Use of Language to Generate Architectural Scenery with AI-Powered Tools

Abstract

The quality of communication with a computer impacts how the designer performs during the design process. Today, Artificial Intelligence (AI) empowers the designer by expanding the solution space using the expertise from previous knowledge. However, the developments in AI-powered design tools mainly focus on visual and spatial enhancements. In the last decade, AI-powered design tools mostly experimented with image transformation models (GANs) to provide fast insights to designers using learned experiences, simulations, or datasets. The studies on the design process using verbal language with the help of AI are limited. Therefore, designers’ capacity to communicate with intelligent machines would lead us to envision the future of AI-powered design tools. In design practice, designers develop individual and contextual studies through digital tools. This study investigates the process of architectural visual generation and verbal communication to describe architectural images by architecture graduates with prior experience or no experience in prior with Midjourney. The research focuses on the designers’ semantic language during the design process with the AI-powered tool and analysis of the verbal part of the communication. The results of this study show that participants’ first impressions of the image and how they express their impressions through description do not correspond with how Midjourney interprets those descriptions. Furthermore, architects’ image generation process using the tool is nonlinear. As architects develop a deeper understanding of changing modes of interactions, they are more likely to benefit from AI-powered tools as collaborative entities.