Building the Habit of Authoring Alt Text: Design for Making a Change
Open accessAbstract
Alternative (alt) text is essential for the accessibility of images to screen reader users. Alt text can be authored by end users or generated automatically using machine learning. Automated methods, while fast and cheap, do not result in high quality alt text. Meanwhile, the large number of images with no alt text on social media indicates that many users do not author alt text for the images they upload. Little is known about whether design elements that motivate and support users are integrated into alt text user interfaces (UIs). We reviewed the current state of alt text UIs in literature, and characterized their design according to behavior change and accountability design factors. We found that the majority of reviewed UIs contained general prompts with no specific motivator or guidance. Many of the UIs did not incorporate design elements to encourage accountability or behavior change. We recommend that future alt text authoring tools incorporate design elements which decrease the user’s cognitive effort, employ motivational and well-timed triggers, and leverage user accountability through alt text visibility and its association with the user’s social presence.
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Most research in this space has focused on content creators or domain experts who author their figures.
“Most research in this space has focused on content creators or domain experts who author their figures [4, 26, 48, 71].”
From How University Disability Services Professionals Write Image Descriptions for HCI Figures Using Generative AI (2026) · cites this paper as [4]
Section 4.1 describes one reviewed paper involving an expert annotator and three UIs in which users authored alt text for personal photos. Sections 3.2 and 5 discuss a review of alt-text tools, but do not establish that most research focuses on content creators or domain experts authoring their own figures. Our copy does not address that claimed predominance. (LLM, conf=0.72)
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Cites
A behavior model for persuasive design
Fogg, B. (2009) · Proceedings of the 4th International Conference on Persuasive Technology · doi:10.1145/1541948.1541999 · Cited by 2,328 · see citing works
Labeling images with a computer game
von Ahn, L., & Dabbish, L. (2004) · ACM SIGCHI Conference on Human Factors in Computing Systems (CHI) · doi:10.1145/985692.985733 · Cited by 2,230 · see citing works
Why we tag: motivations for annotation in mobile and online media
Ames, M., & Naaman, M. (2007) · Proceedings of the SIGCHI Conference on Human Factors in Computing Systems · doi:10.1145/1240624.1240772 · Cited by 833 · see citing works
Crano, W. D., & Prišlin, R. (2005) · Annual Review of Psychology · doi:10.1146/annurev.psych.57.102904.190034 · Cited by 787 · see citing works
Creating persuasive technologies
Fogg, B. J. (2009) · doi:10.1145/1541948.1542005 · Cited by 328 · see citing works
Using Accountability to Reduce Access Policy Violations in Information Systems
Vance, A., Lowry, P. B., & Eggett, D. L. (2013) · Journal of Management Information Systems · doi:10.2753/mis0742-1222290410 · Cited by 248 · see citing works
Rich Representations of Visual Content for Screen Reader Users
Morris, M. R., Johnson, J., Bennett, C. L., & Cutrell, E. (2018) · Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3173574.3173633 · Cited by 159 · see citing works
Behavior Wizard: A Method for Matching Target Behaviors with Solutions
Fogg, B. J., & Hreha, J. (2010) · Lecture notes in computer science · doi:10.1007/978-3-642-13226-1_13 · Cited by 158 · see citing works
Morris, M., Zolyomi, A., Yao, C., Bahram, S., Bigham, J., & Kane, S. K. (2016) · International Conference on Human Factors in Computing Systems · doi:10.1145/2858036.2858116 · Cited by 157 · see citing works
Investigating the appropriateness of social network question asking as a resource for blind users
