mlsanityData to 7 Oct 2026

"She was useful, but a bit too optimistic": Augmenting Design with Interactive Virtual Personas

arXiv 2508.19463 ↗First posted 26 Aug 2025cs.HC cs.AIcited by 0

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Abstract (arXiv)

Personas have been widely used to understand and communicate user needs in human-centred design. Despite their utility, they may fail to meet the demands of iterative workflows due to their static nature, limited engagement, and inability to adapt to evolving design needs. Recent advances in large language models (LLMs) pave the way for more engaging and adaptive approaches to user representation. This paper introduces Interactive Virtual Personas (IVPs): multimodal, LLM-driven, conversational user simulations that designers can interview, brainstorm with, and gather feedback from in real time via voice interface. We conducted a qualitative study with eight professional UX designers, employing an IVP named "Alice" across three design activities: user research, ideation, and prototype evaluation. Our findings demonstrate the potential of IVPs to expedite information gathering, inspire design solutions, and provide rapid user-like feedback. However, designers raised concerns about biases, over-optimism, the challenge of ensuring authenticity without real stakeholder input, and the inability of the IVP to fully replicate the nuances of human interaction. Our participants emphasised that IVPs should be viewed as a complement to, not a replacement for, real user engagement. We discuss strategies for prompt engineering, human-in-the-loop integration, and ethical considerations for effective and responsible IVP use in design. Finally, our work contributes to the growing body of research on generative AI in the design process by providing insights into UX designers' experiences of LLM-powered interactive personas.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 27 of its 105 references that are in the map. First posted on arXiv 26 Aug 2025.

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27 of 105 references.

References · 27

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15 more
  1. 2023CoMPosT: Characterizing and Evaluating Caricature in LLM Simulationscited by 94
  2. 2021Towards a Science of Human-AI Decision Making: A Survey of Empirical Studiescited by 85
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