White, L. L. A., & Amani, S., & Balart, T. S., & Lacy, A. K., & Kim, G. S., & Raju, G., & Watson, K., & Shryock, K. J. (2025, February), Impact of Generative AI Technologies on Blind and Visually Impaired Students: A Case Study  Paper presented at 2025 Collaborative Network for Engineering & Computing Diversity (CoNECD), San Antonio, Texas. https://peer.asee.org/54098

\bibitem{asee_peer_54098}
  White, L. L. A., \& Amani, S., \& Balart, T. S., \& Lacy, A. K., \& Kim, G. S., \& Raju, G., \& Watson, K., \& Shryock, K. J. (2025, February), \emph{Impact of Generative AI Technologies on Blind and Visually Impaired Students: A Case Study}
  Paper presented at 2025 Collaborative Network for Engineering \& Computing Diversity (CoNECD), San Antonio, Texas.
  https://peer.asee.org/54098

Lance Leon Allen White, Sara Amani, Trini Sofia Balart, Amanda Kate Lacy, Gene Sung-Ho Kim, Gibin Raju, Karan Watson P.E., and Kristi J. Shryock.  "Impact of Generative AI Technologies on Blind and Visually Impaired Students: A Case Study".  2025 Collaborative Network for Engineering & Computing Diversity (CoNECD), San Antonio, Texas, 2025, February.  ASEE Conferences, 2025.  https://peer.asee.org/54098 Internet.  24 Mar, 2025

\bibitem{asee_peer_54098}
  Lance Leon Allen White, Sara Amani, Trini Sofia Balart, Amanda Kate Lacy, Gene Sung-Ho Kim, Gibin Raju, Karan Watson P.E., and Kristi J. Shryock.
  "Impact of Generative AI Technologies on Blind and Visually Impaired Students: A Case Study".
  \emph{2025 Collaborative Network for Engineering \& Computing Diversity (CoNECD), San Antonio, Texas, 2025, February}.
  ASEE Conferences, 2025.
  https://peer.asee.org/54098 Internet.  24 Mar, 2025

@INPROCEEDINGS{asee_peer_54098
author = "Lance Leon Allen White, Sara Amani, Trini Sofia Balart, Amanda Kate Lacy, Gene Sung-Ho Kim, Gibin Raju, Karan Watson P.E., and Kristi J. Shryock"
title = "Impact of Generative AI Technologies on Blind and Visually Impaired Students: A Case Study"
booktitle = "2025 Collaborative Network for Engineering \& Computing Diversity (CoNECD)"
year = "2025"
month = "February"
address = "San Antonio, Texas"
publisher = "ASEE Conferences"
note = {https://peer.asee.org/54098}
}

TY  - CPAPER
AB  - The advent of Generative AI (GenAI) in our society has taken root so deeply that even a simple Google search will provide a user with a GenAI response that attempts to summarize and simplify the search process of a user. Incidentally, these GenAI systems like ChatGPT from OpenAI, Gemini from Google, and Copilot from Microsoft are all text-based large language models which provide an increased level of access to people who use screen reading technology to interact with personal computing systems. While examining qualitative responses from a survey developed by this research team focused on understanding the impact ChatGPT and GenAI might have on the future their disciplines a single response intrigued the team: “I got ChatGPT to explain things in words using steps because I didn't understand some of the prof's explanations. I'm blind and human teachers tend to gesture and use meaningless phrases like "this thing" or "over there." ChatGPT can't point.“ The authors of this paper attempt to explore this topic through the examination of the experiences of one of the co-authors in an exploratory case study. This author is congenitally blind and has used GenAI systems in both school and non-academic life. In both contexts, blind learners often have many more questions than their sighted counterparts. These questions often go unanswered, since  the sighted people around them have limited time, patience, or expertise to answer them. GenAI systems never become bored or impatient, and they answer questions in a very detailed, step-by-step written format. Long answers to technical questions that are strictly verbal (for example, a professor’s 30-minute description of a software design diagram) can overload a learner’s working memory. For this reason, detailed answers need to be accessible as text so that the learner can review them. This might take hours for a human to do accurately, but can be completed by a GenAI system in seconds. This work will analyze the potential for GenAI systems to be applied in systems that would greatly benefit the blind and visually impaired population when interacting in our increasingly digital world. It also highlights the lived experience of the blind co-author with the intention of explicitly identifying the shortfalls and necessary improvements for this kind of technology to be implemented into the daily lives of individuals with visual impairment accommodations. Day-to-day interactions will be discussed as well as distinctly engineering and computer science related applications for this technology in this population. Additionally, various disciplines will be considered for either their potential adaptability with only GenAI as a solution and what other accommodations might be necessary to integrate GenAI into the discipline to ensure accessibility of those disciplines to individuals with blindness or other visual impairments.
AU  - Lance Leon Allen White
AU  - Sara Amani
AU  - Trini Sofia Balart
AU  - Amanda Kate Lacy
AU  - Gene Sung-Ho Kim
AU  - Gibin Raju
AU  - Karan Watson P.E.
AU  - Kristi J. Shryock
CY  - San Antonio, Texas
DA  - 2025/02/09
PB  - ASEE Conferences
TI  - Impact of Generative AI Technologies on Blind and Visually Impaired Students: A Case Study
UR  - https://peer.asee.org/54098
ER  -