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.

翻译：人机交互与人工智能领域的最新进展试图通过AI赋能的工具来支持用户体验实践者。尽管新兴模型和新型交互机制展现出潜力，但这些工具的主流应用仍十分有限。我们以人本人工智能为视角，对359篇论文进行了系统性文献综述，旨在梳理当前研究格局、识别发展趋势，并揭示用户体验实践者在AI支持中尚未满足的需求。在双钻设计框架的指导下，我们的分析发现：用户体验实践者对共情构建以及跨界面屏幕体验的独特关注点常被忽视。简单化的AI自动化可能会阻碍宝贵的共情构建过程。此外，仅关注单个界面屏幕而忽视交互流程与用户路径，会降低系统对用户体验设计师的实用价值。基于这些发现，我们呼吁更深入地理解用户思维模式，并构建更偏向设计师的数据集与评估指标，以期人机交互与人工智能社群共同协作，为用户体验提供有效的AI支持。