Call and Response - Error and Precision
Error is good, and precision is a technical myth.
From the hatch tests we drew last week, it is clear that this instrument is most precise when both the X and Y axes are moving together. Diagonal lines, in this case at a 45 degree angle, are drawn on paper with the greatest fidelity to the coded input drawn in CAD space. This makes me think that this instrument and I have some similarities, gravitating towards drawings created in the plan oblique, or axonometric projections.
As a genre of engineering drawing, “parallel projection solves certain problems of representation. Parallel projection shows a three-dimensional image whilst being measurable, making it an easier working drawing than a perspective, for example.” (Lucas) While I am at odds with Lucas’ choice of words like “solves,” “problems,” and “easier”, it is true that as an invention, precision is a key feature of axonometric drawing. In axons, where a plan is rotated 45 degrees and all vertical distances are projected from it, “the deformation of angles is restricted to one plane, and measurements of length retain their proportions.” (Lucas)
On the left, a plan oblique (or axonometric projection). On the right, an isometric projection. (From “Drawing Parallels”, Lucas, 2019)
The line in a drawing might simultaneously represent an edge, a texture, or a thread. These lines form boundaries on paper, and by “establishing a series of such territories, forms can begin to emerge, be the lines fluid or ruled, the territories open or bounded.” (Lucas)
In our shared language and medium of ruled lines, the instrument creates edges and textures all the same. Material is what separates our workflows, as lines drafted in CAD model space are translated into graphite on paper.
Etching of a needlepoint and razor’s edge under Robert Hooke’s microscope, from “Micrographia” (1665)
“As in geometry, the most natural way of beginning is from a mathematical point.” - Robert Hooke
The father of microscopy, Hooke’s famous etchings of a needlepoint and razor’s edge viewed under a microscope point to this myth of precision - the sharpest point is rendered blunt and irregular, jagged and wide. Likewise, a point in a drawing that I draft in CAD is material-less, unsized, and relatively un-located. A point drawn by my instrument is grey and shiny, the size of the lead that it holds, and is placed on sheet of paper - born from material and machine limits.
One of the most insidious effects of the digitization of architectural production has been the foundational use of “a degree of precision that is always redundant to the process of materialization.” (Hughes) The infinite scroll of CAD model space creates an absurd precision, which we only acknowledge through the invention of “allowable tolerance,” a sheepish admittance that we have gone a few decimal places too far. Tolerance, however, does not absolve the architectural expectation of truth.
Error and precision are deeply questioned in the history of science (significant figures), critiqued through the role of instrumentalism within technology studies (machine learning), and viewed through the lens of approximation and inference in biology (biological models); however, “architecture’s particular addiction remains largely uninterrogated.” (Hughes) Precision is a practice of dominance, invented with the purpose of error control, that has now strayed beyond its invention in architecture through the removal of ornament, rejection of organic material, and the introduction of standards and specifications that aim for uniformity and efficiency in building.
I question the expectation of relatively truthful representations drawn by my instrument. What is compelling about drawing together is when our drawings look different, when “errors” are present on paper (like when lines start to pair up together when it only moves along one axis). The contribution of materiality and machine-limited translation are what it adds to our collaboration - it makes assumptions about tolerance and relative truthfulness based on the limits of its movement, size, and grain. It operates on a finite scale, a coordinate system contained by an aluminum frame. This limit produces “errors” between what I draw and what it draws, and this is the exciting part of our collaboration. I cannot expect an exact representation of the lines I placed in CAD, the word representation itself implies a bit of exciting wiggle room, artist/machine influence, and productive error. Errors are useful for artists, machines, and architects and should not be avoided, but rather embraced. Far more interesting is the expectation of error within a rigorous set of boundaries; French theorist Paul Virilio has “convincingly reasoned for the positive guidance of accident or error, arguing that in a modern society, the artist must use such accidents to guard against the hegemony of technology,” (Foote).
Errors mandate close-looking and investigations between method and material. In this specific collaboration, they provide an excuse to spend time looking at lines, the varying pressure of graphite on paper, and understanding what the instrument decides is unimportant. This instrument and I both value the rigor and rules of parallel projection, not the implied embodiment of precision. Shifting scales between infinite space and material production distills the impact of lines with thickness, and instructions modified.
Two drawings executed by the Tiny-Z, one at 1:1 scale to a drawing produced in CAD, and one half that size.
References:
Foote, Jonathan. Review of Architecture of Error: Matter, Measure, and the Misadventures of Precision, by Francesca Hughes. JAE Online. February 27, 2016.
Hughes, Francesca. The Architecture of Error: Matter, Measure, and the Misadventures of Precision, 2014.
Lucas, Ray. Drawing Parallels: Knowledge Production in Axonometric, Isometric and Oblique Drawings, 2019.
Relevant Works:
Chard, Nat. “MACHINES FOR INDETERMINATE ARCHITECTURE.” Perspecta, vol. 46, [Yale University, School of Architecture, The MIT Press], 2013, pp. 358–69,