Abstract
This paper investigates the evolving relationship between generative design algorithms and architectural creativity, a topic of increasing relevance in contemporary practice. As computational tools become more sophisticated, understanding their influence on the creative output of architects is paramount. This research employs a mixed-methods approach, combining a quantitative analysis of design outcomes generated through algorithmic processes with a qualitative assessment of designer perceptions and creative processes. A corpus of architectural projects employing generative design was analyzed for novelty, complexity, and adherence to aesthetic principles, while a survey and interviews were conducted with architects who have utilized these tools. Preliminary findings suggest that generative algorithms can significantly expand the formal possibilities available to designers, fostering novel solutions that might not emerge through conventional methods (Steadman, 2014; Yu et al., 2018). However, the algorithms' impact on creativity is not uniform; it is mediated by the designer's expertise, the specificity of the constraints imposed, and the iterative feedback loops established (Duclos-Prévet et al., 2022; Wang & Han, 2023). While algorithms can augment creative exploration, concerns remain regarding the potential for homogenization of design and the attribution of authorship (Manovich, 2022). This study contributes to the discourse on computational design by providing empirical evidence on how generative algorithms shape, and are shaped by, architectural creativity, offering insights for educators and practitioners navigating this dynamic landscape.