Fostering Sustainability in the Early Stages of the Architectural Design process: a Creative Exploration of AI Generative Models

The field of architecture is experiencing transformative changes with the rise of Artificial Intelligence (AI). This study investigates the use of generative models like Large Language Models (LLM) and Generative Diffusion Models (GDM) in architectural design, focusing on sustainability. Utilizing the concept of 'active human agency', the research evaluates tools like DALL-E 2 (Bing) and ChatGPT (GPT-4) for creating environmentally responsive references in the early phases of the design process. Employing an explorative and qualitative methodology, the investigation includes architectural characteristics of climatic archetypes and concepts related to architecture-biology, applied to different environmental contexts. Initial findings reveal the AI potential in creating environmentally responsive references, with certain limitations in specific interactions and interpretations. The conclusion emphasizes these tools as collaborative aids in early design stages, and underscores the importance of 'active human agency' for meaningful, responsible results, contributing to sustainability in early architectural design processes.