Brady, E. L., Zhong, Y., Morris, M. R., & Bigham, J. P. (2013) · ACM Conference on Computer Supported Cooperative Work (CSCW) · doi:10.1145/2441776.2441915 · Cited by 147 · see citing works
Twitter A11y: A Browser Extension to Make Twitter Images Accessible
Gleason, C., Pavel, A., McCamey, E., Low, C., Carrington, P., Kitani, K., & Bigham, J. P. (2020) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3313831.3376728 · Cited by 123 · see citing works
Gleason, C., Carrington, P., Cassidy, C., Morris, M., Kitani, K. M., & Bigham, J. (2019) · The Web Conference · doi:10.1145/3308558.3313605 · Cited by 108 · see citing works
Eriksén, S. (2002) · Nordic Conference on Human-Computer Interaction · doi:10.1145/572020.572041 · Cited by 91 · see citing works
Fogg, B. J. (2009) · doi:10.1145/1541948.1542001 · Cited by 88 · see citing works
Photo annotation on a camera phone
Wilhelm, A., Takhteyev, Y., Sarvas, R., House, N. V., & Davis, M. (2004) · CHI Conference Extended Abstracts on Human Factors in Computing Systems (CHI EA) · doi:10.1145/985921.986075 · Cited by 87 · see citing works
Zhong, Y., Lasecki, W. S., Brady, E. L., & Bigham, J. P. (2015) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/2702123.2702437 · Cited by 68 · see citing works
Karido: A GWAP for telling artworks apart
Steinmayr, B., Wieser, C., Kneißl, F., & Bry, F. (2011) · doi:10.1109/cgames.2011.6000338 · Cited by 24 · see citing works
Designing for Behavior Change—New Models and Moral Issues
Fogg, B. J., & Euchner, J. (2019) · Research-Technology Management · doi:10.1080/08956308.2019.1638490 · Cited by 23 · see citing works
How annotation styles influence content and preferences
Cheng, J., & Cosley, D. (2013) · Proceedings of the 24th ACM Conference on Hypertext and Social Media · doi:10.1145/2481492.2481519 · Cited by 14 · see citing works
Object-based tag propagation for semi-automatic annotation of images
Ivanov, I., Vajda, P., Lutz Goldmann, A., Lee, J., & Ebrahimi, T. (2010) · Multimedia Information Retrieval · doi:10.1145/1743384.1743471 · Cited by 12 · see citing works
Mangiatordi, A., & Lazzari, M. (2018) · IEEE Consumer Communications and Networking Conference · doi:10.1109/ccnc.2018.8319312 · Cited by 8 · see citing works
iCap: Interactive Image Captioning with Predictive Text
Jia, Z., & Li, X. (2020) · International Conference on Multimedia Retrieval · doi:10.1145/3372278.3390697 · Cited by 8 · see citing works
Tang, L. Y. W., & Carter, J. A. (2011) · PsycEXTRA Dataset · doi:10.1037/e578902012-102 · Cited by 1 · see citing works
Flagged first, then by citations
Research works printed but not linked: 9
- Apostolos Antonacopoulos, Dimosthenis Karatzas, and Jordi Ortiz-Lopez. 2000. Accessing textual information embedded in internet images. In Internet Imaging II, Vol. 4311. SPIE, 198-205.
- Aditya Bodi, Pooyan Fazli, Shasta Ihorn, Yue-Ting Siu, Andrew T Scott, Lothar Narins, Yash Kant, Abhishek Das, and Ilmi Yoon. 2021. Automated Video De- scription for Blind and Low Vision Users. In Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems. 1-7.
- Carlos Duarte, Letícia Seixas Pereira, André Santos, João Vicente, André Ro- drigues, João Guerreiro, José Coelho, and Tiago Guerreiro. 2021. Nipping Inac- cessibility in the Bud: Opportunities and Challenges of Accessible Media Content Authoring. In 13th ACM Web Science Conference 2021. 3-9.
- Cole Gleason, Patrick Carrington, Cameron Cassidy, Meredith Ringel Morris, Kris M Kitani, and Jefrey P Bigham. 2019. "It's almost like they're trying to hide it": How User-Provided Image Descriptions Have Failed to Make Twitter Accessible. In The World Wide Web Conference. 549-559.
- Barbara Kitchenham. 2004. Procedures for performing systematic reviews. Keele, UK, Keele University 33, 2004 (2004), 1-26.
- Kelly Mack, Edward Cutrell, Bongshin Lee, and Meredith Ringel Morris. 2021. Designing Tools for High-Quality Alt Text Authoring. In The 23rd International ACM SIGACCESS Conference on Computers and Accessibility. 1-14.
