MİM405

School of Architecture and Design \ Architecture

3

6

Compulsory

English

MİM 306

Architecture

This course focuses on the intersection of architecture and artificial intelligence (AI), exploring the transformative potential of AI tools in architectural design processes, visualization, and presentations. Students will examine the theoretical foundations of AI applications in architecture, ethical concerns, and the implementation of cutting-edge AI technologies in the field.
Throughout the course, students will be introduced to a range of AI tools such as ChatGPT, Midjourney, Leonardo AI, Stable Diffusion, Luma AI, Adobe Firefly, DALL·E, RunwayML, and Microsoft Sketch2Code. These tools serve various purposes, including conceptual art generation, ideation, site analysis, generative design, image editing, 3D modeling, video synthesis, style transfer, and converting hand-drawn sketches into HTML code.
The course emphasizes experiential learning by engaging students in workshops and projects that incorporate AI tools to enhance the architectural design process. Students will be encouraged to critically assess the influence of AI on the field of architecture, question the reliability and accuracy of AI-generated information, and explore the potential drawbacks of excessive reliance on AI in design workflows.
By the end of the course, students will gain a comprehensive understanding of AI’s role in architecture and its potential impact on the future of the profession. They will develop practical skills in using various AI tools and techniques and will be prepared to apply these capabilities in their own architectural projects and research endeavors.

Adobe Inc. (n.d.). Generative Fill in Photoshop (beta). https://helpx.adobe.com/photoshop/using/generative-fill.html
Audi, R. (2018). Epistemoloji: Bilgi teorisine çağdaş bir giriş (M. Tuncel, Trans.). Nobel Akademik Yayıncılık.
Beyter, T. (2019, May 26). Epistemoloji (Bilgi felsefesi): Neyi, ne kadar, nasıl bilebiliriz? Bilginin doğası nedir? Evrim Ağacı. https://evrimagaci.org/epistemoloji-bilgi-felsefesi-neyi-ne-kadar-nasil-bilebiliriz-7872
Burry, M., & Burry, J. (2020). The new mathematics of architecture (2nd ed.). Thames & Hudson.
Carpo, M. (2021). Beyond digital: Design and automation at the end of modernity. MIT Press.
Celani, G., & Vaz, C. E. V. (2022). Artificial intelligence in architecture: Generative design and machine learning in theory and practice. Architectural Design, 92(4), 8–15. https://doi.org/10.1002/ad.2822
Krish, S., & McCormack, J. (2022). AI-assisted design: Current trends and future directions in computational creativity. Design Studies, 78, 101078. https://doi.org/10.1016/j.destud.2021.101078
Leonardo AI. (n.d.). Leonardo AI. https://leonardo.ai/
Midjourney. (n.d.). Midjourney. https://www.midjourney.com/
OpenAI. (n.d.). ChatGPT. https://chat.openai.com/
OpenAI. (n.d.). DALL·E. https://openai.com/dall-e
Peters, B. (Ed.). (2020). Computational design thinking. Wiley.
Runway AI, Inc. (n.d.). RunwayML. https://runwayml.com/
Terzidis, K. (2023). Artificial intelligence in architectural design. Routledge.
Turing, A. M. (2009). Computing machinery and intelligence. In R. Epstein, G. Roberts, & G. Beber (Eds.), Parsing the Turing test (pp. 23–65). Springer. https://doi.org/10.1007/978-1-4020-6710-5_3
Vardouli, T. (2012). Bilgisayarın bin yüzü: Bilgisayarın tasarımda insanlaştırılması (1965–1975). Dosya, 29, 25–34.

The objective of this course is to provide students with a comprehensive understanding of artificial intelligence (AI) in the context of architecture, focusing on its applications in design, visualisation, and research processes. The course aims to familiarise students with a range of AI tools and their potential for generating innovative solutions, while also encouraging critical reflection on the ethical, social, and environmental aspects of their use. Through interactive workshops, individual exercises, and group projects, students will gain practical skills in integrating AI technologies into architectural workflows. Key goals include fostering creativity, promoting responsible and informed decision-making, and developing the ability to evaluate AI-generated outputs in terms of reliability, accuracy, and limitations.

1. Demonstrate a comprehensive understanding of the basic concepts, principles and techniques of artificial intelligence and its applications in the field of architecture (KNOWLEDGE)
2. Using various AI tools such as ChatGPT, Google Bard, Midjourney, LeonardoAi, Stable Diffusion, Luma AI, Adobe Firefly, DALL-E, RunwayML and Microsoft Sketch2Code in architectural design, visualisation and presentation tasks (SKILLS)
3. Analyse and evaluate the ethical, social and environmental implications of incorporating AI into the architectural design process and develop strategies for responsible and sustainable use of AI technologies in professional practice (COMPETENCY)
4. Using critical thinking, problem solving and creative skills in the use of AI tools in architectural design, presentation and research phases (SKILLS)
5. Effectively communicate the results of AI-supported design processes in various media formats such as presentations, reports and visualisations (SKILLS)
6. Develop a deeper understanding of the opportunities and challenges of AI integration in architectural design, delivery and research processes through participation and collaboration in interdisciplinary discussions with different experts in the fields of AI and architecture (COMPETENCY)
7. Evaluate the reliability and accuracy of the information produced, identify potential risks, limitations and biases in AI-assisted design results and develop strategies to mitigate potential problems (COMPETENCE)

Week 1:
Course introduction and familiarisation
Explanation of the syllabus and expectations
Information about the course and important dates
Making an overview of the topics to be covered during the semester
Week 2:
Can machines think? An evaluation and discussion on the concepts of thinking, designing and creativity
To discuss the concepts of AI, Machine learning and Deep learning
Making an overview on current AI software and application areas
Week 3:
"What is knowledge? What is "Right Information"? How to reach the right information?
An overview of Text-to-Text generating AI software.
"Promt" concept and numerical representation of information
Are we chatting or researching? An evaluation on Chat Bots
Week 4:
What is Data? Processing and interpretation of Data and distinction between Information and Data
Overview of AI software that generates images from text
Discussion on the problem of transferring/transforming data and information from text to image
Week 5:
An overview of text-to-image generating AI software
What is data? What is Data? Processing and interpretation of data
Discussion on the problem of transferring/transformation of data and information from text to image.
Week 6: Project work on the use of artificial intelligence 1
Week 7: Project work on the use of artificial intelligence 1
Week 8: Project work on the use of artificial intelligence 1
Week 9: Project work on the use of artificial intelligence 1 Evaluation and Discussions
Week 10: Project work on the use of artificial intelligence 2
Week 11: Project work on the use of artificial intelligence 2
Week 12: Project work on the use of artificial intelligence 2

• Homework
• Project