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The Impact of Generative AI Coding Assistants on Developers Who Are Visually Impaired

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arxiv 2503.16491 v1 pith:NQNSIG2L submitted 2025-03-10 cs.HC cs.AIcs.CY

classification cs.HCcs.AIcs.CY
keywords codingdevelopersassistantsgenerativeaccessibilityassistantchallengesimpaired
verification ladder T0 review T1 audit T2 compute T3 formal
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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.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. "Before, I Asked My Mom, Now I Ask ChatGPT": Visual Privacy Management with Generative AI for Blind and Low-Vision People

    cs.HC 2025-06 conditional novelty 6.0 of 10

    Blind and low vision people already use generative AI to protect their visual privacy, and they want future tools to process data locally with zero-retention guarantees and sensitive-content redaction.

  2. Single Conversation Methodology: A Human-Centered Protocol for AI-Assisted Software Development

    cs.SE 2025-07 conditional novelty 5.0 of 10

    Proposes a structured protocol for LLM-assisted development that keeps requirements, code, and documentation inside a single persistent conversation to preserve human oversight and traceability.

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