Abstract
While Dark Patterns are widely present in graphical user interfaces, in this research we set out to find out whether they are also starting to appear in Chatbots. Dark Patterns are intentionally deceptive designs that trick users into acting contrary to their intention - and in favor of the organization that implements them. Chatbots, as a kind of conversational user interface, can potentially also suffer from Dark Patterns or other poor interaction design, sometimes referred to as Usability Smells. This keeps users from easily achieving their goals and can lead to frustration or limitations for users. To find Dark Patterns and Usability Smells, we analyzed user reports of negative experiences. Since we found no well known dataset of reports, we created the ChIPS dataset with 69 complaints from different web sources, and then classified them as one of 16 established Dark Patterns, potential new Dark Patterns, Usability Smells, or neither. Results show that, even though there are instances of established Dark Patterns, negative experiences usually are caused by chatbot defects, high expectations from users, or non-intuitive interactions.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
- 2.
https://www.deceptive.design/types, previously called darkpatterns.org.
- 3.
Chatbot Interactions for a Dark Patterns Search.
- 4.
- 5.
- 6.
- 7.
- 8.
- 9.
- 10.
An example can be found here: https://asana.com/de.
- 11.
Sometimes also called ‘Roach Motel’.
- 12.
References
Adamopoulou, E., Moussiades, L.: Chatbots: History, technology, and applications. Mach. Learn. Appl. 2, 100006 (2020). https://doi.org/10.1016/j.mlwa.2020.100006
Ashktorab, Z., Jain, M., Liao, Q.V., Weisz, J.D.: Resilient Chatbots: Repair Strategy Preferences for Conversational Breakdowns. In: Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, pp. 1–12. Association for Computing Machinery (2019). https://doi.org/10.1145/3290605.3300484
Bongard-Blanchy, K., Rossi, A., Rivas, S., Doublet, S., Koenig, V., Lenzini, G.: “I am Definitely Manipulated, Even When I am Aware of it. It’s Ridiculous!”-Dark Patterns from the End-User Perspective. In: Designing Interactive Systems Conference 2021, pp. 763–776 (2021). https://doi.org/10.1145/3461778.3462086
Brereton, P., Kitchenham, B.A., Budgen, D., Turner, M., Khalil, M.: Lessons from applying the systematic literature review process within the software engineering domain. J. Syst. Softw. 80(4), 571–583 (2007). https://doi.org/10.1016/j.jss.2006.07.009
Brignull, H.: Deceptive patterns (2023). https://www.deceptive.design/. Accessed 6 Dec 2023
Budui, R.: The User Experience of Customer-Service Chat: 20 Guidelines (2019). https://www.nngroup.com/articles/chat-ux/. Accessed 6 Dec 2023
Følstad, A., Brandtzaeg, P.B.: Users’ experiences with chatbots: findings from a questionnaire study. Qual. User Exp. 5(1), 3 (2020). https://doi.org/10.1007/s41233-020-00033-2
van der Goot, M.J., Hafkamp, L., Dankfort, Z.: Customer service chatbots: A Qualitative Interview Study into the Communication Journey of Customers. In: Følstad, A., et al. (eds.) CONVERSATIONS 2020. LNCS, vol. 12604, pp. 190–204. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-68288-0_13
Gray, C.M., Chivukula, S.S., Lee, A.: What Kind of Work Do “Asshole Designers” Create? Describing Properties of Ethical Concern on Reddit. In: Proceedings of the 2020 ACM Designing Interactive Systems Conference, pp. 61–73 (2020). https://doi.org/10.1145/3357236.3395486
Gray, C.M., Sanchez Chamorro, L., Obi, I., Duane, J.N.: Mapping the Landscape of Dark Patterns Scholarship: A Systematic Literature Review. In: Companion Publication of the 2023 ACM Designing Interactive Systems Conference, pp. 188–193 (2023). https://doi.org/10.1145/3563703.3596635
