| 研究生: |
沈奕呈 Shen, Yi-Chen |
|---|---|
| 論文名稱: |
評估生成式人工智慧於英國建築實務工作流程的影響與潛能:以倫敦適應性再利用與改造計畫為例 Evaluating the Influence and Potential of GenAI on Practical Workflow within the RIBA Plan of Work: A Case Study of Adaptive Reuse and Retrofit Projects in London |
| 指導教授: |
劉舜仁
Liou, Shuenn-Ren 王逸璇 Wang, I-Hsuan |
| 學位類別: |
碩士 Master |
| 系所名稱: |
規劃與設計學院 - 建築學系 Department of Architecture |
| 論文出版年: | 2026 |
| 畢業學年度: | 114 |
| 語文別: | 英文 |
| 論文頁數: | 159 |
| 中文關鍵詞: | 生成式人工智慧 、英國皇家建築師協會工作計劃指引 、改造與活化再利用 、非結構化資料 、實務工作類型 |
| 外文關鍵詞: | Generative AI, RIBA Plan of Work, Adaptive Reuse & Retrofit, Unstructured Information, Practical Work Types |
| 相關次數: | 點閱:3 下載:0 |
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生成式人工智慧 (GenAI) 正迅速改變全球建築、工程與營建(AEC)產業。然而在英國這個高度競爭且具豐富歷史紋理的實務環境中,該技術整合的狀況仍缺乏研究實證。本研究透過了解 GenAI 對建築工作流程的影響,特別針對倫敦複雜的改造(Retrofit)與舊建築再利用 (Adaptive Reuse) 專案中存在的「非結構化資訊落差」做進一步探討。
將英國皇家建築師協會工作計劃指引 (RIBA Plan of Work) 作為研究基礎,本研究採用混合研究方法架構,運用三角檢證策略分析九位參與者的半結構式訪談,其中具備歷史建築改建與使用GenAI雙重經驗的焦點案例受訪者為研究聚焦範例。
研究結果突顯了一個關鍵的偏差:雖然 GenAI 普遍為建築事務所加速了專案早期概念視覺化的工作,但由於嚴格的專業責任要求,它在專案中後期技術交付階段出現驗證上的落差 (Verification Gap)。此外透過比對分析方法,了解到RIBA工作線性流程,與專項處理非結構化歷史資料專案的遞迴流程有本質上的衝突,因此影響該類型專案在工作類型樣態上的呈現。本研究認為,在英國歷史建築改造與再利用實務中,GenAI 的主要價值不在創造新的形式,而是推動前置化 (Front-Loading) 後期的驗證工作,並在專案流程早期透過語意串接,將相關歷史資料進行結構化處理。
這使得專業能動性 (Professional Agency) 必須發生根本轉變,從過往「創作(Authorship)」轉向「定義 (Definition)」。為了解決實務運作上的問題,研究結論指出建築師必須從手工生產者進一步轉變為邏輯的策略管理者,利用 AI 生成來協助建築從業人在專案過程中,讓當今的設計符合文資價值與法規標準的客觀論述。
Generative Artificial Intelligence (GenAI) is rapidly transforming the global Architecture, Engineering, and Construction (AEC) sector. However, empirical evidence regarding its integration within the UK’s highly competitive and historically dense environment remains scarce. This research examines the influence of GenAI on architectural workflows, specifically addressing the "unstructured information gap" in London's complex retrofit and adaptive reuse projects. Adopting a mixed-methods framework anchored in the RIBA Plan of Work, the study employs a triangulation strategy to analyse semi-structured interviews with nine participants, including the pre-setting focal case experts in heritage contexts.
The results highlight a critical misalignment: while GenAI accelerates conceptual visualisation, it creates a "Verification Gap" in technical delivery because of strict professional liability requirements. The analysis confirms that the linear RIBA workflow conflicts with the recursive nature of processing unstructured legacy data. Consequently, the study establishes that GenAI's primary value lies not in generating new forms but in "Front-Loading" verification, acting as a semantic bridge to structure historical data early in the process. This necessitates a fundamental shift in professional agency from "Authorship" to "Definition". To resolve operational friction, the research concludes that architects must evolve from manual producers to strategic supervisors of logic, utilising AI to generate objective rationale that aligns with heritage values and regulatory standards.
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