AI能复现波斯鸽塔外观却误解其材料与气候智慧
From Clay to Code: Typological and Material Reasoning in AI Interpretations of Iranian Pigeon Towers
- 用三类扩散模型测试不同提示阶段的生成效果
- AI准确还原几何形态但误读材料与气候逻辑
- 适合研究AI对传统建筑认知偏差的学者参考
本研究探讨生成式AI如何理解民间建筑中的设计智慧。以伊朗鸽塔为例，测试Midjourney v6、DALL-E 3和基于Stable Diffusion XL（SDXL）的DreamStudio三个扩散模型，在参照、适应和推测三类提示阶段的表现。采用五项评估框架分析其对类型学、材质、环境、真实感与文化特异性的重构能力。结果表明，AI可稳定复现几何图案，但误读材料选择与气候适应性逻辑。引用图像提升真实感却抑制创造力，完全自由生成则具创新性但文化指向模糊。研究揭示了视觉相似性与建筑逻辑理解之间的界限，提出‘计算性民间推理’作为分析AI如何感知、扭曲并重塑传统设计智慧的框架。
原文摘要 · Abstract (English)
This study investigates how generative AI systems interpret the architectural intelligence embedded in vernacular form. Using the Iranian pigeon tower as a case study, the research tests three diffusion models, Midjourney v6, DALL-E 3, and DreamStudio based on Stable Diffusion XL (SDXL), across three prompt stages: referential, adaptive, and speculative. A five-criteria evaluation framework assesses how each system reconstructs typology, materiality, environment, realism, and cultural specificity. Results show that AI reliably reproduces geometric patterns but misreads material and climatic reasoning. Reference imagery improves realism yet limits creativity, while freedom from reference generates inventive but culturally ambiguous outcomes. The findings define a boundary between visual resemblance and architectural reasoning, positioning computational vernacular reasoning as a framework for analyzing how AI perceives, distorts, and reimagines traditional design intelligence.
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