The Impact of Generative AI Coding Assistants on Developers Who Are Visually Impaired
Claudia Flores-Saviaga, Benjamin V. Hanrahan, Kashif Imteyaz, Steven Clarke, Saiph Savage
TL;DR
The paper tackles how generative AI coding assistants affect developers with visual impairments, addressing a gap in accessibility research. Using Activity Theory, it analyzes a qualitative study of 10 participants interacting with GitHub Copilot in Visual Studio Code, identifying both productivity gains and new barriers related to context switching and cognitive load. Key contributions include a framework for analyzing AI-mediated coding activities, evidence of AI timeouts as a needed design feature, and concrete design recommendations (context histories, interaction organizers, and customizable AI behavior) to align AI assistance with nonvisual workflows. The findings have practical implications for building more inclusive AI coding tools that balance proactive support with user autonomy, ultimately advancing accessibility in software development.
Abstract
The rapid adoption of generative AI in software development has impacted the industry, yet its effects on developers with visual impairments remain largely unexplored. To address this gap, we used an Activity Theory framework to examine how developers with visual impairments interact with AI coding assistants. For this purpose, we conducted a study where developers who are visually impaired completed a series of programming tasks using a generative AI coding assistant. We uncovered that, while participants found the AI assistant beneficial and reported significant advantages, they also highlighted accessibility challenges. Specifically, the AI coding assistant often exacerbated existing accessibility barriers and introduced new challenges. For example, it overwhelmed users with an excessive number of suggestions, leading developers who are visually impaired to express a desire for ``AI timeouts.'' Additionally, the generative AI coding assistant made it more difficult for developers to switch contexts between the AI-generated content and their own code. Despite these challenges, participants were optimistic about the potential of AI coding assistants to transform the coding experience for developers with visual impairments. Our findings emphasize the need to apply activity-centered design principles to generative AI assistants, ensuring they better align with user behaviors and address specific accessibility needs. This approach can enable the assistants to provide more intuitive, inclusive, and effective experiences, while also contributing to the broader goal of enhancing accessibility in software development.