- Letícia Seixas Pereira, João Guerreiro, André Rodrigues, André Santos, João Vicente, José Coelho, Tiago Guerreiro, and Carlos Duarte. 2021. Suggesting text alternatives for images in social media. ACM SIGACCESS Accessibility and Computing 130 (2021), 1-6.
- Abebe Rorissa. 2008. User-generated descriptions of individual images versus labels of groups of images: A comparison using basic level theory. Information processing & management 44, 5 (2008), 1741-1753.
- Paul Benjamin; Vance, Anthony Osborn; Lowry and Dennis Eggett. 2015. Increas- ing Accountability Through User-Interface Design Artifacts: A New Approach to Addressing the Problem of Access-Policy Violations. MIS Quarterly (2015).
Cited by
Sorted by citations
Engaging with Children's Artwork in Mixed Visual-Ability Families
Chheda-Kothary, A., Wobbrock, J. O., & Froehlich, J. E. (2024) · International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS) · doi:10.1145/3663548.3675613 · Cited by 18 · see citing works
Machine Learning for Adaptive Accessible User Interfaces: Overview and Applications
Kristić, M., Zakarija, I., Škopljanac-Mačina, F., & Car, Ž. (2025) · Applied Sciences · doi:10.3390/app152312538 · Cited by 9 · see citing works
Song, H., Shin, M., Kim, Y., Jang, K., Choi, J., Jung, H., & Suh, B. (2025) · ACM International Conference on Intelligent User Interfaces (IUI) · doi:10.1145/3708557.3716366 · Cited by 7 · see citing works
Pereira, L. S., Guerreiro, J., Rodrigues, A., Guerreiro, T., & Duarte, C. (2024) · ACM Transactions on Accessible Computing · doi:10.1145/3647643 · Cited by 4 · see citing works
Raees, M., Iwamoto, Y., Papangelis, K., Heard, J., & Tigwell, G. W. (2026) · arXiv · doi:10.48550/arxiv.2602.08937 · Cited by 1 · see citing works
“Unlike authors of scientific publications or figure creators, DSO professionals are often required to interpret and describe figures from disciplines in which they have little to no expertise, ranging from complex statistical plots to biomedical diagrams, to name a few.”
Iwamoto, Y., Raees, M., Heard, J., & Tigwell, G. W. (2025) · Proceedings of the 27th International ACM SIGACCESS Conference on Computers and Accessibility · doi:10.1145/3663547.3759763 · Cited by 1 · see citing works
CoSight: Exploring Viewer Contributions to Online Video Accessibility Through Descriptive Commenting
Wang, R., Liu, X., Wang, B., Zhang, W., Liao, Z., Li, Z., Pavel, A., & Chen, X. (2025) · ACM Symposium on User Interface Software and Technology (UIST) · doi:10.1145/3746059.3747747 · Cited by 1 · see citing works
Paoletta, A. M., Refrigeri, L., & Baralla, F. (2025) · Communications in computer and information science · doi:10.1007/978-3-032-03021-4_16
Song, H., Shin, M., Choi, J., Kim, Y., Jang, K., Suh, B., & Jung, H. (2026) · Proceedings of the 2026 28th International ACM SIGACCESS Conference on Computers and Accessibility · doi:10.1145/3797867.3828985
- Authors
- Bellscheidt, S., Metcalf, H., Pham, D., & Elglaly, Y. N.
- Affiliations
- Western Washington University (US)
- Venue
- The 25th International ACM SIGACCESS Conference on Computers and Accessibility
- Publisher
- ACM
- Published
- 2023-10-22
- Pages
- 1-5
- OpenAlex
- W4387793240
- Cited by
- 8
- References
- 23
- Citations by year
- 2026: 1 · 2025: 5 · 2024: 2
- FWCI
- 3.35
- Type
- conference paper
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS) (publishedVersion)
- Topics
- Social Sciences › Human Factors and Ergonomics › Digital Accessibility for Disabilities
- Physical Sciences › Computer Science › Human-Computer Interaction › Usability and User Interface Design
- Physical Sciences › Computer Science › Human-Computer Interaction › Innovative Human-Technology Interaction
- Keywords
- alt text, image accessibility, screen readers, user motivation, social media images, cognitive effort, user interface design
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