The most commonly held and influential idea about design is that it’s the art of bringing essentially unrelated parts into a “composition” or an “assembly”. The funny thing is, from a scientific point of view, this idea is entirely wrong. A much better idea about design is that it’s the transformation of one whole into another whole. Not only is this definition more accurate, it’s also crucial for achieving an adaptive design.

Let’s talk about the important implications of this distinction between assembly and transformation.

Why is it scientifically wrong to say that design is the “composition” of essentially unrelated elements? Because nothing that works as a complete system is really “essentially unrelated” — though the sciences used to operate more or less successfully from that abstract premise, and much of technology still does. By contrast, the sciences of the last century have taught us more and more about the essential inter-relatedness of the Universe, from the largest scales of the space-time continuum, to the push-pull world of the quantum. In the biological sciences, we’ve come to understand the multi-layered, historical interdependence of systems, especially evident in the web-like relationships of ecological systems. Wherever we look in nature, we find vast and intricate networks of connections.

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Today’s designers seem to love using new ideas coming from science. They embrace them as analogies, metaphors, and in a few cases, tools to generate startling new designs. (Computer algorithms and spline shapes are a good recent example of the latter.) But metaphors about the complexity of the city and its adaptive structures are not the same thing as the actual complexity of the city.

The trouble is, this confusion can produce disastrous results. It can even contribute to the slow collapse of an entire civilization.

We might think that the difference between metaphor and reality is so obvious that it’s hardly worth mentioning. And yet, such confusion pervades the design world today, and spreads from there into the general culture. It plays a key role in the delusional expectation that metaphors will create reality. Psychiatrists speak of this as an actual disorder known as “magical thinking”: if our symbols are good enough, then reality will follow.

In the hands of designers, this is very dangerous stuff. We see it at work in the failed iconic buildings that were sure to create economic development, or urban vitality, or greater quality of life purely because of a futuristic image. We see it also in the many “tokenistic” sustainability features (wind turbines, etc.) of other iconic new buildings whose actual performance in post-evaluation studies is woefully poor.

From the perspective of design methodology, this phenomenon is an interesting and important design problem in its own right. We recognize it as a fundamental weakness of human thought, and need to adjust our design methodologies accordingly. In this process, the methodologies and insights of a humane science, applied by literate designers, can be invaluable. Distinguishing physical from metaphorical complexity clarifies a presently confused and unsustainable situation, and can help us out of it (the ultimate aim of any science, and any philosophy).

The topics of urbanism, architecture, product design, environmental design, sustainability, and complexity in science are all tightly interrelated. Humans “design” with much the same aim toward which nature “designs” — both aim to increase the complexity of a system so that it works “better”. “Better” in this sense means more stable, more diverse, and more capable of maintaining an organized state — like the health of an organism. We learn from the structures and processes by which nature designs, so that we can also create and sustain these more organized states.

Some scientists shy away from the notion that nature “aims” for anything. But this begs the question: are we not part of nature, and do we not “aim” for something in our own designs, and in the other parts of our life (e.g. seeking our own health and wellbeing)? Then we must accept “aim” as a characteristic of at least some part of nature. Otherwise, we severely hobble the usefulness of the scientific tradition as a relevant tool for designers. (Indeed, we would set ourselves on a very dangerous philosophical path: in effect, rendering the very idea of intelligence — human or otherwise — as meaningless!)

Traditional city fabric evolved over generations as an extension of our own biology, thus representing an application of a kind of “collective intelligence” due to the system, not of any individual. Traditional Islamic urbanism, by Mustapha Ben Hamouche.

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Looked at in a certain way, the human environment is a kind of massive delivery system for critically useful information.

It gives us information about obvious concerns, like where we are, where we need to go, where we might find food, where to look out for dangers (speeding cars, unsafe drop-offs, etc.) and many other things. And more subtly but importantly, it tells us where we will most likely feel safe and well.

It now seems that when we find an environment beautiful, a form of integrated higher-level information telling us something important about the structure of the place, it is likely that it’s doing something positive for us. A grove of delicious ripe fruit is likely to be much more beautiful than one of diseased trees and rotted fruit — and that’s no coincidence. Our aesthetic discernments have evolved as sophisticated assessments of what is likely to be in our best interest as organisms.

Put simply, we have a natural hunger for beauty — because we have a natural hunger for the deeper, biologically relevant characteristics of places and things that we find beautiful. This works through information input and our neurophysiological system, which developed to process and interpret information and to discern its relevant and often hidden meaning beneath the obvious.

There is also evidence that we strongly prefer information grouped into patterns that we can mentally manage most easily — as the psychologist George A. Miller showed, we seem to prefer “chunks” of two and three, and, combinations of these, up to about seven or so. We also seem to have a natural affinity for the complex patterns that plants and other natural structures exhibit. This is one reason that we have an instinctive affinity for certain biological patterns, termed biophilia (see our post “Frontiers of Design Science: Biophilia”).

