The AI plot twist
AI has been advancing quietly for years in the progressive segment of the architecture and design industry. Machine learning libraries have been integrated into software like Revit, Rhino-Grasshopper, and standalone applications, offering functionalities such as machine learning-based optimization and efficient layout design. This led to heightened anticipation for the integration of powerful analytical methods and tools based on ML algorithms into traditional 3D environments. However, AI had a surprising “plot twist” or an “unexpected move” with the emergence of text-to-image platforms like Midjourney or Stable Diffusion, based on deep generative models (diffusion models). Such a technology – capable of registering the latent correlation in complex data and somehow closer to the imaginative processes of the human mind – unleashed an unexpected, but powerful wave of creativity, emphasizing the ideation phase of design. We can metaphorically state that while we were anticipating the AI to fuel the left side of our brain, it unexpectedly ignited the right side, the realm of creativity.
After this first revolution a new direction is emerging and is about giving designers a deeper control of tools and relative output. Parametric AI, Sketch to Render, Sketch to 3D and novel layout optimization tools are the next frontiers of the AI Aided Design, poised to have an enormous impact on the profession and education alike. These advancements will enable designers to wield AI technology as a powerful tool, providing them with enhanced control and facilitating the realization of their creative visions.
The creative industries have always been at the forefront of applying and adapting new technologies.
While robotic fabrication has been used in industry for decades, the growing interest of architects and designers in large-scale robotic fabrication has led to the adaptation of “creative” computational design tools to facilitate individualized design and fabrication. Today, roboticists with creative backgrounds are shaping robotic manufacturing in a variety of high-tech fields.
This ability to look beyond the boundaries of one’s own industry is not the kind of creativity that AI is taking over – interdisciplinarity is not just about deriving new connections from existing data, but also about communicating between different actors, understanding complex constraints, and often implementing a minimum viable product at a stage where these constraints are not yet fully defined.
This is a particular strength of the creative industries – and something that can benefit greatly from AI technology. Today, architects and designers use visual programming to more easily translate their concepts into algorithms. In the future, AI will be able to further abstract this process so that MVPs can be generated, implemented, and tested more efficiently, taking care of the basic features so that designers can focus on the innovative aspects. At this stage, the use of AI does not mean that we have to give up our creativity, but that we will apply creativity at a more abstract level than before.
Evolving technologies such as AI will continue to disrupt existing fields, possibly pushing some out of the mainstream and into a niche, just as industrialization did for craftspeople. As in the past, the creative industries will need to adapt, innovate and, above all, improvise – something we have always been very good at.