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• "We Figure It Out Together": A Framework for Relational Communication in Disabled and Neurodivergent LGBTQIA+ Romantic Partnerships

  Kirk Andrew Crawford, Foad Hamidi · 2026 · Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems (CHI '26)

  Crawford and Hamidi investigate how disabled and neurodivergent LGBTQIA+ romantic partners collaboratively build and sustain communication practices over time, an area largely overlooked in HCI research that has tended to focus on single points in time or on specific…

  cognitive accessibility · neurodiversity · LGBTQIA+ · disability · intersectionality

• "Computer Says No": Disabled Welfare Experiences and Envisioned Futures Under AI Governance

  Humphrey Curtis, Adam D G Jenkins, Alistair Gentry, Sioban Zacharek, Sally McVicker, Timothy Neate, Filip Bircanin · 2026 · Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems (CHI '26)

  Curtis and colleagues investigate how people with aphasia — a language impairment most often caused by stroke that affects reading, writing, speech, and comprehension — experience the increasingly digitised and AI-automated UK welfare state, and how they would redesign it. The…

  AI · artificial intelligence · AI governance · algorithmic decision-making · aphasia

• SceneScout: Towards AI-Driven Access to Street Level Imagery for Blind Users

  Gaurav Jain, Leah Findlater, Cole Gleason · 2026 · Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems (CHI '26)

  Jain, Findlater and Gleason present SceneScout, a prototype web interface that uses a multimodal large language model (GPT-4o) to make street level imagery — the panoramic pedestrian-height photography behind Apple Maps Look Around and Google Street View — directly usable by…

  accessibility · navigation · screen readers · AI · multimodal AI

• From Struggle to Success: Context-Aware Guidance for Screen Reader Users in Computer Use

  Nan Chen, Jing Lu, Zilong Wang, Luna K. Qiu, Siming Chen, Yuqing Yang · 2026 · Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems (CHI '26)

  Chen, Lu, Wang, Qiu, Chen and Yang present AskEase, an NVDA add-on that delivers on-demand, step-by-step, screen-reader-friendly guidance for blind and low-vision computer users tackling unfamiliar desktop software. The work responds to a persistent problem: mainstream tutorials…

  accessibility · screen readers · AI · LLM · assistive technology

• The ORBIT India Dataset: Understanding the Challenges of Collecting a Disability-First AI Dataset in Low-Resource Environments

  Gesu India, Martin Grayson, Cecily Morrison, Daniela Massiceti, Simon Robinson, Jennifer Pearson, Matt Jones · 2026 · Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems (CHI '26)

  This paper introduces ORBIT-India, the first teachable object recognition dataset contributed entirely by people who are blind or have low vision in India. It extends the UK/Canada-collected ORBIT dataset (Massiceti et al., 2021) to the Indian context — home of the world's…

  AI · accessibility · datasets · teachable object recognition · vision impairment

• How Multimodal Large Language Models Support Access to Visual Information: A Diary Study With Blind and Low Vision People

  Ricardo E. Gonzalez Penuela, Crescentia Jung, Sharon Lin, Ruiying Hu, Shiri Azenkot · 2026 · Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems (CHI '26)

  This CHI 2026 paper reports a two-week diary study with 20 Blind and Low Vision (BLV) participants (ages 19–75, 11 female/9 male, 13 blind/7 low vision) investigating how multimodal large language models (MLLMs) support real-world access to visual information. The authors built…

  AI · accessibility · multimodal large language models · MLLM · visual question answering

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