Discussion & Future Work
First, some limitations and shortcomings of this work should be addressed (which might also suggest paths for future work). Notably, there is a U.S. American (and specifically East Coast) bias among my interview subjects, with New York City, Cambridge/Boston, and Pittsburgh especially overrepresented relative to the rest of the world. In addition, fully two-thirds of my interview subjects identify as male, a disparity I would love to see reversed. In addition to striving for more egalitarian representation, it is likely that further examples of positive deviance are to be found among groups that have traditionally been marginalized. The goal would not be to co-opt their practices, but to amplify those voices, and to bring about more diverse, thoughtful work toward the creation of desirable futures.
Technically, the software prototypes among my case studies are myopic with respect to the graphic user interface. Again, with my background as web developer, working within the computer screen is my comfort zone. However, there is also ample room for work taking a more embodied approach, through physical computing, virtual or augmented reality, and embedded interfaces (for just a few examples). I believe that software as research tools within those paradigms would help to further nuance the components of the framework, providing different computational perspectives on and approaches to generating, simulating, and interrogating.
In terms of future work, I see this framework as having great potential in pedagogy. While I have depicted computational design at various points as a set of overlapping, neighboring practices and approaches to design, borrowing heavily from other fields, it is also the case that (for example) Computational Design is a singular track in the School of Architecture at Carnegie Mellon University. Two hours east of here, at Penn State University, is the Stuckeman Center for Design Computing. MIT, meanwhile, houses the Design and Computation Group within their architecture school. If, in these examples (among many others) from the academy, it is to be presented as a cohesive area of study, I propose that this framework provides a high-level overview of productive approaches to computational design. Irrespective of technological shifts and advances in the coming decades, I see this framework as remaining relevant as an argument in favor of unique human agency in the tide of advancing computational efficiency (especially in the age of artificial intelligence and machine learning). The evidence I have offered in this thesis suggests that it has viability at both the graduate and advanced undergraduate levels in design studios to provide a framing of the ‘how’ and ‘why’ of computational design. Devising a seminar syllabus, a design project or series of projects, or using the framework to restructure an existing course would all be viable means of testing the efficacy of the framework in computational design education. Concretely, a studio instructor could strive to self-consciously instill a mindset of generating and simulating in their students toward the formulation of design questions and the iteration and refinement of design interventions, all the while maintaining an interrogative stance toward the student’s materials and tools. In doing so, this will also engender a mindset of critical questioning as well as openness to shaping and exploring spaces of possibility.
Another direction for the framework lies outside of the academy and traditional design learning contexts. Architecture is an intellectually open but practically closed field, with a grueling internship and licensing process and appalling representation of women and minorities among its professional ranks. Computational design, as an area of study typically housed within architecture schools, suffers from many of the same problems (again, as does this thesis research). To address this, there must be opportunities outside of traditional universities and academic programs. The two events described in the introduction, the computational design symposium and the Cybernetics Conference, were each affiliated with various institutions, but opened doors to the wider public. In addition, each demonstrated impressively diverse representation (both demographically and according to discipline). Other organizations, such as the School for Poetic Computation and Learning Gardens, a community of “self-organized learning groups,”1 provide promising alternatives to the university classroom or design studio as well as to for-profit programs aimed squarely at career placement. As the computational design framework outlined here is itself critical and projective, it would be appropriate for its pedagogical embodiment to also chart a new educational path forward.
1. Learning Gardens, http://learning-gardens.co/. Accessed December 1, 2017. ↩