What do Blind and Low-Vision People Really Want from Assistive Smart Devices? Comparison of the Literature with a Focus Study
Not on the map. Why?
Abstract (arXiv)
Over the last decade there has been considerable research into how artificial intelligence (AI), specifically computer vision, can assist people who are blind or have low-vision (BLV) to understand their environment. However, there has been almost no research into whether the tasks (object detection, image captioning, text recognition etc.) and devices (smartphones, smart-glasses etc.) investigated by researchers align with the needs and preferences of BLV people. We identified 646 studies published in the last two and a half years that have investigated such assistive AI techniques. We analysed these papers to determine the task, device and participation by BLV individuals. We then interviewed 24 BLV people and asked for their top five AI-based applications and to rank the applications found in the literature. We found only a weak positive correlation between BLV participants' perceived importance of tasks and researchers' focus and that participants prefer conversational agent interface and head-mounted devices.
Key facts. Cited by 6 papers in the map (data through 14 Oct 2026). First posted on arXiv 25 May 2025.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2025: 3; 2026: 3.
6 papers.
- 2025"It's trained by non-disabled people": Evaluating How Image Quality Affects Product Captioning with Vision-Language Modelscited by 3
- 2025Less Redundancy: Boosting Practicality of Vision Language Model in Walking Assistantscited by 2
- 2025Situat3DChange: Situated 3D Change Understanding Dataset for Multimodal Large Language Modelcited by 2
- 2026Say It My Way: Exploring Control in Conversational Visual Question Answering with Blind Userscited by 2
- 2026Cripping AI: Reimagining AI Through Lived Disability Experiencescited by 0
- 2026Bespoke Visual Assistance: What and How do Blind and Low-Vision People Create with Agentic Programming?cited by 0
- 2026Bespoke Visual Assistance: What and How do Blind and Low-Vision People Create with Agentic Programming?23 Jul 2026
- 2026Cripping AI: Reimagining AI Through Lived Disability Experiences3 May 2026
- 2026Say It My Way: Exploring Control in Conversational Visual Question Answering with Blind Users18 Feb 2026
- 2025"It's trained by non-disabled people": Evaluating How Image Quality Affects Product Captioning with Vision-Language Models12 Nov 2025
- 2025Situat3DChange: Situated 3D Change Understanding Dataset for Multimodal Large Language Model13 Oct 2025
- 2025Less Redundancy: Boosting Practicality of Vision Language Model in Walking Assistants22 Aug 2025