Work

Exploring Generative AI to Support Disability Service Professionals in Writing Image Descriptions for HCI Science Figures

Year: 2025

Type: conference-paper

Abstract: Alternative text (alt text) or image descriptions for scientific figures make them accessible to screen reader users.Yet, generating high-quality alt text remains a significant challenge, particularly for people lacking subject-matter expertise.Emerging AI tools, such as generative AI, can help people understand contexts where they lack subject expertise.This work explores how university Disability Services Office (DSO) professionals write alt text for scientific figures without subject expertise.We conducted a user study with 12 DSO professionals who authored alt text for scientific figures, first without and then using generative AI.We assessed the participants' processes for alt text generation and their confidence in the resulting output.We also conducted semi-structured interviews to understand DSO professionals' experiences with the alt text generation.Our findings reveal that AI assistance improved participants' confidence and efficiency, but introduced new challenges for interaction and trust.Participants expressed caution about relying on AI-generated descriptions without sufficient domain knowledge and editing.These insights highlight the need for AI-augmented tools that better scaffold the alt text writing process for accessibility professionals.

Source: International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS)

DOI: 10.1145/3663547.3759763

Authors: Yugo Iwamoto, Muhammad Raees, Jamison Heard, Garreth W. Tigwell

Institution: Rochester Institute of Technology

Language: English

Topic: Digital Accessibility for Disabilities

Subfield: Human Factors and Ergonomics

Field: Social Sciences

Domain: Social Sciences

SDG: Reduced inequalities

Open Access status: bronze

Funder: National Science Foundation