Research in environmental psychology reveals that we prefer information-rich environments, though we like them to be easily broken up into manageable higher-level informational “chunks”: buildings and spaces that have coherent relationships, that have identifiable pathways and entrances, that are layered in room-like sequences, that offer enticement, that form complex circuits and spatial relationships. The most attractive streets for pedestrians have these kinds of intricate, information-rich structures.

And we prefer that the surfaces of buildings present us with rich information that we can “decompose” into manageable units that are still related among themselves and to the overall whole (they define a “system”). This means, among other things, that the structures at different scales do not have too abrupt a relationship to one another, but instead, have a coherent, proportional kind of relationship. Geometrical coherence, both on the same scale, and across different scales, seems to play a key role in what we perceive as beautiful and nourishing.

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There is a poorly understood restriction at the heart of the way we design today: virtually all our plans are mathematically doomed to be “incomplete.” But in a seeming paradox, if we can understand this restriction better, we can learn to make much better designs. One good way to do that is to learn from new scientific insights in the mathematics of computer processes, or “computations”.

Here’s a guided tour through this fascinating and most important subject.

Let’s start by noting that, as designers, we rely on mental models to understand, change, and evaluate what we do — even if we do it unconsciously. We need these “pictures in our heads” to guide our actions around various alternatives, not unlike the way we choose routes with driving maps. Even our language is a kind of model of what we are doing, giving us a sense of the issues and problems, and what we can expect of various alternatives. (This paragraph is an example!)

Such mental models, or maps, allow us to respond to real conditions, and act intelligently. As designers, we can choose one or more models that help us to solve the problems we face, and meet the goals we have for the design.

There is a fundamental problem with all models, however, as the logician and mathematician Kurt Gödel implied in a famous 1931 paper. They are “incomplete” — they always leave something out. This is a key requirement for all models to even be useful. After all, a map that is just as detailed as the region it represents will leave us just as lost as being in the region! (The Argentine writer J. L. Borges wrote a wonderful one-paragraph story that illustrates this beautifully, “On Exactitude in Science”). So maps are useful because they are simpler — because they are abstract.

Looking at it another way, the reality we are trying to understand is “computationally irreducible.” We can never reduce it to a formula, or a perfect blueprint. No matter what we do, we will always have to leave something out. It’s just the way language works, and the way human ideas work — it’s how they help us to be more intelligent.

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“Only connect,” the writer E. M. Forster said famously — and modern scientists working with network structures are learning how right he was. Forster was talking about how to tell a good story, but it turns out that the same principles for creating richly interconnected structures do apply to making good cities, or other good designs. And what’s all the more interesting (and important) is how bad we’ve gotten at this in recent years — and why that came to pass.

Jane Jacobs, the great urbanist and economist, put these ideas to intelligent use in her observation of what made cities such evident crucibles of economic productivity. It was proximities, she said, and networks of proximity, that allowed people to exchange knowledge and creative activities. These “Jacobs spillovers” are a major subject of research in economic science today.

Something similar seems to help explain why cities are such resource-efficient places too. Just as cities promote “knowledge spillovers,” they seem to promote “resource spillovers” too, where the waste of one process (say, heat from an energy plant) can become the input of another (say, to heat a building). But these efficiencies can only happen if there is a pattern of proximity, and the possibility of inter-connection.

Cities, Jacobs realized, are webs of connectivity, between people, activities, and places. And these webs were all rooted in the connective pattern of the public realm — the street and the sidewalk. Not only did this public realm allow the creation of networks of connection on the physical scale of human beings and their movements, it also allowed users to control the degree of connections, and to disconnect and reconnect where they needed to.

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In 1984, the environmental psychologist Roger Ulrich made a startling discovery. In studying hospital patients recovering from surgery, he found that one factor alone accounted for significant differences in post-operative complications, recovery times, and need for painkillers. It was the view from their windows!

Half the patients had views out to beautiful nature scenes. The other half saw a blank wall. This was an astonishing result — the mere quality of aesthetic experience had a measurable impact on the patients’ health and wellbeing. Moreover — and this certainly caught the attention of hard-nosed economists — because the patients stayed less time, used fewer drugs, and had fewer complications, their stay in the hospital actually cost less.

Experiments by Roger Ulrich showed that a simple view out to a natural scene conveyed a range of measurable health benefits to recovering patients.

Ulrich’s study began a wave of research into an area known as biophilia — the apparent instinctive preference we have for certain natural geometries, forms, and characteristics within our environments. Over time, many more studies have been done showing that when the characteristics of natural environments are present, human beings tend to feel calmer, more at ease, more comfortable, less stressed — and, most astounding, their health can actually improve.

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There’s a quiet, but important, revolution going on in environmental design today. It started in hospitals, of all places.

Medical science has long used an “evidence-based” methodology. It’s a trial-and-error process that goes through an evolutionary cycle: the doctor tries something, evaluates it, then goes on to use what works. In this way medicine has developed after millennia of experimentation with cures, interventions, herbal remedies, etc.; even today, its application is heuristic. Your doctor might give you a small dose of something, and then if you feel better, will give you more. If you feel worse, stop taking it! Doctors study many patients and their reactions to treatments, and use the collective evidence to modify medicines and procedures, and improve them. Based on this accrued knowledge we can successfully treat diseases today that were once thought to be inevitable afflictions.

