Institute of Sociology NASU

Ethical imperatives of digital design in journalism and advertising: a media-critical approach to visual literacy

stmm. 2026 (3): 146-157

DOI https://doi.org/10.15407/sociology2026.03.146

Full text:

ANNA DERKACH, Senior Lecturer at the Department of Marketing and Advertising, Vinnytsia Institute of Trade and Economics, State University of Trade and Economics (87, Soborna St., Vinnytsia, 21000)

a.derkach@vtei.edu.ua

https://orcid.org/0009-0004-0482-387X

ALONA TANASIICHUK, Doctor of Sciences in Economics, Professor at the Department of Marketing and Advertising, Vinnytsia Institute of Trade and Economics, State University of Trade and Economics (87, Soborna St., Vinnytsia, 21000)

tanass2005@ukr.net

https://orcid.org/0000-0002-7967-0239

SCOPUS ID: 57217823466

IVAN PEDORUK, Meritorious Journalist of Ukraine, Associate Professor at the Department of Marketing and Advertising, Vinnytsia Institute of Trade and Economics, State University of Trade and Economics (87, Soborna St., Vinnytsia, 21000)

i.pedoruk@vtei.edu.ua

https://orcid.org/0009-0000-5325-4854

The article offers a theoretical and conceptual interpretation of the ethical imperatives of digital design in the context of the convergence of digital journalism and advertising. It is argued that digital design functions not only as a means of visual presentation but also as an element of the architecture of digital interaction that affects audience perception, interpretation of information, and behavioral decisions. The article distinguishes between a narrow understanding of design as the visual arrangement of a particular media message and a broader understanding of design as the UX organization of a digital platform. The main ethical risks of digital design are systematized, including visual mimicry, dark patterns, affective visualization, algorithmic personalization, and visual reduction of complexity. A model of ethical design imperatives is proposed, comprising the principles of semantic integrity, interpretative openness, minimization of cognitive load, and digital responsibility. To support the practical application of the model, a set of indicators for assessing the ethical quality of visual and UX solutions is presented. Visual literacy is defined as a metacognitive competence that supports audience cognitive autonomy under conditions of information overload and algorithmically personalized influence.

Keywords: visual ethics, digital design, digital journalism, media criticism, visual literacy, dark patterns, algorithmic personalization, cognitive autonomy, cognitive security

References:

1. Bösch, C., Erb, B., Kargl, F., Kopp, H., Pfattheicher, S. (2016). Tales from the dark side: Privacy dark strategies and dark patterns. Proceedings on Privacy Enhancing Technologies, 4, 237-254. https://doi.org/10.1515/popets-2016-0038

2. Bucher, T. (2017).The algorithmic imaginary: Exploring the ordinary affects of Facebook algorithms. Information, Communication & Society, 20(1), 30-44. https://doi.org/10.1080/1369118X.2016.1154086

3. Chang, W.J., Seaborn, K., Adams, A.A. (2024). Theorizing Deception: A Scoping Review of Theory in Research on Dark Patterns and Deceptive Design. Extended Abstracts of the CHI Conference on Human Factors in Computing Systems, 321, 1-7. https://doi.org/10.1145/3613905.3650997

4. Coeckelbergh, M. (2020). Artificial intelligence, responsibility attribution, and a relational justification of explainability. Science and Engineering Ethics, 26, 2051-2068. https://doi.org/10.1007/s11948-019-00146-8

5. Couldry, N., Hepp, A. (2017). The Mediated Construction of Reality. Cambridge: Polity Press.

6. European Data Protection Board. (2023). Guidelines 03/2022 on Deceptive Design Patterns in Social Media Platform Interfaces: How to Recognise and Avoid Them. Version 2.0. 2023.

