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

arXiv: https://arxiv.org/abs/2503.16491 · HTML: https://mlsanity.com/paper/2503.16491/

## Key facts

- Cited by 7 papers in the map (data through 14 Oct 2026).
- Builds on 21 of its 112 references that are in the map.
- First posted on arXiv 10 Mar 2025.

## Builds on (most cited first, 21 of 21)

- [Large Language Models for Software Engineering: A Systematic Literature Review](https://mlsanity.com/paper/2308.10620/) (2023)
- [The Impact of AI on Developer Productivity: Evidence from GitHub Copilot](https://mlsanity.com/paper/2302.06590/) (2023)
- [GitHub Copilot AI pair programmer: Asset or Liability?](https://mlsanity.com/paper/2206.15331/) (2022)
- [Productivity Assessment of Neural Code Completion](https://mlsanity.com/paper/2205.06537/) (2022)
- [Reading Between the Lines: Modeling User Behavior and Costs in AI-Assisted Programming](https://mlsanity.com/paper/2210.14306/) (2022)
- [Studying the effect of AI Code Generators on Supporting Novice Learners in Introductory Programming](https://mlsanity.com/paper/2302.07427/) (2023)
- [A Large-Scale Survey on the Usability of AI Programming Assistants: Successes and Challenges](https://mlsanity.com/paper/2303.17125/) (2023)
- [Design Principles for Generative AI Applications](https://mlsanity.com/paper/2401.14484/) (2024)
- [Prompting Large Language Models to Tackle the Full Software Development Lifecycle: A Case Study](https://mlsanity.com/paper/2403.08604/) (2024)
- [Investigating and Designing for Trust in AI-powered Code Generation Tools](https://mlsanity.com/paper/2305.11248/) (2023)
- [Natural Language Generation and Understanding of Big Code for AI-Assisted Programming: A Review](https://mlsanity.com/paper/2307.02503/) (2023)
- [Navigating the Complexity of Generative AI Adoption in Software Engineering](https://mlsanity.com/paper/2307.06081/) (2023)
- [How Beginning Programmers and Code LLMs (Mis)read Each Other](https://mlsanity.com/paper/2401.15232/) (2024)
- [Is AI the better programming partner? Human-Human Pair Programming vs. Human-AI pAIr Programming](https://mlsanity.com/paper/2306.05153/) (2023)
- [Rich Screen Reader Experiences for Accessible Data Visualization](https://mlsanity.com/paper/2205.04917/) (2022)
- [Datavoidant: An AI System for Addressing Political Data Voids on Social Media](https://mlsanity.com/paper/2210.13594/) (2022)
- [The Transformative Influence of LLMs on Software Development & Developer Productivity](https://mlsanity.com/paper/2311.16429/) (2023)
- [Chart4Blind: An Intelligent Interface for Chart Accessibility Conversion](https://mlsanity.com/paper/2403.06693/) (2024)
- [The Global Care Ecosystems of 3D Printed Assistive Devices](https://mlsanity.com/paper/2210.14984/) (2022)
- [Understanding the Career Mobility of Blind and Low Vision Software Professionals](https://mlsanity.com/paper/2404.17036/) (2024)
- [Accessibility evaluation of major assistive mobile applications available for the visually impaired](https://mlsanity.com/paper/2407.17496/) (2024)

## Built on by (most cited first, 7 of 7)

- ["Before, I Asked My Mom, Now I Ask ChatGPT": Visual Privacy Management with Generative AI for Blind and Low-Vision People](https://mlsanity.com/paper/2507.00286/) (2025)
- [Vibe Coding in Product Teams: Reconfiguring AI-Assisted Workflows, Prototyping, and Collaboration](https://mlsanity.com/paper/2509.10652/) (2025)
- [Finding the Signal in the Noise: An Exploratory Study on Assessing the Effectiveness of AI and Accessibility Forums for Blind Users' Support Needs](https://mlsanity.com/paper/2602.18623/) (2026)
- [Dr. Claw: An AI Scientist Workspace for Vibe Research](https://mlsanity.com/paper/2609.00365/) (2026)
- [Single Conversation Methodology: A Human-Centered Protocol for AI-Assisted Software Development](https://mlsanity.com/paper/2507.12665/) (2025)
- [Upskilling with Generative AI: Practices and Challenges for Freelance Knowledge Workers](https://mlsanity.com/paper/2604.27231/) (2026)
- [Gricea: An Open Science Platform for Conversational AI Research](https://mlsanity.com/paper/2609.22039/) (2026)

## Abstract (arXiv)

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.