as a transparent expression of fit, but as situated negotiation of power. Drawing from an eight-month ethnographic study at a local nonprofit, we examine how low-income, racially-diverse, and disabled families navigate institutional cultures that reinforce normative expectations around disability and AT use. Building on postcolonial theories of power, we introduce the concept of minor resistance to describe the subtle, everyday tactics through which individuals lower the cost of access on their own terms. We argue that this shift in analytical lens reframes the goal of accessibility design from optimizing use to lowering the cost of choice. We conclude with implications for how designers can support community-driven responses to structural barriers by centering self-determination.

Equitable urban transportation applications require high-fidelity digital representations of the built environment (streets, crossings, curb ramps and more). Direct inspections and manual annotations are costly at scale, while conventional machine learning methods require substantial annotated training data for adequate performance. This study explores vision language models as a tool for annotating diverse urban features from satellite images, reducing the dependence on human annotation. Although these models excel at describing common objects in human-centric images, their training sets may lack signals for esoteric built environment features, making their performance uncertain. We demonstrate a proof-of-concept using a vision language model and a visual prompting strategy that considers segmented image elements. Experiments on two urban features --- stop lines and raised tables --- show that while zero-shot prompting rarely works, the segmentation and visual prompting strategies achieve nearly 40% intersection-over-union accuracy. We describe how these results motivate further research in automatic annotation of the built environment to improve equity, accessibility, and safety at scale and in diverse environments.

Inaccessible urban infrastructure creates and reinforces systemic exclusion of people with disabilities and impacts public health, physical activity, and quality of life for all. To improve the design of our cities and to enable more equitable policies and location-centric technology designs, we need new data collection techniques, data standards, and accessibility-infused analytic tools and interactive maps focused on the quality, safety, and accessibility of pathways, transit ecosystems, and buildings. In this workshop, we bring together leading experts in human mobility, urban design, disability, and accessible computing to discuss pressing urban access challenges across the world and brainstorm solutions. We invite contributions from practitioners, transit officials, disability advocates, and researchers.

Tactile maps can help people who are blind or have low-vision navigate and familiarize themselves with unfamiliar locations. Ideally, tactile maps can be customized to an individual’s unique needs and abilities because of their limited space for representation. We present Maptimizer, a tool that generates tactile maps based on users’ preferences and requirements. Maptimizer uses a two stage optimization process to pair representations with geographic information and tune those representations to present that information more clearly. In a small user study, Maptimizer helped participants more successfully and efficiently identify locations of interest in unknown areas. These results demonstrate the utility of optimization techniques and generative design in complex accessibility domains.

Data is an inseparable part of community management. Data openness and transparency has been a driver for change in government accountability and public engagement by providing unprecedented access to information. More prominently, there exists enthusiasm about the possibilities created by new and more extensive sources of data to improve our understanding and management of communities. This work examines a case study in collecting and operationalizing sustainable open data and specifically open government or civic data - information, public or otherwise, which anyone is free to access, analyze and re-use for any purpose - through a platform and community organizing effort in crowdsourcing open pedestrian network data. We outline a number of tensions or challenges in opening data, specifically in a number of realms where public interest stands to benefit from uses of the data, yet no single commercial or governmental entity is either liable or has a clear monetary interest associated with freely opening that data. In these specific cases, collection of these open data becomes a community-based challenge to undertake, which raises a number of additional socio-technical, political, and data provenance considerations. Beyond the technical contributions of our framework (in the open-source tools to support community activities, our case study contributes a number of insights and recommendations regarding community engagement, use of participatory co-design jointly with data collection tools, and planning for sustainable data stewardship in the involved communities.

Sidewalks are central to an accessible transportation network, as they connect all other transportation modes. The street-side environment, especially the location and connectivity of the sidewalks, has not been widely integrated into information systems used to report accessibility and walkability in wayfinding applications. Typical sidewalk mapping methods rely on surveyor collections, which are non-standardized, laborious, costly, difficult to maintain, and do not scale well. In this work, we introduce a working proof-of-concept system for automated mapping of sidewalk networks on portable computing devices. Our system utilizes efficient neural networks, image sensing, GPS, and compact hardware to perform sidewalk mapping on portable devices. We discuss future opportunities for cities and transportation agencies to advance their knowledge of the transportation network they own and manage in order to improve accessibility for all travelers.