7. Federal Trade Commission. (2022). Bringing Dark Patterns to Light. FTC Staff Report.

8. Graßl, P., Schraffenberger, H., Zuiderveen Borgesius, F., Buijzen, M. (2021). Dark and Bright Patterns in Cookie Consent Requests. Journal of Digital Social Research, 3(1), 1-38. https://doi.org/10.33621/jdsr.v3i1.54

9. Gray, C.M., Kou, Y., Battles, B., Hoggatt, J., Toombs, A.L. (2018). The Dark (Patterns) Side of UX Design. Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems, 534, 1-4. https://doi.org/10.1145/3173574.3174108

10. Gray, C.M., Sánchez Chamorro, L., Obi, I., Duane, J.-N. (2023). Mapping the Landscape of Dark Patterns Scholarship: A Systematic Literature Review. DIS Companion '23: Companion Publication of the 2023 ACM Designing Interactive Systems Conference, 10 July, 188-193. https://doi.org/10.1145/3563703.3596635

11. Gray, C.M., Santos, C.T., Bielova, N., Mildner, T. (2024). An Ontology of Dark Patterns Knowledge: Foundations, Definitions, and a Pathway for Shared Knowledge-Building. CHI '24: Proceedings of the CHI Conference on Human Factors in Computing Systems, 289, 1-22. https://doi.org/10.1145/3613904.3642436

12. Luguri, J., Strahilevitz, L. (2021). Shining a Light on Dark Patterns. Journal of Legal Analysis, 13(1), 43-109. https://doi.org/10.1093/jla/laaa006

13. Mathur, A., Acar, G., Friedman, M., Lucherini, E., Mayer, J., Chetty, M., Narayanan, A. (2019). Dark patterns at scale: Findings from a crawl of 11K shopping websites. Proceedings of the ACM on Human-Computer Interaction, 3(CSCW), 81, 1-32. https://doi.org/10.1145/3359183

14. Matz, S.C., Kosinski, M., Nave, G., Stillwell, D.J. (2017). Psychological targeting as an effective approach to digital mass persuasion. Proceedings of the National Academy of Sciences, 114(48), 12714-12719. https://doi.org/10.1073/pnas.1710966114

15. Mildner, T., Savino, G.-L., Doyle, P.R., Cowan, B.R., Malaka, R. (2023). About Engaging and Governing Strategies: A Thematic Analysis of Dark Patterns in Social Networking Services. Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems, 192, 1-15. https://doi.org/10.1145/3544548.3580695

16. Narayanan, A., Mathur, A., Chetty, M., Kshirsagar, M.(2020). Dark patterns: Past, present, and future. Communications of the ACM, 63(9), 42-47. https://doi.org/10.1145/3397884

17. Noble, S.U. (2018). Algorithms of Oppression: How Search Engines Reinforce Racism. New York: NYU Press. https://doi.org/10.18574/nyu/9781479833641.001.0001

18. Norman, D. (2019). The Design of Everyday Things. [In Ukrainian]. Kharkiv: Klub Simeynoho Dozvillia.

19. OECD. (2022). Dark Commercial Patterns. OECD Digital Economy Papers, 33.

20. Papanek, V. (2020). Design for the Real World. Human Ecology and Social Change. [In Ukrainian]. Kyiv: ArtHuss.

21. Pariser, E. (2011). The Filter Bubble: What the Internet is Hiding from You. London: Penguin Books. https://doi.org/10.3139/9783446431164

22. Pocheptsov, G. (2019). Information Policy. [In Ukrainian]. Kyiv: Znannia.

23. Potiatynyk, B. (2015). Media Criticism: Theory and Practice. [In Ukrainian]. Lviv: PAIS.

24. Sunstein, C.R. (2017). #Republic: Divided democracy in the age of social media. Princeton: Princeton University Press. https://doi.org/10.1515/9781400884711

25. Susser, D., Roessler, B., Nissenbaum, H. (2019). Online manipulation: Hidden influences in a digital world. Georgetown Law Technology Review, 4(1). https://doi.org/10.2139/ssrn.3306006

26. Thaler, R.H., Sunstein, C.R. (2008). Nudge: Improving Decisions about Health, Wealth, and Happiness. New Haven: Yale University Press.

27. Wu, T. (2016). The Attention Merchants: The Epic Scramble to Get Inside Our Heads. New York: Knopf.

28. Zuboff, S. (2019). Surveillance capitalism and the challenge of collective action. New Labor Forum, 28(1). https://doi.org/10.1177/1095796018819461

Received 18.04.2026

Accepted for publication after review 24.06.2026