Akademik Veri Yönetim Sistemi
XIV. Uluslararası Sinan Sempozyumu, Edirne, Türkiye, 17 Nisan 2025, cilt.1, ss.29-40, (Tam Metin Bildiri)
THE IMPACT OF AI ON ARCHITECTURAL CREATIVITY: A COMPARATIVE ANALYSIS OF CREATIVITY LEVELS
Design, traditionally considered a process based on human creativity, is now being reshaped with the integration of AI-supported tools. Especially in dealing with ill-defined problems, the architectural design process, traditionally relying on human intuition and creative thinking, gains a new dimension through the automation and data power provided by AI. Numerous studies explore the role of artificial intelligence in creative disciplines, addressing both the advantages and disadvantages of AI. However, the interaction between human intuition and the data richness provided by AI, and how this interaction changes according to individual creativity levels, has not yet been fully investigated. This study examines the impact of AI-supported design tools on architectural creativity through a comparative analysis, contrasting them with traditional sketching methods based on different creativity levels. The study's primary hypothesis is that AI-supported design tools affect the creative process in ways that differ from traditional sketching methods, and that the extent to which AI-supported design tools make the design process more efficient and creative may be related to the creativity levels of individuals. Furthermore, it is hypothesized that AI-supported design may have different effects on creativity parameters (originality, appropriateness, and aesthetic value) compared to traditional sketching methods. To determine participants' initial creative potential, George Land’s Creativity Test was used, and Amabile’s Consensual Assessment Technique (CAT) was employed to evaluate design outputs. Participants, who were balanced according to their creativity scores, were divided into two groups and completed two different design tasks using traditional sketching and AI-supported design methods. The findings revealed that students with lower creativity scores performed better in AI-supported design, but no direct correlation was found between the creativity test scores and the design tool used. The study also showed that AI-supported design increased originality but scored lower on appropriateness compared to traditional sketching methods. No significant difference was found between the two methods in terms of aesthetic value. This research highlights the advantages and limitations of integrating AI into the architectural design process, offering valuable insights into how the creative process is shaped. The results provide important information on how AI-supported design can be used more effectively in educational and professional contexts in the future.
Keywords: Creativity, DALL-E, assisted creation tools, artificial intelligence, design education.