The Use of Text-To-Image Generation Artificial Intelligence Tools for the Production of Biophilic Design in Architecture

Öz

Advances in artificial intelligence (AI) systems capable of generating images from text hold significant and innovative potential in the field of architecture. Combining biophilic design principles with AI image-generation models offers new opportunities for innovative architectural approaches. This study explores how text-to-image AI tools can be used to create biophilic office spaces that aim to increase the comfort and work capacity of office workers by connecting with nature. With reference to the biophilic criteria in Browning, Ryan and Clancy's (2014) research, the study examines the use of artificial intelligence systems to generate biophilic solutions in architectural design. In the article, Leonardo AI tool was used to produce office spaces that meet these criteria. When prompts related to biophilic criteria were entered into the AI tool, it was found that it produced spaces that meet biophilic design standards. This research points to an important step in integrating AI-assisted text-image generation with biophilic design thinking in the early stages of architectural design. As a result, this study demonstrates not only the capacity of AI to generate images, but also its ability to align with biophilic design principles and it’s potential to enhance these principles.

Anahtar Kelimeler

• Biophilic Approach
• Artificial intelligence
• Biophilic design
• Form finding
• Architectural design

Mimaride Biyofilik Tasarım için Metinden Görüntü Üretme Potansiyeli Olan Yapay Zeka Araçlarının Kullanımı

Öz

Metinden görüntü üretme yeteneğine sahip yapay zekâ (YZ) sistemlerindeki ilerlemeler, mimarlık alanında önemli ve yenilikçi potansiyeller barındırmaktadır. Biyofilik tasarım ilkelerinin yapay zekâ görüntü oluşturma modelleriyle birleştirilmesi, yenilikçi mimari yaklaşımlar için yeni fırsatlar sunmaktadır. Bu çalışma, doğayla bağlantı kurarak ofis çalışanlarının konforunu ve çalışma kapasitesini artırmayı amaçlayan biyofilik ofis alanları oluşturmak için metinden görüntü oluşturan yapay zekâ araçlarının nasıl kullanılabileceğini araştırmaktadır. Çalışma, Browning, Ryan ve Clancy'nin (2014) araştırmasında yer alan biyofilik kriterleri referans alarak, mimari tasarımda biyofilik çözümler üretmek amacıyla yapay zekâ sistemlerinin kullanılmasını incelemektedir. Makalede Leonardo AI aracı kullanılarak bu kriterlere uygun ofis alanları üretilmiştir. Yapay zekâ aracına, biyofilik kriterler ile ilgili istemler girildiğinde biyofilik tasarım standartlarını karşılayan alanlar ürettiği tespit edilmiştir. Bu araştırma, yapay zekâ destekli metin-görüntü oluşturmanın mimari tasarımın ilk aşamalarda biyofilik tasarım düşüncesiyle entegre edilmesinde önemli bir adıma işaret etmektedir. Sonuç olarak çalışma, yapay zekanın sadece görüntü oluşturma kapasitesini değil, aynı zamanda biyofilik tasarım ilkeleriyle uyum sağlama yeteneğini ve bu ilkeleri geliştirme potansiyelini göstermektedir.

Anahtar Kelimeler

• Biyofilik yaklaşım
• Yapay zekâ
• Biyofilik tasarım
• Form bulma
• Mimari tasarım

Kaynakça

1. Abdel H. 2022a. Mr.Green'in ofisi / MIA design studio. https://www.archdaily.com/977944/mreens-office-mia-design-studio (accessed date: March 12, 2022).
2. Abdel H. 2022b. Biophilic office andyrahman architect. https://www.archdaily.com/982765/biophilic-office-andyrahman-architect?ad_medium=gallery (accessed date: March 12, 2022).
3. Aslan T, Aydın K. 2023. Metinden görüntü üretme potansiyeli olan yapay zekâ sistemleri sanat ve tasarım performanslarının incelenmesi. OMÜ J Edu Fac, 42(2): 1049-1198. https://doi.org/10.7822/omuefd.1293657
4. Browning W, Ryan C, Clancy J. 2014. 14 Patterns of biophilic design improving health & well-being in the built environment. Terrapin Bright Green LLC, 2014: 63.
5. Chang CC, Cheng GJY, Nghiem TPL, Song XP, Oh RRY, Richards DR, Carrasco LR. 2020. Social media nature and life satisfaction: global evidence of the biophilia hypothesis. Sci Reports, 10(1): 4125.
6. Chiu TK. 2023. The impact of generative AI (GenAI): on practices policies and research direction in education: A case of ChatGPT and Midjourney. Interact Learn Environ, 2023: 1-17.
7. Cobb PJ. 2023. Large language models and generative AI Oh My!: Archaeology in the Time of ChatGPT Midjourney and Beyond. Adv Archaeoll Pract 11(3): 363-369.
8. Crowson K, Biderman S, Kornis D, Stander D, Hallahan E, Castricato L, Raff E. 2022 October. Vqgan-clip: Open domain image generation and editing with natural language guidance. Springer Nature, Bern, Switzerland, pp: 88-105.