Over the years, the medical profession has taken an increasing interest in the design of hospitals, because it has become evident that the patients’ health had a lot to do with the design of the spaces. Did infectious diseases spread more rapidly when patients shared rooms? (Yes, they did.) Were certain kinds of surfaces better or worse at preventing the spread of germs? (Yes.) Did patients do better when their rooms had the kinds of designs that reduced stress? (Yes, again.) These observations and many others have become the subject of “evidence-based design” — design that uses the evidentiary methods of medicine.

Gradually doctors as well as environmental designers began asking the same kinds of questions about the larger urban environment. After all, it did no good to treat a patient at the hospital if he went right back out and got sick again. So epidemiologists like Dr. Howard Frumkin and Dr. Richard Jackson began to look at evidence of, for example, how urban environments could promote walking and exercise, and how nature influences health and wellbeing.

Researchers are documenting evidence of the consequences of urban design choices on human health, resource depletion and other worrisome factors — a particularly urgent need as these models proliferate around the world. Photo: David Evers

Others, like Dr. Roger Ulrich, investigated how environments of all kinds affected wellbeing in other ways, including the (habitually dismissed) health implications of aesthetic qualities. They made an extraordinary discovery: the characteristics of nature, as observed in plants, trees, water, as well as pleasant views, had measurably positive effects on patients’ recovery, stress levels, and physiological wellbeing. (We will have more to say about this extraordinary topic of Biophilia in an upcoming post.)

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A remarkable revolution is under way in the design sciences today — fueled by powerful new insights into the workings of nature, and articulated by the burgeoning science of complexity. New terms tantalize us with their suggestion of innovative directions and new possibilities: self-organization, biophilia, generative design, and much more.

But what’s visible on the surface is still mostly froth: old ways of doing things gussied up in fancy clothing of the new. To see what’s really going on we have to dig a lot deeper, and we need to understand the science a bit more fully.

Within this promising field, no topic is likely more promising than “self-organization” — the ability of complex adaptive systems to grow, order, and organize all by themselves, without any master controller. We observe this phenomenon at work in complex termite colonies that lack architects and blueprints, in biological cells organizing and differentiating into organs without any additional controls, and as we now see, in the very processes that gave rise to life itself.

The complexity scientist Stuart Kauffman described this phenomenon as “order for free” — a kind of spontaneous order that is able to solve problems and adapt successfully to environments. Clearly this is a powerful and very important natural mechanism that might hold important clues for human use.

As a matter of fact, we do see characteristics of self-organization in many human settlements — for example, the remarkably well-ordered villages of traditional societies that did not use architects with blueprints, but instead, relied upon fairly simple rules for generating form, and adapting it to the form that existed. These processes turn out to be efficient at solving human problems — much as the termite mounds manage to achieve very sophisticated self-regulating cooling systems, or species develop very successful solutions to problems of swimming or flight. And they can accommodate powerful forms of art too — a point we’ll come back to.

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The great systems theorist Herbert Simon once gave a very concise definition of design: it was, he said, the “transformation from existing states to preferred ones”. This elegant little phrase packs a punch. For who is doing the preferring—the designer? the artist? the corporate moneymaker? No, the users. Which users, however, and how do we identify them? And how do we know what they prefer? How do we know what the existing state is? How do we know how to get from existing to preferred—what tools and methods can we use? And how can we evaluate that process and correctly re-adapt it as we need to?

This idea of design—as “transformation” using an adaptive process—is very much at the heart of the design theorist Christopher Alexander’s work. Through that adaptive process, we generate a form that achieves our “preferred” state. But at each step of this transformation, Alexander says, we are dealing with a whole system—not an assembly of bits. This turns out to be a crucial point for leading design technologists.

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The words “living” and “technology” do not often occur in the same sentence. We think of technology as something mechanical, inert, dead — very different from life, and even dangerous to living systems. And yet the word “technology” simply means “the knowledge of making” — that is, how to create structures in the world that help us do the things that we want and need to do to thrive as human beings.

Living organisms do very similar kinds of things: a Nautilus makes its shell, a colony of termites makes its mound, a cell makes its twin — and ultimately, through a compounding process, this kind of duplication, combined with gradual differentiation, makes complex organisms. (We will come back to the bit about differentiation.) In a real sense, we call this the “technology of life.”

Essential qualities generated by a technology of life are best discovered in small human creations: not decorative, not superficial, not fashionable, but so honest as to touch the core of living geometry.  Photo: Alexia Salingaros

The insights we are gaining about these processes are opening the door to a new chapter in design — an era of “bio-design”, “biophilia”, and “biomimicry”. It’s an exciting promise, particularly in an era when our old technologies seem to be failing us. The crude industrial processes that powered our world for a century or more leave us with depletion, fragmentation, and decay. Living systems can show us the way to recover and sustain the damaged systems upon which life depends.

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