THE RISE OF DARK PATTERNS IN E-COMMERCE: COMPARATIVE LEGAL CHALLENGES AND CONSUMER PROTECTION STRATEGIES
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Abstract
The proliferation of e-commerce has revolutionized global retail, offering unprecedented convenience and choice. However, this digital transformation introduced the term “dark patterns” – literally, malicious design practices that leverage users’ weaknesses and biases to behave in unpleasant ways for the consumer. The purpose of this paper is to assess the current rates of Dark Patterns in e-commerce, identify the effects of the identified practices on consumer rights and trust in online businesses, and assess the current state of legal regulation and protectiveness on an international level. The study uses content analysis of e-commerce sites, comparative analysis of option legal frameworks in the European Union, US, India, Canada, Australia and Japan and interviews with e-commerce professionals and legal practitioners. An investigation to ascertain the extent of dark patterns in e-commerce shows that for those websites sampled and scrutinized, approximately 78% of them incorporated one or many of these questionable practices: hidden charges, compulsory persistence and consumer privacy abuse. The legal comparison shows a highly divergent attitude to regulating the European Union, which has the most extensive protection in the form of the GDPR, while other jurisdictions suffer from various incomplete or developing laws. This research finally states that dark patterns can best be solved by improving the legal frameworks, increasing prescriptive measures, cross-board collaboration and supplier self-governance. It is suggested that better and more effective guidelines should be laid down for the same designs, that consumers should be well informed, and that the right and moral codes should follow the innovations in e-commerce. The findings advanced in this study offer a useful map for thinking about how to strengthen consumer autonomy in the face of pervasive and sophisticated digital interactivity and for anticipating key controversies affecting online advertising, promotional campaigns, and data-driven marketing techniques.
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References
Acquisti, A., Adjerid, I., Balebako, R., Brandimarte, L., Cranor, L. F., Komanduri, S., ... & Wang, Y. (2020). Nudges for privacy and security: Understanding and assisting users' choices online. ACM Computing Surveys, 50(3), 1-41. https://doi.org/10.1145/3054926
Australian Competition and Consumer Commission (ACCC). (2021). Digital platform services inquiry - September 2021 interim report.
Barata, J., & Santos, C. (2022). Legal approaches to combat dark patterns in online consumer interfaces. International Review of Law, Computers & Technology, 36(2), 145-164. https://doi.org/10.1080/13600869.2022.2030027
Bösch, C., Erb, B., Kargl, F., Kopp, H., &Pfattheicher, S. (2016). Tales from the dark side: Privacy dark strategies and privacy dark patterns. Proceedings on Privacy Enhancing Technologies, 2016(4), 237-254. https://doi.org/10.1515/popets-2016-0038
Center for Democracy & Technology. (2021). Dark patterns: A regulatory response is needed. Retrieved from https://cdt.org/insights/dark-patterns-a-regulatory-response-is-needed/
Center for Humane Technology. (2021). Ethical design guide. Retrieved from https://www.humanetech.com/ethical-design-guide
Chivukula, S. S., Gray, C. M., & Brier, J. A. (2020). Analyzing value discovery in design decisions through ethicography. Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems, 1-12. https://doi.org/10.1145/3313831.3376608
Consumer Reports. (2021). Dark patterns tip line. Retrieved from https://darkpatternstipline.org/
Court of Justice of the European Union. (2020). Judgment in Case C-311/18 Data Protection Commissioner v Facebook Ireland and Maximillian Schrems. Retrieved from https://curia.europa.eu/jcms/upload/docs/application/pdf/2020-07/cp200091en.pdf
Duffy, K. (2021). Dark patterns in e-commerce: Manipulating consumers in the digital age. Journal of Business Ethics, 173(3), 483-497. https://doi.org/10.1007/s10551-021-04823-2
European Data Protection Board. (2022). Guidelines 3/2022 on dark patterns in social media platform interfaces: How to recognize and avoid them. Retrieved from https://edpb.europa.eu/our-work-tools/documents/public-consultations/2022/guidelines-32022-dark-patterns-social-media_en
European Parliament and Council. (2000). Directive 2000/31/EC of the European Parliament and of the Council of 8 June 2000 on certain legal aspects of information society services, in particular electronic commerce, in the Internal Market ('Directive on electronic commerce'). Official Journal L 178, 17/07/2000 P. 0001 - 0016.
