An Autoethnographic Case Study of Generative Artificial Intelligence's Utility for Accessibility
arXiv:2308.09924 · doi:10.1145/3597638.3614548
Abstract
With the recent rapid rise in Generative Artificial Intelligence (GAI) tools, it is imperative that we understand their impact on people with disabilities, both positive and negative. However, although we know that AI in general poses both risks and opportunities for people with disabilities, little is known specifically about GAI in particular. To address this, we conducted a three-month autoethnography of our use of GAI to meet personal and professional needs as a team of researchers with and without disabilities. Our findings demonstrate a wide variety of potential accessibility-related uses for GAI while also highlighting concerns around verifiability, training data, ableism, and false promises.
References in corpus (6)
- A Comprehensive Survey of AI-Generated Content (AIGC): A History of Generative AI from GAN to ChatGPT
- The Impact of AI on Developer Productivity: Evidence from GitHub Copilot
- ChatGPT is not all you need. A State of the Art Review of large Generative AI models
- A Complete Survey on Generative AI (AIGC): Is ChatGPT from GPT-4 to GPT-5 All You Need?
- Exploring outlooks towards generative AI-based assistive technologies for people with Autism
- Areas of Strategic Visibility: Disability Bias in Biometrics