Between Accident and Control: Contrasting Traditions of Computational Design

Daniel Cardoso-Llach

Since architects began to flirt with computers in the 1960s, debates about the role of computation in architecture have often been framed antagonistically – as arenas for technophobes and technophiles to clash, each staking a claim on the unique value, or promise, of their respective practices. This dichotomy is tempting. On the one hand, images of automated design systems – offering creative freedom, managerial efficiency, or ‘personalized’ design solutions – abound in architecture’s six-decades romance with computation. Seductive and often reductive, these images outlined the contours of a computationally augmented practice of architecture, and captured the imagination of many architects in academia and industry, effectively ushering an entire academic sub-field.

Fig. 1: A reconstruction of Ivan Sutherland’s 1964 “Sketchpad” system, the first interactive graphics system, sits alongside Blooms Day, a 1969 generative painting by George Stiny, in Designing the Computational Image, Imagining Computational Design, an exhibition curated by Daniel Cardoso Llach in 2017 at the Miller Gallery, Pittsburgh.

Computers were greeted more cautiously, on the other hand, by those architects who saw them either as means of producing ineffective simulacra, or as a dangerously transformative force in architecture. For some in this group, computer screens simply failed to approximate the plasticity of sketches drawn by hand, or the tactility of a physical model; for others – aware of the social and organizational tensions introduced by technologies – computers conjured (not entirely unjustified) pre-industrial fears of automation, de-skilling and alienation.

A sort of bargain was thus struck across these seemingly distant intellectual territories: the idea that the computer is ‘just another tool’ that architects can utilize in their design process – another paintbrush or easel in the architect’s atelier. Frequently deployed in studio reviews, ‘think pieces’ and course syllabi, this concept has become part of many architects’ conventional wisdom, configuring a comfortable middle ground where computational ideas and techniques can co-exist with (albeit at a safe distance from) architecture’s hard core.

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[1] Cardoso Llach, Daniel, Builders of the Vision: Software and the Imagination of Design. London: Routledge, 2015.
[2] Sutherland, Ivan, “Structure in Drawing and the Hidden-Surface Problem,” in Reflections on Computer Aids to Design and Architecture, edited by Nicholas Negroponte, 73-77 (excerpt not including the “hidden surface problem”). New York, 1975. I discuss the question of structure in the computational image in Cardoso Llach, Daniel, “Architecture and the Structured Image: Software Simulations as Infrastructures for Building Production” in Operative Artifacts: Imagery in the Age of Modeling, Sabine Ammon, Inge Hindterwaldner, eds. Springer, 2017.
[3] For a discussion of the notion of software as theory of design, see Cardoso Llach, Daniel, “Software Comes to Matter: Towards a Material History of Computational Design,” DesignIssues 31, no. 3, Summer 2015: 41–55. https://doi.org/10.1162/DESI_a_00337.
[4] “Algorithmic Aesthetics” is the title of a 1978 book by George Stiny and James Gips. “Algorithmic Aesthetics: Computer Models for Criticism and Design in the Arts,” Algorithmic Aesthetics,1978, http://www.algorithmicaesthetics.org/. I borrow this title here to refer to works that include Stiny and Gips’ work as well as the work of others.
[5] See Bense, Max. “The project of generative aesthetics”, 1965.
[6] George Stiny and James Gips, “Shape Grammars and the Generative Specification of Painting and Sculpture” in Segmentation of Buildings for 3D Generalisation. Proceedings of the Workshop on Generalisation and Multiple Representation, Leicester, 1971.
[7] For a discussion on the new forms of authorial agency emerging as a result of machine learning and data, see Cardoso Llach, Daniel, “Data as Interface: The Poetics of Machine Learning in Design,” in Machine Learning. Medien, Infrastrukturen Und Technologien Der Künstlichen Intelligenz (Machine Learning. Media, Infrastructures and Technologies of Artificial Intelligence). Transcript, 2018.
[8] To a significant extent, these cultures are traceable to the 1990s work of the Aesthetics and Computation Group at the MIT MediaLab. Among these, the community of creative coders around Processing is particularly strong. Processing is a computer language derived from Java designed to simplify complex aspects of programming in order to making it accessible to visual artists and designers across fields. See, for example, Casey Reas and Ben Fry, Processing: A Programming Handbook for Visual Designers and Artists, Second Edition, Cambridge, Massachusetts: MIT Press, 2015.
[9] Transactions of the Martin Centre for Architectural and Urban Studies, University of Cambridge, Volume 4, 1980. Steadman, Phil and Janet Owers (ed.)
[10] See James Wines’ essay, pp 38-49 in this volume.
[11] Tekton also registers architecture’s fundamental concern with material articulation.
[12] For a detailed discussion of these questions, see Cardoso Llach, Builders of the Vision, op cit.
[13] Ibid.
[14] Peter Galison has usefully observed that in the aftermath of the Second World War, computer simulations allowed scientists of different fields to collaborate, becoming a kind of “trading zone” for researchers without a shared disciplinary background. Galison, Peter, Image and Logic: A Material Culture of Microphysics, Chicago: University of Chicago Press, 1997.
[15] For an extended discussion of this project see Cardoso Llach, Daniel, “Tracing Design Ecologies,” in Digital STS Handbook, ed. Janet Vertesi and David Ribes, Princeton University Press, 2017, and Daniel Cardoso Llach, “Visualizing BIM Coordination,” 2012, on vimeo.com: https://vimeo.com/51693897