Abstract
Artificial intelligence (AI) is a current phenomenon that influences every aspect of life. Particularly in the realms of society and design, AI’s capacity to generate images from text prompts is increasingly prevalent. Recent studies expand the integration of AI and machine learning (ML) principles into design education. This study highlights an experiment involving AI integration within the Design Semiotics for Interior Architecture and Environmental Design (IAED), a second-year major undergraduate course aimed at imparting essential skills for comprehending design’s embedded meanings and decoding cultural and social messages. The study’s motive is to foster creative exploration in design education by encouraging interactions among students, design semiotics, and AI using Midjourney, a generative AI tool that generates images from text prompts. Conducted over five weeks and structured into four stages, the experiment fosters iterative analysis and synthesis among student pairs. These stages involve (1) responding to randomly generated question models (i.e. How ‘abstract concept’ can be defined in the context of ‘spatial keyword’ based on the / through / as ‘semiotics terminology’?), designing prompts for Midjourney, and generating images, (2) providing feedback on peers’ images, (3) refining prompts based on feedback, and (4) creating new images through blending previous iterations. The finale of this experiment involves presenting the entire process and reflecting on the experience of utilizing generative AI. The study’s findings define both the advantages and challenges associated with employing generative AI programs and their associated ML technologies in design education.
Details
Presentation Type
Paper Presentation in a Themed Session
Theme
KEYWORDS
Artificial Intelligence, Design Education, Semiotics, Text-to-Image, Prompt