A robot-assisted feeding system can potentially help a user with upper-body mobility impairments eat independently. However, autonomous assistance in the real world is challenging because of varying user preferences, impairment constraints, and possibility of errors in uncertain and unstructured environments. An autonomous robot-assisted feeding system needs to decide the appropriate strategy to acquire a bite of hard-to-model deformable food items, the right time to bring the bite close to the mouth, and the appropriate strategy to transfer the bite easily. Our key insight is that a system should be designed based on a user's preference about these various challenging aspects of the task. In this work, we explore user preferences for different modes of autonomy given perceived error risks and also analyze the effect of input modalities on technology acceptance. We found that more autonomy is not always better, as participants did not have a preference to use a robot with partial autonomy over a robot with low autonomy. In addition, participants' user interface preference changes from voice control during individual dining to web-based during social dining. Finally, we found differences on average ratings when grouping the participants based on their mobility limitations (lower vs. higher) that suggests that ratings from participants with lower mobility limitations are correlated with higher expectations of robot performance.

This panel will provide practical advice on what and how to teach accessibility in a variety of settings. In this context, teaching accessibility means teaching about computer technologies that people with various disabilities can use and be productive with. At the undergraduate level it could mean teaching about how to design and build accessible web sites and applications. At the graduate level it could be teaching about building applications that can help people with disabilities with specific tasks. An entire course could focus on accessibility or it could be just part of an existing course. It is also important to learn about the diversity of consumers of technologies: what their abilities are and what access infrastructures they use every day. All the panelists have extensive experience in teaching accessibility. They will provide the audience of the panel deep insights into what they might do to teach accessibility in their own courses.

Robot-assisted feeding (RAF) systems offer enormous potential benefits to community-centered care-giving environments. However, developers of RAF technologies often focus on evaluating their standard transactional functionality, omitting the impact of such technologies in contexts that extend past the interaction of the robot and food receiver. RAF technologies have complex social, cultural and self-identity implications, since a "meal" extends well beyond the simple provisioning of nourishment. To better understand these implications we conducted a contextual inquiry in an assisted-living community with five potential care recipients and five caregivers, as well as interviews with fifteen domain experts including occupational therapists and feeding specialists. Based on our findings from these studies, we developed a new framework for RAF technologies that formulates this vital task as a community-centered relational service. We then use this framework to qualitatively and quantitatively assess three existing feeding systems and identify areas of improvement. Our work reveals new insights about stakeholders of RAF technologies and provides a roadmap for technology developers to better serve the needs of these stakeholders.

Despite significant heterogeneity in pedestrian mobility, maps and trip planning services have traditionally treated pedestrians as a monolithic, limited extension to street traffic-centric approaches. Here, we present a demonstration of the AccessMap website, an open source, city-scale, interactive web map based on open data that provides individualized pedestrian infrastructure information and automatic trip planning services. Via the AccessMap website, customizable settings instigate real-time visual feedback of infrastructure accessibility and are used to automatically generate bespoke trip plans via an open API.

We introduce interaction proxies as a strategy for runtime repair and enhancement of the accessibility of mobile applications. Conceptually, interaction proxies are inserted between an application's original interface and the manifest interface that a person uses to perceive and manipulate the application. This strategy allows third-party developers and researchers to modify an interaction without an application's source code, without rooting the phone, without otherwise modifying an application, while retaining all capabilities of the system (e.g., Android's full implementation of the TalkBack screen reader). This paper introduces interaction proxies, defines a design space of interaction re-mappings, identifies necessary implementation abstractions, presents details of implementing those abstractions in Android, and demonstrates a set of Android implementations of interaction proxies from throughout our design space. We then present a set of interviews with blind and low-vision people interacting with our prototype interaction proxies, using these interviews to explore the seamlessness of interaction, the perceived usefulness and potential of interaction proxies, and visions of how such enhancements could gain broad usage. By allowing third-party developers and researchers to improve an interaction, interaction proxies offer a new approach to personalizing mobile application accessibility and a new approach to catalyzing development, deployment, and evaluation of mobile accessibility enhancements.