Toward supporting quality alt text in computing publications
Open accessAbstract
While researchers have examined alternative (alt) text for social media and news contexts, few have studied the status and challenges for authoring alt text of figures in computing-related publications. These figures are distinct, often conveying dense visual information, and may necessitate unique accessibility solutions. Accordingly, we explored how to support authors in creating alt text in computing publications---specifically in the field of human-computer interaction (HCI). We conducted two studies: (1) an analysis of 300 recently published figures at a general HCI conference (ACM CHI), and (2) interviews with 10 researchers in HCI and related fields who have varying levels of experience writing alt text. Our findings characterize the prevalence, quality, and patterns of recent figure alt text and captions. We further identify challenges authors encounter, describing their workflow barriers and confusions around how to compose alt text for complex figures. We conclude by outlining a research agenda on process, education, and tooling opportunities to improve alt text in computing-related publications.
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DSO professionals, often tasked with meeting regulatory compliance and accessibility needs, struggle to write alt text for figures in scientific publications outside their academic background.
“However, DSO professionals, often tasked with meeting regulatory compliance and accessibility needs, struggle to write alt text for figures in scientific publications outside their academic background [54, 79].”
From How University Disability Services Professionals Write Image Descriptions for HCI Figures Using Generative AI (2026) · cites this paper as [79]
The Abstract and §5.1 describe challenges that researchers and publication authors face when writing alt text for complex figures. But §3.2 identifies the interviewees as people who had helped create figures for computing research publications; the paper does not establish that DSO professionals struggle with figures outside their academic background or describe their regulatory-compliance responsibilities. (LLM, conf=0.84)
Experimental — accuracy not yet measuredDetailed alternative (alt) text or image descriptions are essential for understanding visual content for people with specific accessibility needs, such as those who are blind, have low vision, or have learning disabilities and use screen readers.
“Detailed alternative (alt) text or image descriptions 1 are essential for understanding visual content for people with specific accessibility needs, for instance, for those who are blind, have low vision, or have learning disabilities and use screen readers [37, 69, 79].”
From How University Disability Services Professionals Write Image Descriptions for HCI Figures Using Generative AI (2026) · cites this paper as [79]
The Introduction says figures convey information and need alt text, while §4.2.4 discusses descriptions that blind readers can understand and screen-reader navigation. This supports the claim for blind readers, but the paper does not establish it for people with learning disabilities; its focus is also computing-publication figures rather than visual content generally. (LLM, conf=0.84)
Experimental — accuracy not yet measuredWithout adequate support from content experts, the alt text DSO professionals produce can be overly generic or misrepresentative of the source material, which can significantly impact people's understanding of figures.
“Without adequate support from content experts, the alt text they produce can be overly generic or misrepresentative of the source material [43, 79], which, as a result, can significantly impact people's understanding of figures.”
From How University Disability Services Professionals Write Image Descriptions for HCI Figures Using Generative AI (2026) · cites this paper as [79]
Section 4.1.2 (page unavailable) reports incomplete alt text and discrepancies between alt text and figures, including incorrect labels. The paper studies publication authors, however, and does not establish that DSO professionals produce such text because they lack support from content experts. The sentence presents the effect on readers’ understanding as a consequence rather than as a finding directly attributed to this citation. (LLM, conf=0.85)
Experimental — accuracy not yet measuredThis concern is often attributed to authors' challenges in writing effective alt text for science figures.
“This concern is often attributed to authors' challenges in writing effective alt text for science figures [71, 79].”
From How University Disability Services Professionals Write Image Descriptions for HCI Figures Using Generative AI (2026) · cites this paper as [79]
The Discussion reports that authors struggled with workflows and with composing alt text for complex figures, supporting the explanation based on author challenges. But the study focuses on HCI and related computing publications; it does not establish that this concern is often attributed to those challenges across science figures generally. (LLM, conf=0.79)
Experimental — accuracy not yet measuredWriting alt text becomes a nontrivial task without domain expertise, even for experienced accessibility professionals.
“Therefore, writing alt text becomes a nontrivial task without domain expertise, even for experienced accessibility professionals [25, 33, 79].”
From How University Disability Services Professionals Write Image Descriptions for HCI Figures Using Generative AI (2026) · cites this paper as [79]
Section 5 (Discussion; page unavailable) says authors struggled to write alt text even after years of experience, including when describing domain-specific visual concepts. But the paper studies authors of computing publications; it does not establish that experienced accessibility professionals without domain expertise faced those difficulties. Section 4.2.2 identifies one participant as an accessibility expert without making that connection. (LLM, conf=0.85)
Experimental — accuracy not yet measured
Prior work emphasizes the importance of evaluating alt text by establishing baseline metrics, for instance, by semantic content scoring and user/human comprehension analysis.
“Altogether, prior work [40, 69, 79] emphasizes the importance of evaluating alt text by establishing baseline metrics, for instance, by semantic content scoring and user/human comprehension analysis.”
From How University Disability Services Professionals Write Image Descriptions for HCI Figures Using Generative AI (2026) · cites this paper as [79]
Section 3.1 (page unavailable) describes a rubric for scoring how well alt text conveys figure content, supporting evaluation through content-based quality scores. Section 2.1 discusses a semantic-content model from prior work. The paper does not report evaluating alt text through reader comprehension analysis, so that example is not supported by this source. (LLM, conf=0.84)
Experimental — accuracy not yet measuredThe complexity of science figures makes it challenging to write effective alt text, and it remains a significant problem.
“The complexity of science figures also makes it challenging to write effective alt text; therefore, it remains a significant problem [54, 65, 79, 79].”
From How University Disability Services Professionals Write Image Descriptions for HCI Figures Using Generative AI (2026) · cites this paper as [79]
Several existing studies emphasize the importance of assessing alt text, particularly for academic and technical content.
“Several existing studies emphasize the importance of assessing alt text, particularly for academic and technical content [14, 47, 79].”
From How University Disability Services Professionals Write Image Descriptions for HCI Figures Using Generative AI (2026) · cites this paper as [79]
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“Therefore, writing alt text becomes a nontrivial task without domain expertise, even for experienced accessibility professionals [32, 73, 24].”
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- Authors
- Williams, C., de Greef, L., Harris, E., Findlater, L., Pavel, A., & Bennett, C.
- Affiliations
- Carnegie Mellon University (US)
- Apple Inc.
- Apple (United States) (US)
- Venue
- Proceedings of the 19th International Web for All Conference
- Publisher
- ACM
- Published
- 2022-04-25
- Pages
- 1-12
- OpenAlex
- W4224985432
- Cited by
- 26
- References
- 11
- Citations by year
- 2026: 5 · 2025: 9 · 2024: 8 · 2023: 3 · 2022: 1
- FWCI
- 7.65
- Type
- conference paper
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- International Web for All Conference (W4A) (publishedVersion)
- Topics
- Social Sciences › Human Factors and Ergonomics › Digital Accessibility for Disabilities
- Social Sciences › Arts and Humanities › History and Philosophy of Science › Academic Writing and Publishing
- Physical Sciences › Computer Science › Human-Computer Interaction › Usability and User Interface Design
- Keywords
- alt text, figure captions, accessibility, human-computer interaction, writing support, visual information, accessibility education
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