用人机交互(HCI)方法在建筑设计中应用人工智能教育(AIEd)

Eídos Pub Date : 2024-01-01 DOI:10.29019/eidos.v17i23.1282
Lok Hang Cheung, Juan Carlos Dall’Asta
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引用次数: 0

摘要

人工智能(AI)在建筑设计(AIEd)领域的应用取得了长足的发展,而生成式人工智能(GAI)在建筑设计教育中的应用潜力巨大。然而,应对与人工智能相关的挑战非常重要。这些挑战包括过度炒作、隐藏的内在弊端(如公平性和道德),以及在涉及人工智能时缺乏人际互动的趋势。为了解决这些问题,本文介绍了一个包含三个关键视角的三角研究框架:愿景、技术和用户接受度。该框架与人机交互(HCI)原则、人工智能技术发展以及人工智能教育的以往经验相一致。通过采用这种多视角分析方法,本文旨在全面了解建筑设计中的人工智能现象。此外,本文所介绍的研究还超越了理论讨论的范畴,说明了如何将研究成果应用于实践。它展示了一个正在进行的建筑设计课程的设计,该课程结合了从研究中获得的见解。从正在设计的模块中观察到的三个关键点表明,有必要将重点转向多模式人工智能与现有参数化工具的整合。其次,必须强调人工智能是设计伙伴,而不是假设人工智能在不同阶段的具体用途。最后,提供用户友好型工具和理论基础可以激励学生在设计过程之外进行探索,扩大他们的研究和设计范围。
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Human-computer Interaction (HCI) Approach to Artificial Intelligence in Education (AIEd) in Architectural Design
The field of artificial intelligence (AI) in architectural design (AIEd) has experienced significant growth, and there is great potential for the application of Generative AI (GAI) in architectural design education. However, addressing challenges associated with AI is important. These include overhyped speculation, hidden inherent drawbacks such as fairness and ethics, and a trend of lacking human interaction when AI is involved. To tackle these issues, this paper introduces a triangulated research framework encompassing three key perspectives: vision, technology, and user acceptance. This framework aligns with Human-computer Interaction (HCI) principles, AI technology development, and past experiences in AIEd. By adopting this multi-perspective analysis approach, the paper aims to comprehensively understand the phenomena surrounding AI in architectural design. Furthermore, the research presented in this paper goes beyond theoretical discussions and illustrates how the research findings are applied in practice. It showcases the design of an ongoing architectural design course that incorporates the insights gained from the research. Three key observations from the ongoing designed modules indicate the need to shift the focus towards integrating multi-modal AIs and existing parametric tools. Secondly, it is essential to emphasise AIs as design partners rather than making assumptions about AIs’ specific uses at different stages. Lastly, providing user-friendly tools and theoretical foundations motivates students to explore beyond the design process, expanding their research and design boundaries.
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