… so much corn, so much cloth, so much everything, that things will be practically without price. There will be no poverty. All work will be done by living machines. Everybody will be free from worry and liberated from the degradation of labor. Everybody will live only to perfect himself.
Karel Capek, Rossum’s Universal Robots
Computer-aided design cannot occur without machine intelligence—and would be dangerous without it. In our era, however, most people have serious misgivings about the feasibility and more importantly, the desirability of attributing the actions of a machine to intelligent behavior. These people generally distrust the concept of machines that approach (and thus why not pass?) our own human intelligence. In our culture an intelligent machine is immediately assumed to be a bad machine. As soon as intelligence is ascribed to the artificial, some people believe that the artifact will become evil and strip us of our humanistic values. Or, like the great gazelle and the water buffalo, we will be placed on reserves to be pampered by a ruling class of automata.
Why ask a machine to learn, to understand, to associate courses with goals, to be self-improving, to be ethical—in short, to be intelligent?
The answer is the underlying postulate of an architecture machine. A design machine must have an artificial intelligence because any design procedure, set of rules, or truism is tenuous, if not subversive, when used out of context or regardless of context. It follows that a mechanism must recognize and understand the context before carrying out an operation. Therefore, a machine must be able to discern changes in meaning brought about by changes in context, hence, be intelligent (A. Johnson, 1969c). And to do this, it must have a sophisticated set of sensors, effectors, and processors to view the real world directly and indirectly.
Intelligence is a behavior. It implies the capacity to add to, delete from, and use stored information. What makes this behavior unique and particularly difficult to emulate in machines is its extreme dependence on context: time, locality, culture, mood, and so forth. For example, the meaning of a literary metaphor is conveyed through context; assessment of such meaning is an intelligent act. A metaphor in a novel characterizes the time and culture in which it was written.
One test for machine intelligence, though not necessarily machine maturity, wisdom, or knowledge, is the machine’s ability to appreciate a joke. The punch line of a joke is an about-face in context; as humans we exhibit an intelligence by tracing back through the previous metaphors, and we derive pleasure from the new and surprising meanings brought on by the shift in context. People of different cultures have difficulty understanding each other’s jokes.
Some architects might propose that machines cannot design unless they can think, cannot think unless they want, and cannot want unless they have bodies; and, since they do not have bodies, they therefore cannot want; thus cannot think, thus cannot design: quod erat demonstrandum. This argument, however, is usually emotional rather than logical. Nonetheless, the reader must recognize, if he is an “artificial intelligence” enthusiast, that intelligent machines do not exist today and that theories of machine intelligence at this time can at best be substantiated with such an example as a computer playing a superb game of checkers (Samuel, 1967) and a good game of chess (Greenblatt, et al., 1967). Furthermore, architecture, unlike a game of checkers with fixed rules and a fixed number of pieces, and much like a joke, determined by context, is the croquet game in Alice in Wonderland, where the Queen of Hearts (society, technology, economics) keeps changing the rules.
In the past when only humans were involved in the design process, the absence of resolute rules was not critical. Being an adaptable species, we have been able to treat each problem as a new situation, a new context. But machines at this point in time are not very adaptable and are prone to encourage repetition in process and repetition in product. The result is often embodied in a simple procedure that is computerized, used over and over, and then proves to be immaterial, irrelevant, and undesirable.
Ironically, though it is now difficult for a machine to have adaptable methods, machines can be employed in a manner that treats pieces of information individually and in detail. Imagine a machine that can respond to local situations (a family that moves, a residence that is expanded, an income that decreases). It could report on and concern itself specifically with the unique and the exceptional. It would concentrate on the particulars, “for particulars, as everyone knows, make for virtue and happiness; generalities are intellectually necessary evils” (Huxley, 1939). Human designers cannot do this; they cannot accommodate the particular, instead they accommodate the general. “He (the architect) is forced to proceed in this way because the effectuation of planning requires rules of general applicability and because watching each sparrow is too troublesome for any but God” (Harris, 1967a).
Consider a beach formed of millions of pebbles; each has a specific color, shape, and texture. A discrete pebble could have characteristics, for example, black, sharp, hard. At the same time the beach might be generally described as beige, rolling, soft. Humans learn particulars and remember generalities, study the specific and act on the general, and in this case the general conflicts with the particular. The problem is therefore twofold: first, architects cannot handle large-scale problems (the beaches) for they are too complex; second, architects ignore small-scale problems (the pebbles) for they are too particular and individual. Architects do not appear to be well trained to look at the whole urban scene; nor are they apparently skilled at observing the needs of the particular, the family, the individual. As a result “less than 5 percent of the housing built in the United States and less than 1 percent of the urban environment is exposed to the skills of the design professions” (Eberhard, 1968b).
But architects do handle “building-size” problems, a kind of concern that too often competes with general goals and at the same time couches personal needs in antihuman structures. The result is an urban monumentalism that, through default, we have had foisted upon us by opulent, self-important institutions (that can at least control large chunks of the beach); our period is a period of neo-Hancockism and post-Prudentialism. The cause is the distinct maneuverability gap that exists between the scale of the mass and the scale of the individual, the scale of the city and the scale of the room.
Because of this, an environmental humanism might only be attainable in cooperation with machines that have been thought to be inhuman devices but in fact are devices that can respond intelligently to the tiny, individual, constantly changing bits of information that reflect the identity of each urbanite as well as the coherence of the city. These devices need the adaptability of humans and the specificity of present-day machines. They must recognize general shifts in context as well as particular changes in need and desire.
The following chapters have a “pebble-prejudice.” Most computer-oriented tasks today are the opposite: the efficient transportation system, the public open space, the flow of goods and money. Our bias toward localized information implies two directions for the proposed relationship between designer and machine. The first is a “do-it-yourselfism,” where, as in the Marshall McLuhan (1965) automation circuit, consumer becomes producer and dweller becomes designer. Machines located in homes could permit each resident to project and overlay his architectural needs upon the changing framework of the city. The same machine might report the number of shopping days before Christmas as well as alert the inhabitant to potential transformations of his habitat.
The second direction presupposes the architect to be the prime interpreter between physical form and human needs. The machine’s role in this case is to exhibit alternatives, discern incompatibilities, make suggestions, and oversee the urban rights of individuals. In the nature of a public service the architect-machine partnership would perform, to the utmost of each actor’s respective design intelligence, the perpetual iteration between form and criteria. The two directions are not exclusive; their joint enterprise is actually one.
What needs to be articulated, regardless of the format of the man-machine relationship, is the goal of humanism through machines. The question is not one of rationalism versus vitality (Juenger, 1949), nor the degree of rationalism (Ellen Berkeley, 1968), nor the castration of spirit by technique (Mumford, 1967). The concern is to avoid dehumanizing a process whose aim is definitely humanization. It is simply untrue that “unpleasant as it may be to contemplate, what probably will come to be valued is that which the computer can cope with—that is, only certain kinds of solutions to social problems” (Michael, 1963). We will attempt to disprove the pessimism of such comments. To do this, we will ask machines not only to problem-solve but also to problem-worry (S. Anderson, 1966).
In this book, there is no distinction between hardware and software, between special-purpose computers and general-purpose computers. The lines between what has been done, what can be done, and what might be done are all fuzzy. Our interest is simply to preface and to encourage a machine intelligence that stimulates a design for the good life and will allow for a full set of self-improving methods. We are talking about a symbiosis that is a cohabitation of two intelligent species.