What do Blind and Low-Vision People Really Want from Assistive Smart Devices? Comparison of the Literature with a Focus Study

TL;DR

This study compares existing AI-based assistive devices for blind and low-vision individuals with their actual needs, revealing misalignments and preferences for conversational interfaces and head-mounted devices.

Contribution

It provides a comprehensive analysis of recent research and directly surveys BLV users to identify gaps and preferences in assistive AI technology.

Findings

Weak correlation between research focus and user priorities

Participants favor conversational agents and head-mounted devices

Research often does not align with user needs

Abstract

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.