Home » Excessive Resolution: Artificial Intelligence and Machine Learning in Architectural Design
Designers have been using computer-based tools for design and fabrication for almost one generation. In the course of the last 30 years we have learned that computers can help us draw and build new forms of unprecedented complexity, and we have also discovered that, using CAD-CAM technologies, we can massproduce variations at no extra cost: that is already history—the history of the first digital turn in architecture. Today, however, more and more powerful computational tools can do way more than that. Computers, oddly, seem now capable of solving some design problems on their own—sometimes problems we could not solve in any other way. Twenty years ago we thought computers were machines for making things; today we find out they are even more indispensable as machines for thinking. That’s one reason why many, including many design professionals, are now so excited about Artificial Intelligence (AI). The term itself, however, is far from new: it was already popular in the 1950s and ’60s, when computer scientists thought that Artificial Intelligence should imitate the logic of the human mind—that computers should “think” in the same way we do. Today, to the contrary, it is increasingly evident that computers can solve some hitherto impervious categories of problems precisely because they follow their own, quite special, logic: a logic that is different from ours. And already it appears that this new, post-human (or, simply, nonhuman) logic vastly outsmarts ours in many cases.
The main difference between the way we think and the way computers solve problems is that our own brain was never hard-wired for big data. When we have to deal with too many facts and figures, we must inevitably drop some—or compress them into shorter notations we can more easily work with. Most classical science was a means to that end. Geometry and mathematics—calculus in particular— are stupendous data-compression technologies. They allow us to forget too many details we could never remember anyway, so we can focus on the essentials. Sorting is another trick of our trade. As we could never find one name in a random list of 1 million, we invest a lot of work in sorting that list before we use it: if the names are ordered alphabetically, for example, as in a telephone directory, we can aim directly at the name we are looking for without having to read all the names in the list, which would take forever. Yet that’s exactly what computers do: since they can scan any huge sequence of letters and numbers in almost no time, they do not need to keep anything sorted in any particular order. Take alphabetic sorting as a metaphor for the way we think in general: we put things in certain places so we know where they are when we need them; we also sort things and ideas to make some sense of the world. But computers need none of that: unlike us, they can search without sorting. Computers are not in the business of investigating the meaning of life either.