Shape-finding in Biophilic Architecture: Application of AI-based Tool

Viliūnas, Gediminas; Gražulevičiūtė–Vileniškė, Indrė

doi:10.2478/aup-2022-0007

Cited by 2 publications

(2 citation statements)

References 16 publications

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“…The ethical implications of AI's potential to manipulate emotional responses, particularly in sensitive fields like architectural design, call for careful scrutiny (Chiarella et al, 2022 ; Futami et al, 2022 ). The interaction between AI-generated emotions and human responses in architectural imagery is an area of growing interest, with studies focusing on how these images influence human emotional and behavioral responses, and what this implies for the future of architectural experience (Viliunas and Grazuleviciute-Vileniske, 2022 ; Enjellina et al, 2023 ).…”

Section: Literature Reviewmentioning

confidence: 99%

Decoding emotional responses to AI-generated architectural imagery

Zhang,

Fort,

Giménez Mateu

2024

Front. Psychol.

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IntroductionThe integration of AI in architectural design represents a significant shift toward creating emotionally resonant spaces. This research investigates AI's ability to evoke specific emotional responses through architectural imagery and examines the impact of professional training on emotional interpretation.MethodsWe utilized Midjourney AI software to generate images based on direct and metaphorical prompts across two architectural settings: home interiors and museum exteriors. A survey was designed to capture participants' emotional responses to these images, employing a scale that rated their immediate emotional reaction. The study involved 789 university students, categorized into architecture majors (Group A) and non-architecture majors (Group B), to explore differences in emotional perception attributable to educational background.ResultsFindings revealed that AI is particularly effective in depicting joy, especially in interior settings. However, it struggles to accurately convey negative emotions, indicating a gap in AI's emotional range. Architecture students exhibited a greater sensitivity to emotional nuances in the images compared to non-architecture students, suggesting that architectural training enhances emotional discernment. Notably, the study observed minimal differences in the perception of emotions between direct and metaphorical prompts among architecture students, indicating a consistent emotional interpretation across prompt types.ConclusionAI holds significant promise in creating spaces that resonate on an emotional level, particularly in conveying positive emotions like joy. The study contributes to the understanding of AI's role in architectural design, emphasizing the importance of emotional intelligence in creating spaces that reflect human experiences. Future research should focus on expanding AI's emotional range and further exploring the impact of architectural training on emotional perception.

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Section: Literature Reviewmentioning

confidence: 99%

Decoding emotional responses to AI-generated architectural imagery

Zhang,

Fort,

Giménez Mateu

2024

Front. Psychol.

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“…Through her work, she creates synthetic images in between our know natural morphologies -assembling new biological shapes, patterns, and organisms (Crespo, 2022). Along the same vein is the research on shape-finding in Biophilic Architecture (Viliunas and Grazuleviciute-Vileniske, 2022). Here the authors utilize a VQ-GAN+CLIP network to successfully unearth images of new unexpected forms with biophilic characteristics based on a selected vocabulary, which can be the start of a further creative search for architects.…”

Section: Related Workmentioning

confidence: 99%

AI Diffusion as Design Vocabulary - Investigating the use of AI image generation in early architectural design and education

Bank Stigsen,

Moisi,

Rasoulzadeh

et al. 2023

eCAADe Proceedings

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This paper investigates the potential of Text-to-Image AI in assisting the ideation phase in architectural design and education. The study proposes a structured workflow and tests it with first-year architecture students. It aims to create a comprehensive design vocabulary by using AI-generated images as primary design references and incorporating them into a modelling workflow. The paper implements a process combining specific vocabulary extraction, image generation, 2D to 3D translation, and spatial composition within a six weeklong design course. The findings suggest that such a process can enhance the ideation phase by generating new and diverse design inspirations, improve spatial understanding through the exploration of various design elements, and provide students with a targeted visual vocabulary that helps define design intention and streamlines the modelling process.

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Shape-finding in Biophilic Architecture: Application of AI-based Tool

Cited by 2 publications

References 16 publications

Decoding emotional responses to AI-generated architectural imagery

Decoding emotional responses to AI-generated architectural imagery

AI Diffusion as Design Vocabulary - Investigating the use of AI image generation in early architectural design and education

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