Usable but Conventional: An Empirical Study on the UX of AI-Generated Interface Prototypes

📅 2026-05-14
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🤖 AI Summary
This study presents the first systematic empirical investigation into the dual performance of user interfaces prototyped by generative artificial intelligence (GenAI), specifically examining the trade-off between utility and creativity. Through a blind experiment involving 92 participants, the research employed the UEQ-S questionnaire to evaluate GenAI-generated prototypes against human-designed counterparts across dimensions of pragmatic quality (e.g., usability, efficiency) and hedonic quality (e.g., originality, novelty). Findings indicate that AI-generated prototypes received positive assessments on pragmatic attributes but scored neutrally or negatively on hedonic aspects. These results highlight current limitations of GenAI in balancing functional effectiveness with creative expression in interface design, offering empirical insights to inform future human-AI collaborative approaches in user experience development.
📝 Abstract
This paper investigates User Experience (UX) with prototypes generated by Generative Artificial Intelligence (GenAI) tools. An empirical survey with 92 participants evaluated AI-generated and human-created prototypes without prior identification of authorship. We measured UX using the UEQ-S, covering pragmatic and hedonic dimensions. Results indicate positive evaluations in pragmatic aspects, such as usability and efficiency, and neutral or negative evaluations in hedonic aspects, including originality and innovation. We concluded that GenAI can produce functional interfaces but tends to reinforce visual and structural patterns that affect perceptions of originality.
Problem

Research questions and friction points this paper is trying to address.

User Experience
Generative AI
Interface Prototypes
Originality
Hedonic Quality
Innovation

Methods, ideas, or system contributions that make the work stand out.

Generative AI
User Experience (UX)
Interface Prototyping
UEQ-S
Design Originality