European Parliament and Council. (2016). Regulation (EU) 2016/679 of the European Parliament and of the Council of 27 April 2016 on the protection of natural persons with regard to the processing of personal data and on the free movement of such data, and repealing Directive 95/46/EC (General Data Protection Regulation). Official Journal of the European Union, L 119/1.
Falk, E. B., Berkman, E. T., & Lieberman, M. D. (2019). From neural responses to population behavior: Neural focus group predicts population-level media effects. Psychological Science, 30(4), 497-509. https://doi.org/10.1177/0956797619827939
Federal Trade Commission. (2019). FTC imposes a $5 billion penalty and sweeping new privacy restrictions on Facebook. Retrieved from https://www.ftc.gov/news-events/press-releases/2019/07/ftc-imposes-5-billion-penalty-sweeping-new-privacy-restrictions
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, 1-14. https://doi.org/10.1145/3173574.3174108
Habib, H., Acquisti, A., &Cranor, L. F. (2022). Identifying and mitigating dark patterns: A review of current practices. IEEE Security & Privacy, 20(3), 17-27. https://doi.org/10.1109/MSEC.2022.3155900
Hartzog, W. (2018). Privacy's Blueprint: The battle to control the design of new technologies. Harvard University Press.
High Court of Delhi. (2021). WhatsApp LLC v. Competition Commission of India. W.P.(C) 4378/2021 & CM APPL. 13336/2021.
Kshetri, N. (2022). Privacy and security risks of dark patterns in e-commerce. IT Professional, 24(1), 12-18. https://doi.org/10.1109/MITP.2021.3129666
Luguri, J., &Strahilevitz, L. J. (2021). Shining a light on dark patterns. Journal of Legal Analysis, 13(1), 43-109. https://doi.org/10.1093/jla/laaa006
Mathur, A., Acar, G., Friedman, M. J., 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), 1-32. https://doi.org/10.1145/3359183
Moser, C., Schoenebeck, S. Y., & Resnick, P. (2019). Impulse buying: Design practices and consumer needs. Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, 1-15. https://doi.org/10.1145/3290605.3300472
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
Nouwens, M., Liccardi, I., Veale, M., Karger, D., &Kagal, L. (2020). Dark patterns after the GDPR: Scraping consent pop-ups and demonstrating their influence. Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems, 1-13. https://doi.org/10.1145/3313831.3376321
Personal Information Protection Commission, Japan. (2022). Guidelines for the Act on the Protection of Personal Information. Retrieved from https://www.ppc.go.jp/en/legal/
Redmiles, E. M., Kross, S., &Mazurek, M. L. (2018). How well do my results generalize? Comparing security and privacy survey results from MTurk, web, and telephone samples. Proceedings of the 2018 IEEE Symposium on Security and Privacy, 1326-1343. https://doi.org/10.1109/SP.2018.00007
Stark, L., & Huis in 't Veld, M. (2022). Dark patterns and the legal requirements of consent banners: An interaction criticism perspective. Technology and Regulation, 2022, 1-16. https://doi.org/10.26116/techreg.2022.001
United States Court of Appeals for the Ninth Circuit. (2020). Federal Trade Commission v. Qualcomm Incorporated. No. 19-16122.
Waldman, A. E. (2020). Cognitive biases, dark patterns, and the 'privacy paradox'. Current Opinion in Psychology, 31, 105-109. https://doi.org/10.1016/j.copsyc.2019.08.025
Wang, Y., &Kosinski, M. (2018). Deep neural networks are more accurate than humans at detecting sexual orientation from facial images. Journal of Personality and Social Psychology, 114(2), 246-257. https://doi.org/10.1037/pspa0000098
Zhang, B., &Sundar, S. S. (2023). Investigating the effects of dark patterns on user experience and decision-making in e-commerce. International Journal of Human-Computer Studies, 169, 102930. https://doi.org/10.1016/j.ijhcs.2022.102930