FigurA11y: AI Assistance for Writing Scientific Alt Text

Explainable AI (XAI)Visual Impairment Technologies (Screen Readers, Tactile Graphics, Braille)Software Engineers & DevelopersUI/UX DesignersHCI Researchers

High-quality alt text is crucial for making scientific figures accessible to blind and low-vision readers. Crafting complete, accurate alt text is challenging even for domain experts, as published figures often depict complex visual information and readers have varied informational needs. These challenges, along with high diversity in figure types and domain-specific details, also limit the usefulness of fully automated approaches. Consequently, the prevalence of high-quality alt text is very low in scientific papers today. We investigate whether and how human-AI collaborative editing systems can help address the difficulty of writing high-quality alt text for complex scientific figures. We present FigurA11y, an interactive system that generates draft alt text and provides suggestions for author revisions using a pipeline driven by extracted figure and paper metadata. We test two versions, motivated by prior work on visual accessibility and writing support. The base Draft+Revise version provides authors with an automatically generated draft description to revise, along with extracted figure metadata and figure-specific alt text guidelines to support the revision process. The full Interactive Assistance version further adds contextualized suggestions: text snippets to iteratively produce descriptions, and hypothetical user questions with possible answers to reveal potential ambiguities and resolutions. In a study of authors (N=14), we found the system assisted them in efficiently producing descriptive alt text. Generated drafts and interface elements enabled authors to quickly initiate and edit detailed descriptions. Additionally, interactive suggestions from the full system prompted more iteration and highlighted aspects for authors to consider, resulting in greater deviation from the drafts without increased average cognitive load or manual effort.

Quick Actions

Share

Share this page

ios_share

https://hci.top/en/papers/iui/139211/2024

AdRecommended

Learn AI Coding at CodeNow

At a Glance

Paper Snapshot

fact_check
dataset
Source
IUI
calendar_month
Year
2024
emoji_events
Award
No award tagged
group
Authors
3 authors
sell
Subtopics
Explainable AI (XAI), Visual Impairment Technologies (Screen Readers, Tactile Graphics, Braille)
work
Professions
Software Engineers & Developers, UI/UX Designers, HCI Researchers
article
Content Status
Abstract only
hub
Related Papers
4 related papers