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AI Assistance for UX: A Literature Review Through Human-Centered AI

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arxiv 2402.06089 v2 pith:O43BKEK5 submitted 2024-02-08 cs.HC

Yuwen Lu , Yuewen Yang , Qinyi Zhao , Chengzhi Zhang , Toby Jia-Jun Li This is my paper · ORCID
classification cs.HC
keywords practitionerssupporthuman-centeredliteraturereviewscreenstoolsuser
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Recent advancements in HCI and AI research attempt to support user experience (UX) practitioners with AI-enabled tools. Despite the potential of emerging models and new interaction mechanisms, mainstream adoption of such tools remains limited. We took the lens of Human-Centered AI and presented a systematic literature review of 359 papers, aiming to synthesize the current landscape, identify trends, and uncover UX practitioners' unmet needs in AI support. Guided by the Double Diamond design framework, our analysis uncovered that UX practitioners' unique focuses on empathy building and experiences across UI screens are often overlooked. Simplistic AI automation can obstruct the valuable empathy-building process. Furthermore, focusing solely on individual UI screens without considering interactions and user flows reduces the system's practical value for UX designers. Based on these findings, we call for a deeper understanding of UX mindsets and more designer-centric datasets and evaluation metrics, for HCI and AI communities to collaboratively work toward effective AI support for UX.

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Cited by 2 Pith papers

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  2. The role of large language models in UI/UX design: A systematic literature review

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    A systematic review of 38 studies finds LLMs are increasingly integrated across the UI/UX design lifecycle, with prompt engineering and human oversight as key practices.

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