Performance on Activities of Daily Living and User Experience When Using Artificial Intelligence by Individuals With Vision Impairment
William Seiple, Hilde P. A. van der Aa, Fernanda Garcia‐Piña, Izekiel Greco, Calvin W. Roberts, Ruth M. A. van Nispen
Abstract
Purpose: This study assessed objective performance, usability, and acceptance of artificial intelligence (AI) by people with vision impairment. The goal was to provide evidence-based data to enhance technology selection for people with vision loss (PVL) based on their loss and needs. Methods: Using a cross-sectional, counterbalanced, cross-over study involving 25 PVL, we compared performance using two smart glasses (OrCam and Envision Glasses) and two AI apps (Seeing AI and Google Lookout). We refer to these as assistive artificial intelligence implementations (AAIIs). Completion and timing were quantified for three task categories: text, text in columns, and searching and identifying. Usability was evaluated with the System Usability Scale (SUS). Results: The odds ratios (ORs) of being able to complete Text tasks were significantly higher when using AAIIs compared to the baseline. OR when performing "Searching and Identifying" tasks varied among AAIIs, with Seeing AI and Envision improving the performance of more tasks than Lookout or OrCam. Participants expressed high satisfaction with the AAIIs. Conclusions: Despite the findings that performance on some tasks and when using some AAIIs did not result in a greater number of PVL being able to complete the tasks, there was overall high satisfaction, reflecting an acceptance of AI as an assistive technology and the promise of this developing technology. Translational Relevance: This evidence-based performance data provide guidelines for clinicians when recommending an AAII to PVL.