Search

People with disabilities (PwD) regularly encounter ableist hate and microaggressions online. These spaces are generally moderated by machine learning models, but little is known about how effectively AI models identify ableist speech and how well their judgments align with PwD. To investigate this, we curated a first-of-its-kind dataset of 200 social media comments targeted towards PwD, and prompted state-of-the art AI models (i.e., Toxicity Classifiers, LLMs) to score toxicity and ableism for each comment, and explain their reasoning. Then, we recruited 190 participants to similarly rate and explain the harm, and evaluate LLM explanations. Our mixed-methods analysis highlighted a major disconnect: AI underestimated toxicity compared to PwD ratings, while its ableism assessments were sporadic and varied. Although LLMs identified some biases, its explanations were flawed--they lacked nuance, made incorrect assumptions, and appeared judgmental instead of educational. Going forward, we discuss challenges and opportunities in designing moderation systems for ableism, and advocate for the involvement of intersectional disabled perspectives in AI.

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., Comment: To appear at CHI 2024

Teachers of the visually impaired (TVIs) regularly present tactile materials (tactile graphics, 3D models, and real objects) to students with vision impairments. Researchers have been increasingly interested in designing tools to support the use of tactile materials, but we still lack an in-depth understanding of how tactile materials are created and used in practice today. To address this gap, we conducted interviews with 21 TVIs and a 3-week diary study with eight of them. We found that tactile materials were regularly used for academic as well as non-academic concepts like tactile literacy, motor ability, and spatial awareness. Real objects and 3D models served as "stepping stones" to tactile graphics and our participants preferred to teach with 3D models, despite finding them difficult to create, obtain, and modify. Use of certain materials also carried social implications; participants selected materials that fostered student independence and allow classroom inclusion. We contribute design considerations, encouraging future work on tactile materials to enable student and TVI co-creation, facilitate rapid prototyping, and promote movement and spatial awareness. To support future research in this area, our paper provides a fundamental understanding of current practices. We bridge these practices to established pedagogical approaches and highlight opportunities for growth regarding this important genre of educational materials., Comment: 35 pages, 6 figures, 3 tables, to be published in TACCESS