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Notes

Design Needs Complexity Theory

Despite Christopher Alexander’s notable application of complexity theory in design during the 60's and 70's, the two fields have mysteriously grown apart. The contemporary design world demonstrates little interest in complexity theory, and design is generally absent in the world of complexity theory. I think this separation is not only a missed opportunity, but also a tragic error for humanity on a larger scale.

Forgetting Christopher Alexander

In the spring of 2011, when I was a design student in Copenhagen, my professor loaned me a copy of Christopher Alexander’s A Pattern Language (1977).

Heavy with thin pages, the red, leather-bound book felt like a Bible in my hands. Although I didn’t fully grasp what I was reading at first (in some ways I'm still trying to wrap my mind around it), I realized that Alexander was describing a truth about reality which was much deeper than architecture.1 I had never read anything like it—it was somehow mathematical yet poetic, sophisticated yet straightforward, philosophical yet practical. After finishing A Pattern Language, I swiftly devoured as many of his books and essays as I could find.

A proper introduction to Alexander’s work would require its own book, but I’m going to summarize the important elements with a crude ontology.2 I view Alexander's work as a series of concatenated levels: an object-level artifact or tool; an information architecture that structures the artifact; a process that generates that information architecture; an epistemology that implicates that process; and a moral value system that motivates all of the above. Let’s dive in.

Level 1: Artifact

At the surface level, A Pattern Language is a design and construction handbook for everyone. It contains 253 rules of thumb expressed in the form of patterns. Patterns are reusable sets of relationships forged over time to address common problems. For example, first-floor window sills should be 12 to 14 inches high (pattern #222). Car parking should occupy no more than 9% of land (#22). Balconies should be no shallower than 6 feet (#167). Patterns in this sense are highly applicable and concrete.

 
 
Labeled excerpts from A Pattern Language

Labeled excerpts from A Pattern Language

Level 2: Information Architecture

A Pattern Language is believed to be the first book written in hypertext, with non-hierarchical links (see “context” above) between closely related patterns. This was by necessity, as patterns form an interconnected web which can generate a vast range of combinatorial possibilities to address unique, contextual needs. As suggested by the title, this format is similar to a language in which just a few letters can be combined in many ways to form tens of thousands of words, which can be combined in even more ways to form an infinite number of sentences.3

Level 3: Process

Patterns must be applied and interrelated through a process. In texts like Systems Generating Systems (1968), The Timeless Way of Building (1979), and The Nature of Order (1981), Alexander describes a design process akin to "the way it works in nature," that is, through step-by-step adaptation. In contrast to the top-down approach of modernist design,4 Alexander's method is more like gardening. The designer accepts more limited control over outcomes in exchange for the generativity and context-sensitivity of an open-ended compositional process.

Level 4: Epistemology

Alexander describes a research method, called the “Mirror of Self” test, by which we can evaluate a design. Subjects are asked to self-examine the degree to which a given system or object (say, a salt shaker) “enhances their wholeness” relative to that of another item (say, a bottle of ketchup). Despite the unusual question, most people are able to give a firm answer—and, according to Alexander in The Nature of Order, responses are astonishingly consistent. Alexander wrote about the results, “People make the same choice, whether they are young or old, man or woman, European or African or American.”

Alexander’s method implicates an epistemological framework that allows for an objective reality beyond that which is perceptible to, “the dry positivist view too typical of technical scientific thinking.” He described aesthetics as “a mode of perceiving deep structure, a mode no less profound than other simpler forms of scientific observation and experimentation."

To the modern rationalist thinker, this likely sounds a little woo-woo. But as we’ll see, science may be catching up.

Level 5: Value System

Persistent in Alexander’s work is a call to make the world more whole through “living structures.” In Notes on the Synthesis of Form (1964), this value system is a matter of form having fit within its unique context. In The Timeless Way of Building, he describes “the quality without a name” which he later calls life or wholeness. This quality is deeply relational. In A Pattern Language, he implores designers:

“When you build a thing, you cannot merely build that thing in isolation. You must repair the world around it, and within it, so that the larger world becomes more coherent and more whole; and the thing takes its place in the web of nature as you make it.”

To Alexander, design is a process that is interwoven with the natural world around it and can, and should, positively contribute to rebuilding and improving society.

Not long after first encountering Alexander's work, I enrolled as a graduate student at UC Berkeley’s College of Environmental Design—where Alexander taught until the early 2000’s.

To my surprise, however, I could hardly detect a trace of his imprint at the CED. Despite the fact that he taught there for four decades and produced an abundance of meaningful work, Alexander was almost never mentioned. Most students made it through their entire programs without ever hearing his name.

Why were such monumental ideas seemingly erased?


An Absence in Complexity

In the fall of 2019, I found myself at the Santa Fe Institute with some of my friends and colleagues from Google. We are all deeply fascinated by complex systems, so being at SFI—the world-renowned epicenter of complexity science—felt to us a bit like a trip to Mecca.

The event we were attending was a fairly small three-day symposium. To our amazement, we frequently found ourselves in conversations over coffee with luminaries like Geoffrey West (author of Scale), Eric Beinhocker (author of Origins of Wealth), Joshua Epstein (pioneer of agent-based modeling), and Brian Arthur (a godfather of complexity economics). Occasionally we’d step out into the dry New Mexico air to give our aching brains an opportunity to process everything.

