From Provenance to Aberrations: Image Creator and Screen Reader User Perspectives on Alt Text for AI-Generated Images

要旨

AI-generated images are proliferating as a new visual medium. However, state-of-the-art image generation models do not output alternative (alt) text with their images, rendering them largely inaccessible to screen reader users (SRUs). Moreover, less is known about what information would be most desirable to SRUs in this new medium. To address this, we invited AI image creators and SRUs to evaluate alt text prepared from various sources and write their own alt text for AI images. Our mixed-methods analysis makes three contributions. First, we highlight creators’ perspectives on alt text, as creators are well-positioned to write descriptions of their images. Second, we illustrate SRUs’ alt text needs particular to the emerging medium of AI images. Finally, we discuss the promises and pitfalls of utilizing text prompts written as input for AI models in alt text generation, and areas where broader digital accessibility guidelines could expand to account for AI images.

著者
Maitraye Das
Northeastern University, Boston, Massachusetts, United States
Alexander J.. Fiannaca
Google, Seattle, Washington, United States
Meredith Ringel. Morris
Google DeepMind, Seattle, Washington, United States
Shaun K.. Kane
Google Research, Boulder, Colorado, United States
Cynthia L. Bennett
Google, New York, New York, United States
論文URL

https://doi.org/10.1145/3613904.3642325

動画

会議: CHI 2024

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2024.acm.org/)

セッション: Supporting Accessibility of Text, Image and Video B

313B
5 件の発表
2024-05-14 23:00:00
2024-05-15 00:20:00