9. Hartig T, Mitchell R, De Vries S, Frumkin H. 2014. Nature and health. Annual Rev Public Health, 35: 207-228.
10. Hung SH, Chang CY. 2021. Using AI to extract biophilic design elements and predict health benefits and tradition environmental Qi. https://auckland.figshare.com/articles/conference_contribution/Using_AI_to_Extract_Biophilic_Design_Elements_and_Predict_Health_Benefits_and_Tradition_Environmental_Qi/13578209 (accessed date: March 12, 2022).
11. Kelleher JD. 2019. Deep learning. MIT press, London, UK, pp: 251.
12. Kellert S, Finnegan B. 2011. Biophilic design: the Architecture of Life. A 60 minute video. www.bullfrogfilms.com (accessed date: March 12, 2022).
13. Kellert S, Wilson EO. 1993. The biophilia hypothesis. Island Press, Washington DC, USA, pp: 187.
14. Kellert S. 1997. Kinship to mastery: Biophilia in human evolution and development. Island Press, Washington DC, USA, pp: 114.
15. Kellert S. 2005. Building for life: Understanding and designing the human-nature connection. Island Press, Washington DC, USA, pp: 243.
16. Kellert S. 2012. Birthright: People and nature in the modern world. Yale University Press, New Haven, USA, pp: 104.
17. Kellert SJ. Heerwagen MM. 2008. Biophilic design: the theory science and practice of bringing buildings to life. John Wiley, London, UK, pp: 457.
18. Kellert SR, Calabrese EF. 2015. The practice of biophilic design. https://www.biophilic-design.com/_files/ugd/21459d_81ccb84caf6d4bee8195f9b5af92d8f4.pdf (accessed date: March 12, 2022).
19. Kellert SR, Heerwagen J, Mador M. 2011. Biophilic design: the theory science and practice of bringing buildings to life. John Wiley & Sons, London, UK, pp: 412.
20. Korpela KM, Ylén M, Tyrväinen L, Silvennoinen H. 2008. Determinants of restorative experiences in everyday favorite places. Health Place 14(4): 636-652.
21. Korpela KM, Ylén M, Tyrväinen L, Silvennoinen H. 2010. Favorite green waterside and urban environments restorative experiences and perceived health in Finland. Health Prom Inter, 25(2): 200-209.
22. Leach N. 2021. Architecture in the age of artificial intelligence. Bloomsbury Publishing Plc, London, UK, pp: 15-97.
23. Nieuwenhuijsen MJ, Khreis H, Triguero-Mas M, Gascon M, Dadvand P. 2017. Fifty shades of green: pathway to healthy urban living. Epidemiol, 28(1): 63-71.
24. Oppenlaender J. 2022. The creativity of text-to-image generation. Academic Mindtrek ‘22: Proceedings of the 25th International Academic Mindtrek Conference, November 16-18, New York, USA, pp: 192-202.
25. Paananen V, Oppenlaender J, Visuri A. 2023. Using text-to-image generation for architectural design ideation. Inter J Architect Comput, 2023: 14780771231222783.
26. Ríos-Rodríguez ML, Testa Moreno M, Moreno-Jiménez P. 2023. Nature in the office: A systematic review of nature elements and their effects on worker stress response. Healthcare, 11(21): 2838).
27. Rombach R, Blattmann A, Ommer B. 2022. Text-guided synthesis of artistic images with retrieval-augmented diffusion models. arXiv preprint arXiv, 2207: 13038.
28. Scopelliti M, Carrus G, Bonaiuto M. 2019. Is it really nature that restores people? A comparison with historical sites with high restorative potential. Front Psychol, 9: 426012.
29. Shahid F. 2024. The organic challenge: The organic challenge: cultivating conscious design for biodigital tectonics within aı’s prompt-to-pixel process. J Artificial Intellig Architect, 3(1): 11-23.
30. Souza DM, Wehrmann J, Ruiz DD. 2020. Efficient neural architecture for text-to-image synthesis. In 2020 International Joint Conference on Neural Networks, 19-24 July 2020, Glasgow, UK, pp: 1-8.
31. URL-1: https://www.merriam-webster.com/dictionary/biophilia (accessed date: March 12, 2022).
32. URL-2: Leonardo.Ai. https://leonardo.ai/ (accessed date: March 12, 2022).
33. URL-3: https://www.lovethatdesign.com/project/smart-dubai-office-dubai/ (accessed date: March 12, 2022).
34. URL-4: https://archello.com/story/78395/attachments/photos-videos/6 (accessed date: March 12, 2022).
35. Viliunas G, Grazuleviciute-Vileniske I. 2022. Shape-finding in biophilic architecture: application of ai-based tool. Architect Urban Plan, 18(1): 68-75.
36. Wang L. 2018. A London office boasts biophilic design for a healthier happier workplace. https://inhabitat.com/a-london-office-boasts-biophilic-design-for-a-healthier-happier-workplace/ (accessed date: March 12, 2022).
37. Wilson E.O. 1986. Biophilia: the Human Bond with Other Species. Harvard University Press, Cambridge, USA, pp: 96.
38. Zamfirescu-Pereira JD, Wong RY, Hartmann B, Yang Q. 2023. Why Johnny can’t prompt: how non-AI experts try (and fail): to design LLM prompts. In Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems, April 23-28, Hamburg, Germany, pp: 1-21.