生成式图像人工智能在支持早期建筑师-客户沟通中的可供性探索
Exploring the Affordances of Generative Image AI for Supporting Early-stage Architect-client Communication
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中文总结 AI 辅助
本研究通过11对建筑师-客户的实验，发现生成式图像AI能促进共同理解和客户参与，但存在风格偏见和方向不稳定问题，并为未来系统设计提供启示。
中文摘要 AI 辅助
文本到图像的生成式人工智能能够从自然语言提示中近乎实时地生成渲染图，这使得它在早期建筑设计中快速可视化概念方面越来越受欢迎。与此同时，高效交流想法和建立共同理解长期以来一直是建筑师与客户沟通中的核心挑战。生成式图像人工智能的速度将如何改变这种沟通？为探讨这一问题，我们开展了一项涉及11对建筑师-客户的研究，每对参与者通过视频会议使用生成式图像人工智能协作生成客户“梦想之家”的早期渲染图。我们的研究结果表明，生成式图像人工智能通过提供具体的视觉材料和促进想法交流，帮助参与者建立了坚实的共同理解。它还改变了对话动态，使客户能够更积极地参与设计方向的塑造。然而，也出现了一些挑战，包括对特定类型图像的风格偏见以及因生成代际间的变化而导致的设计方向不可预测的转变。最后，我们提出了对未来基于生成式图像人工智能的支持建筑师-客户沟通的系统设计启示。
英文摘要
Text-to-image generative AI can produce renderings from natural-language prompts in near real time, making it increasingly popular for rapidly visualizing concepts in early-stage architectural design. Meanwhile, exchanging ideas efficiently and building shared understanding have long been central challenges in architect-client communication. How might the speed of generative image AI change this communication? To explore this question, we conducted a study with 11 architect-client pairs, in which each pair used generative image AI over video conference to collaboratively produce early-stage renderings of the client's "dream house." Our findings suggest that generative image AI helped pairs develop a solid shared understanding by providing concrete visual materials and supporting the exchange of ideas. It also shifted conversation dynamics, enabling clients to participate more actively in shaping design direction. However, challenges emerged, including a stylistic bias toward particular types of images and unpredictable shifts in design direction caused by variation across generations. We conclude with implications for the design of future generative image AI-based systems that support architect-client communication.
发表机构
- Georgia Institute of Technology（佐治亚理工学院）
机构由 AI 辅助整理，请以论文原文为准。
