Existing research has explored various methods to support people with noise sensitivity (PWNS), from desensitization therapies to technological solutions. However, there is a gap in systems that identify and monitor characteristics of noise sensitivity experiences to help PWNS and their companions better understand their condition and make informed management decisions. To fill this gap, we developed AudioBuddy, an app with sensing and tracking features designed to promote awareness between PWNS and their companions. We tested AudioBuddy as a technological probe over a two-week field deployment. Our results show that AudioBuddy can support awareness of how sounds and environments influence the psychophysiological states of PWNS, aiding in understanding noise sensitivity experiences. Nonetheless, technical limitations impacted the depth of awareness participants could attain. We discuss challenges and opportunities for future systems to facilitate awareness among PWNS and their companions.
Dental clinics can be challenging sensory environments, creating discomfort and stress, especially for neurodivergent individuals with Sensory Processing Disorder. Interactive environmental systems offer potential to transform these spaces, providing adaptable, sensory-inclusive experiences. However, the design space for environment-based interventions in dental settings remains largely unexplored. To address this, we conducted in-depth, 2-hour co-design sessions with 13 neurodivergent participants to explore environment-based strategies for meeting diverse sensory needs. We identified five core design goals for inclusive dental environments: experience transformation, distraction, exposure management, restoration, and social facilitation. Our technology-agnostic design catalogue can inform multiple implementation approaches, including projection mapping, ambient displays, and responsive physical elements. We contribute design patterns for interactive environmental systems, methodological insights for participatory design with neurodivergent communities, and demonstrate how tangible materials serve as proxies for environmental interventions, with implications for Augmented Reality system design. This study advances inclusive design practices and highlights co-designing with neurodivergent individuals.
Media representations of people with disabilities profoundly influence societal perceptions, yet have historically been absent, stereotyped, or inaccurate. As AI-generated visual media becomes increasingly prevalent, there is a critical opportunity to address these misrepresentations. Responding to the lack of collectively negotiated representation standards, this paper presents our human-centric approach to engaging disability communities meaningfully in AI data practices. Over three months, we worked closely with three disability organizations across the Global North and South to develop the Community Library Creator that introduces design scaffolds to support communities in defining ‘good’ representation and curating community-centric AI datasets; laying the foundations for community-specific evaluation metrics and future model adaptations. We contribute qualitative insights into the complexities of community-led data curation; discuss the value and practical challenges of intersecting human insights with AI requirements; and reflect on human-centered AI approaches that empower communities to share their perspectives and actively shape AI data practices.
Despite efforts to increase the representation of disabled people in AI datasets, accessibility datasets are often annotated by crowdworkers without disability-specific expertise, leading to inconsistent or inaccurate labels. This paper examines these annotation challenges through a case study of annotating speech data from people who stutter (PWS). Given the variability of stuttering and differing views on how it manifests, annotating and transcribing stuttered speech remains difficult, even for trained professionals. Through interviews and co-design workshops with PWS and domain experts, we identify challenges in stuttered speech annotation and develop practices that integrate the lived experiences of PWS into the annotation process. Our findings highlight the value of embodied knowledge in improving dataset quality, while revealing tensions between the complexity of disability experiences and the rigidity of static labels. We conclude with implications for disability-first and multiplicity-aware approaches to data interpretation across the AI pipeline.
Existing assistive technologies (AT) often adopt a one-size-fits-all approach, overlooking the diverse needs of people with visual impairments (PVI). Do-it-yourself AT (DIY-AT) toolkits offer one path toward customization, but most remain limited—targeting co-design with engineers or requiring programming expertise. Non-professionals with disabilities, including PVI, also face barriers such as inaccessible tools, lack of confidence, and insufficient technical knowledge. These gaps highlight the need for prototyping technologies that enable PVI to directly make their own AT. Building on emerging evidence that large language models (LLMs) can serve not only as visual aids but also as co-design partners, we present an exploratory study of how LLM-based AI can support PVI in the tangible DIY-AT co-making process. Our findings surface key challenges and design opportunities: the need for greater spatial and visual support, strategies for mitigating novel AI errors, and implications for designing more accessible AI-assisted prototypes.
Financial decision-making is critical to adult autonomy, yet many adults with Down syndrome (AwDS) have limited opportunities or support to develop money management skills, often receiving allowances while caregivers oversee financial obligations. To better understand the experiences AwDS have with budgeting and their support preferences, we designed and prototyped three cash-based budgeting technology probes: a gamified tablet application, a tablet-based augmented reality application, and a custom tangible device. Seven AwDS used all three prototypes to complete simplified money management tasks. Across probes, modality tradeoffs shaped engagement and checking: gamification increased interest but encouraged rushing; AR reduced arithmetic but encouraged users to trust the system’s output and skip verification; tangible controls supported participation yet introduced coordination challenges. Error recovery relied on brief, situated prompts linking screen and cash, shaped by prior budgeting/technology experience. These findings point to three design implications: (1) surface budgeting as a stimulating multi-goal puzzle, not just a sequence of steps; (2) design error recovery that connects screen state and real money; (3) support interdependent use without collapsing autonomy.
People with Intellectual Disabilities (ID) remain underrepresented in the co-design of technology, despite a growing emphasis on inclusive design within HCI. This scoping review synthesises knowledge on co-design methods by examining how people with ID and their support networks have been involved in technology design. A systematic search of four databases identified 25 relevant papers. Our analysis draws together the design methods and inclusion strategies used across these studies, highlighting practices, tools, and adaptations that accommodated diverse abilities, built trust, and supported agency. From this synthesis, we articulate how co-design practices have been tailored to promote inclusivity and propose principles and approaches to guide future research that centres ID perspectives. These findings provide researchers, designers, and practitioners with insights for fostering the equitable participation of people with ID in the design of technology.