User interfaces (UIs) are the primary gateway for users to access digital systems, ranging from healthcare and finance applications to AI-powered platforms. Yet many of these interfaces embed dark patterns - manipulative design strategies that deceive, coerce, or otherwise influence users into making unintended decisions that benefit services while threatening users’ privacy, safety, and autonomy. Recently, the UI design process has evolved rapidly with the widespread adoption of generative AI. In particular, designers increasingly use prompt-to-design generators (Prodegens) to create UI prototypes directly from natural language prompts. This emerging paradigm of designer-Prodegen collaboration may reshape the landscape of dark patterns, yet its effects remain largely unexplored. In this study, we investigate how such collaborations influence dark patterns that harm users’ privacy rights. Specifically, We conducted designer-centric studies with 17 professional UI designers to examine their awareness, attitudes, and practices, and complemented this with a technical evaluation of real-world prompts across multiple Prodegens. Our analysis identifies both designer practices related to dark pattern occurrence and mitigation, as well as system-level factors in Prodegens that facilitate dark patterns, providing insights for mitigating privacy risks from the perspectives of designers, Prodegen developers, and end users.
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When Designers Meet GenAI: Understanding the Role of Prompt-to-Design Generators in Privacy Dark Patterns
Studies with 17 professional UI designers examine how collaborating with prompt-to-design generators, which turn natural-language prompts into prototypes, shapes the privacy-harming manipulative patterns that end up in interfaces.