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Robot Architects

Published onApr 23, 2021
Robot Architects

Rather than “problem-solving,” I characterized the design process as “problem-worrying.” I suggested that architecture is concerned with structuring man’s environment to facilitate the achievement of human purposes (intellectual, psychological and utilitarian) where those purposes are incompletely known and cannot be extrapolated from what is given in the situation. Rather, human purposes are altered by the very environment that is created to facilitate them. The structuring of the environment must be accomplished, then, through the exercise of tentative foresight and the critical examination of that foresight and the actions to which it leads. According to this description, neither the human purposes nor the architect’s methods are fully known in advance. Consequently, if this interpretation of the architectural problem situation is accepted, any problem-solving technique that relies on explicit problem definition, on distinct goal-orientation, on data collection, or even on non-adaptive algorithms will distort the design process and the human purposes involved.

Stanford Anderson, “Problem-Solving and Problem-Worrying”

It is interesting to ponder what a human designer must do or the behavior he must exhibit in order to be a good architect, a talented architect, an ethical architect—not, perforce, a successful architect. We know that he must somehow contribute and promote physical environments that both house and stimulate the good life. But we do not know much about the good life; it has no “utility function” and cannot be optimized. We know that he must have an understanding of and ease with physical form. But we do not know how our own cognitive processes visualize shape and geometry. We know that he must interpret human needs and desires. But we do not know how to acquire these needs and desires.

What probably distinguishes a talented, competent designer is his ability both to provide and to provide for missing information. Any environmental design task is characterized by an astounding amount of unavailable or indeterminate information. Part of the design process is, in effect, the procurement of this information. Some is gathered by doing research in the preliminary design stages. Some is obtained through experience, overlaying and applying a seasoned wisdom. Other chunks of information are gained through prediction, induction, and guesswork. Finally some information is handled randomly, playfully, whimsically, personally.

It is reasonable to assume that the presence of machines, of automation in general, will provide for some of the omitted and difficult-to-acquire information. However, it would appear foolish to suppose that, when machines know how to design, there will be no missing information or that a single designer can give the machine all that it needs. Consequently, we, the Architecture Machine Group at M.I.T., are embarking on the construction of a machine that can work with missing information. To do this, an architecture machine must understand our metaphors, must solicit information on its own, must acquire experiences, must talk to a wide variety of people, must improve over time, and must be intelligent. It must recognize context, particularly changes in goals and changes in meaning brought about by changes in context.

The Jaquet-Droz Writer (circa 1774). The little boy is 28 inches tall, carved from wood, and composed of a very complicated mechanism which still works. It has carefully written, “I do not think, therefore I will never be.” (Photograph courtesy of Editions du Griffon, automaton in Neuchâtel Museum)

“And it will serve us right” (Asimov, 1969). (Reprinted from “Psychology Today,” magazine, April 1969, © Communications/Research/Machines, Inc. Photograph by Stephen Wells)

In contrast, consider for a moment a society of designers built upon machine aides that cannot evolve, self-improve, and most importantly, cannot discern shifts in context. These machines would do only the dull ignoble tasks, and they would do these tasks employing only the procedures and the information designers explicitly give them. These devices, for example, could indiscriminately optimize partial information and generate simplistic solutions that minimize conflicts among irrelevant criteria. Furthermore, since no learning is permitted in our not-so-hypothetical situation, these machines would have the built-in prejudices and “default options” of their creators. These would be unethical robots.

Unfortunately most researchers seem to be opting for this condition. As a result, many computer-aided design studies are relevant only insofar as they present more fashionable and faster ways of doing what designers already do. And since what designers already do does not seem to work, we will get inbred methods of work that will make bad architecture, unresponsive architecture, even more prolific.

I therefore propose that we, architects and computer scientists, take advantage of the professional iconoclasms that exist in our day—a day of evolutionary revolution; that we build machines equipped with at least those devices that humans employ to design. Let us build machines that can learn, can grope, and can fumble, machines that will be architectural partners, architecture machines.


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