Designing is an inherently generative process. Instinctively—or perhaps by training, as this is what I was taught to do in architecture school—designers are almost immediately drawn to put together something that they think addresses the problem at hand. These prototypes are excellent at revealing what works and what doesn’t in order to attain the desired outcomes, and this is a method—we were told—that even proto-designers, such as tool makers and artisans used, before scaled drawings and modelling technology were ubiquitous. They made things, put them to work, and if they weren’t good enough, they would adjust them in the next version. This is how they built up know-how, and ultimately advanced their craft. The ‘trick’ is to do this enough. To iterate between generating and testing so you assess all the possibilities in the spectrum and settle for the best one. But what if a better alternative is still out there? What if, because of contextual constraints, time limitations or a creative rough patch, that better alternative has escaped the designer’s creative capabilities or imagination and never comes to be?
Artistic production could also be considered generative in nature, and for similar reasons: when the goal is to express an artistic idea and convey a sensorial experience, exhaustive search and careful refinement are the methods of the trade. However, one notable difference between designed artefacts and works of art lies in the fact that the former always have a practical purpose that supersedes the artistic character of the artefact. The task of designers is twofold, as it requires focus not only on addressing the practical problem at hand, but also on how the solution provided will impact the environment where it will be deployed. This is especially true for the design of physical objects meant to be looked at, inhabited, or interacted with (for more on this see Lawson 2006), as they will have aesthetic and environmental implications deeply related to cultural and contextual issues, which are unpredictable, and can sometimes override the value of the intended practical solution.
The fundamental value of generation in creative disciplines, such as visual arts and design, is that it enables creative exploration. Sometimes called ‘looking for inspiration’, this process involves the observation of artefacts—either pre-existing or purposefully generated—in search of elements and/or characteristics perceived as conducive to satisfying the expectations that the new artefact is meant to address. In traditional design and arts, the ability that a creator has to to generate and explore a landscape of alternatives derives from their talent, and is what supports the heroic narrative behind creativity. Generative systems have been used for this purpose by designers, artists and makers since the times of Aristotle (for more on this see Mitchell 1977). Generally speaking generative systems can be described as sets of building blocks and explicit rules that are used to generate new things. The rules determine how, when and for how long the building blocks are manipulated, aggregated, deleted, decomposed and/or recomposed, resulting in a new artefact. Classic examples of generative systems are John Conway’s Game of Life and Stiny and Gips’ Shape Grammars (the latter are actually the foundations for a whole family of generative systems).
Setting up a generative system is not an easy task. It requires thorough understanding of the components and rules, and in turn designers and artists have to partially give up control over their creative process, as what comes out of the system is often hard to predict.
The upside of this compromise is that through the use of generative systems, it becomes possible to explore lineages of alternatives, rather than being limited to those one can imagine directly.
Additionally, the knowledge of building blocks and rules developed through the definition of a generative system enables the quantitative evaluation of characteristics of the artefacts it produces —e.g. the statistical distribution of individual building blocks and the detection of patterns or motifs, just to name a few— which can potentially lead to the development of methods to guide the exploration of vast spaces of creative possibilities.
For these reasons we believe that generative systems—specifically digital ones—are a well suited method for creative exploration and to search for innovation in design and visual arts (for more on this see this article).
Growing 3D Prints
For the past year we have been experimenting with a generative system that uses the constraints of fused deposition modelling (FDM) 3D printing as the conceptual basis for a 2D bio-inspired dynamic life simulation, which is then used to generate 3D printable objects. Growing 3D prints is not a fully fledged design driven generative system, as the objects it produces are not necessarily meant to address practical problems. However, it enables us to produce a vast landscape of alternatives where we can search for the ones that best take care of conflicting goals: printability and aesthetic interest, where the former is purely practical, and is determined by the limitations of the manufacturing process of choice, and the latter is bound by ideas of style, complexity, pattern association and other subjective attributes. Our aim is to explore the tension between the artistic and practical attributes of physical objects.