Re_Imaged: Reimaging architecture through artificially intelligent generated images

Artificial Intelligence is a machine learning technique that exists everywhere in our day-to-day life. From a simple Google search that provides answers to any questions, to autocorrect suggestions provided while writing emails, we encounter AI in every next phase of our life. Humans have developed an invisible trust in AI that remains unrecognized.

Artificial intelligence (AI) development in architecture has been a protracted and intriguing process. Recent advances in text-to-image generating software powered by AI have proven to be an efficient tool for architects to visualize their designs with a different perspective and enhance the thinking process. However, the lack of the tool's ability to capture the designer's integrity has shown the requirement for human involvement.

This thesis claims that human decision-making skills remain crucial despite AI-augmented design's benefits. By conducting a comparative analysis between human-developed architecture and AI-augmented designs through the process of AI text-to-image generating tool Stable Diffusion, the thesis argues that human brain involvement is necessary due to the lack of Stable Diffusion's ability to understand architectural drawings and elements, the ability to representing architectural depth through spaces and emotions, and its inadequate learning from the past design experiences.