Abstract:Current approaches to addressing deceptive design largely focus on visible interface manipulations, commonly referred to as "dark patterns". With the rise of generative AI, deception is becoming more difficult to spot and easier to live with, as it is quietly embedded in default settings, automated suggestions, and conversational interactions rather than discrete interface elements. These subtle, normalised forms of influence, which Simone Natale frames as "banal deception", shape everyday digital use and blur the line between AI-enabled assistance and manipulation.
This position paper explores banality as a lens through which to reason through deception in generative AI experiences, especially with chatbots. We explore what Natale describes as users' own involvement in their deception, and argue that this perspective could lead to future work for introducing friction to safeguard users from deception in generative AI interactions, such as empowering users through raising awareness, providing them with intervention tools, and regulatory or enforcement improvements. We present these concepts as points for discussion for the deceptive design scholarly community.
| Comments: | Accepted at CHI'26 ACAI Workshop |
| Subjects: | Human-Computer Interaction (cs.HC); Computers and Society (cs.CY) |
| ACM classes: | H.5.2; K.4.1; K.4.2 |
| Cite as: | arXiv:2605.07012 [cs.HC] |
| (or arXiv:2605.07012v1 [cs.HC] for this version) | |
| https://doi.org/10.48550/arXiv.2605.07012 arXiv-issued DOI via DataCite (pending registration) |
From: Ishitaa Narwane [view email]
[v1]
Thu, 7 May 2026 22:49:55 UTC (83 KB)
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