Deceptive Patterns
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Fighting Malicious Designs: Towards Visual Countermeasures Against Dark Patterns

Author
René Schäfer, P. Preuschoff, René Röpke, Sarah Sahabi, Jan O. Borchers
Date
11 May 2024
Publisher
International Conference on Human Factors in Computing Systems
Focus
HCI & Psychology
Category
Academic Scholar

This work tested three visual countermeasures against 13 common dark patterns in an interactive lab study and was able to extract multiple clusters of dark patterns where participants preferred specific countermeasures for similar reasons.

Dark patterns are malicious UI design strategies that nudge users towards decisions going against their best interests. To create technical countermeasures against them, dark patterns must be automatically detectable. While researchers have devised algorithms to detect some patterns automatically, there has only been little work to use obtained results to technically counter the effects of dark patterns when users face them on their devices. To address this, we tested three visual countermeasures against 13 common dark patterns in an interactive lab study. The countermeasures we tested either (a) highlighted and explained the manipulation, (b) hid it from the user, or (c) let the user switch between the original view and the hidden version.