Gray, C.M., Santos, C., Bielova, N.: Towards a preliminary ontology of dark patterns knowledge. In: Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems, pp. 1–9. Association for Computing Machinery (2023). https://doi.org/10.1145/3544549.3585676
Grigera, J., Garrido, A., Rivero, J.M., Rossi, G.: Automatic detection of usability smells in web applications. Int. J. Hum Comput Stud. 97, 129–148 (2017). https://doi.org/10.1016/j.ijhcs.2016.09.009
Hernandez-Bocanegra, D.C., Ziegler, J.: Conversational review-based explanations for recommender systems: Exploring users’ query behavior. In: Proceedings of the 3rd Conference on Conversational User Interfaces, pp. 1–11 (2021). https://doi.org/10.1145/3469595.3469596
Hidaka, S., Kobuki, S., Watanabe, M., Seaborn, K.: Linguistic Dead-Ends and Alphabet Soup: Finding Dark Patterns in Japanese Apps. In: Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems, pp. 1–13. Association for Computing Machinery (2023). https://doi.org/10.1145/3544548.3580942
van Hooijdonk, C., Martijn, G., Liebrecht, C.: A Framework and Content Analysis of Social Cues in the Introductions of Customer Service Chatbots. In: Følstad, A., et al. (eds.) Chatbot Research and Design, CONVERSATIONS 2022. LNCS, vol. 13815, pp. 118–133. Springer, Cham (2023). https://doi.org/10.1007/978-3-031-25581-6_8
Kowalczyk, M., Gunawan, J.T., Choffnes, D., Dubois, D.J., Hartzog, W., Wilson, C.: Understanding Dark Patterns in Home IoT Devices. In: Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems, pp. 1–27. Association for Computing Machinery (2023). https://doi.org/10.1145/3544548.3581432
Kvale, K., Freddi, E., Hodnebrog, S., Sell, O.A., Følstad, A.: Understanding the user experience of customer service chatbots: what can we learn from customer satisfaction surveys? In: Følstad, A., et al. (eds.) CONVERSATIONS 2020. LNCS, vol. 12604, pp. 205–218. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-68288-0_14
Mathur, A., et al.: Dark patterns at scale: Findings from a Crawl of 11K Shopping Websites. Proc. ACM Hum. Comput. Interact. 3(CSCW), 1–32 (2019). https://doi.org/10.1145/3359183
Mathur, A., Kshirsagar, M., Mayer, J.: What makes a Dark Pattern... Dark? Design Attributes, Normative Considerations, and Measurement Methods. In: Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems, pp. 1–18. Association for Computing Machinery (2021). https://doi.org/10.1145/3411764.3445610
Mildner, T., Doyle, P., Savino, G.L., Malaka, R.: Rules Of Engagement: Levelling Up To Combat Unethical CUI Design. In: Proceedings of the 4th Conference on Conversational User Interfaces, pp. 1–5 (2022). https://doi.org/10.1145/3543829.3544528
Owens, K., Gunawan, J., Choffnes, D., Emami-Naeini, P., Kohno, T., Roesner, F.: Exploring Deceptive Design Patterns in Voice Interfaces. In: Proceedings of the 2022 European Symposium on Usable Security, pp. 64–78 (2022). https://doi.org/10.1145/3549015.3554213
Yildiz, E., Bensch, S., Dignum, F.: Incorporating social practices in dialogue systems. In: Følstad, A., et al. (eds.) Chatbot research and design, CONVERSATIONS 2021. LNCS, vol. 13171, pp. 108–123. Springer, Cham (2022). https://doi.org/10.1007/978-3-030-94890-0_7
Zagal, J.P., Björk, S., Lewis, C.: Dark patterns in the design of games. In: Foundations of Digital Games 2013 (2013)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2024 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Traubinger, V., Heil, S., Grigera, J., Garrido, A., Gaedke, M. (2024). In Search of Dark Patterns in Chatbots. In: Følstad, A., et al. Chatbot Research and Design. CONVERSATIONS 2023. Lecture Notes in Computer Science, vol 14524. Springer, Cham. https://doi.org/10.1007/978-3-031-54975-5_7
Download citation
DOI: https://doi.org/10.1007/978-3-031-54975-5_7
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-54974-8
Online ISBN: 978-3-031-54975-5
eBook Packages: Computer ScienceComputer Science (R0)