Investigating Visual Countermeasures Against Dark Patterns in User Interfaces

Abstract

Dark patterns are malicious interface design strategies on the web and in apps that trick users into decisions that go against their best interests, costing them money, time, or private data. While there are approaches to classifying these patterns and investigating user awareness, there has been little work looking into visual countermeasures against dark patterns. In this work, we used an online survey to investigate concepts for six visual countermeasures against three common dark patterns: Confirmshaming, Low-stock Message, and Visual Interference. Our results indicate two opposing forces for users: On the one hand, users dislike systems actively making silent changes to their screen, preferring to be informed about the presence of dark patterns. On the other hand, they do not want applications to become visually cluttered, as this may impact their productivity. We found that different applications of dark patterns require different countermeasures, and that individual preferences vary strongly.