Though he had passed away four years prior, the presence of John H. Holland—a leading figure in the genesis of complexity science and an SFI founder—was strongly felt. As I think many at SFI would agree, there’s likely no better person from whom we can learn the basics of complexity.

Holland characterized complex systems as exhibiting the following five behaviors:

1. Self-organization

Elements of the system self-organize into ordered patterns, as occurs with flocks of birds or schools of fish.

2. Chaotic behavior

Small changes in initial conditions produce large changes later on (popularly known as 'the butterfly effect').

3. 'Fat-tailed' behavior

Extreme events (e.g. mass extinctions and market crashes) happen more often than a normal (bell-curve) distribution would predict.

4. Adaptive interaction

Interacting agents (like traders in a marketplace or players in a Prisoner's Dilemma) update their strategies in diverse ways as they accumulate experience.

5. Emergence

Spontaneous, global order results from many local interactions between agents who lack a source of centralized control.

The leaderless murmuration—caused by each starling adapting its flight path in response to that of its nearest neighbor—is a classic example of emergence.

The leaderless murmuration—caused by each starling adapting its flight path in response to that of its nearest neighbor—is a classic example of emergence.

Since complex systems exist in such a wide range of phenomena, SFI convenes a vast breadth of disciplines. At the symposium, we met physicists, political scientists, epidemiologists, economists, sociologists, ecologists, computer scientists, and even philosophers.

To my surprise, however, there were no designers. No architects, no industrial designers, no graphic designers, no urban designers, no UX designers, and no service designers. Here we were, peering into the fundamental nature of the very social problems designers profess to solve, yet they were nowhere to be found.

Why were designers absent?


Alexander gave us a starting point for applying complexity theory in design

Though Alexander’s work predates the formal term “complexity science,” both describe the same fundamental patterns of complex systems.5 Both focus on interactions within systems where the whole is greater than the sum of its parts.

For example, Alexander described pattern languages as "very complex sets of interacting rules.” Using precisely the same understanding as Alexander, a central interest of complexity science is pattern formation.

Alexander described his evolutionary design process as a "new technique that focuses on emergence” (emphasis added) towards greater fitness between form and context. Meanwhile, biologist and complexity scientist Stuart Kauffman describes evolution as a process occurring across “fitness landscapes” with “adjacent possibilities.”

Visualization of Stuart Kauffman’s fitness landscape

Visualization of Stuart Kauffman’s fitness landscape

By 2003, Alexander was in direct conversation with complexity science. He penned an essay titled New Concepts in Complexity Theory, inviting complexity science into the normative design framework.

The essay’s attempt to bridge between the fields highlights where Alexander and complexity science diverge, and begins to explain the rift we witness between complexity science and design today. While complexity science is chiefly interested in describing and understanding complex systems as they arise in nature or society, Alexander embraces the logic of complex systems into the practice of design.

“In [fields dealing with complexity] the scientists are passive as to the issue of creation. In architecture, we are the active proponents.”
New Concepts in Complexity Theory, 2003

Alexander makes the case that the kind of fitness that arises from complex systems in nature (the evolution of a bird's beak, for example) can and must be achieved by designers through new step-by-step adaptive processes.

Still, Alexander’s move towards actionable complexity doesn’t fully explain why design and complexity theory no longer overlap.

Why have design and complexity theory grown apart?

In 2005, a survey of 1,051 design professionals, faculty, and students asked respondents to prioritize various potential design research topics. Systems theory (a superset of complexity theory) ranked at the bottom of pressing matters for research. (Sustainability—which perhaps most exemplifies the need to understand complex systems—ranked first.)6

I don't know exactly why designers have turned away from complex systems, but one possibility is that complexity challenges a central doctrine of design—namely, that it is the designer’s job to identify desirable outcomes and exert as much control over the process as possible towards those ends.

In some cases, such as the design of a simple object with a simple function (e.g. a chair), this conceptualization may be sufficient.7

But in the world of complex systems—cities, economies, ecologies, society, and the like—complexity theory teaches us that the totalitarian designer’s approach is both likely to backfire in unexpected ways and sacrifices the vast networks of local intelligence distributed throughout the system.

Complexity theory suggests a new conception of design that flies in the face of mainstream practices over the last century. Reimaging design in this way will not come easily, but in many cases, it is necessary.

Why should designers understand complexity theory?

“Complexity is the science of the 21st century”
—Stephen Hawking

I believe that complexity science is the beginning of an upcoming (and deeply necessary) revolution in the cognitive tooling of society. The mental models of a deterministic machine-like reality have gotten us far in complicated domains where systems actually operate in this manner (such as Newtonian physics), but we’ve seen these methods collapse in the face of systems that are complex. Worse still, the failure of these enlightenment ideas to achieve social progress has induced a sort of epistemic resignation that the systems surrounding us are unknowable and uncontrollable, thus rendering our actions effectively meaningless. This is not true!

As a field centered around forging the future by developing new solutions, design in particular must understand complexity. The wicked problems of the 21st century—climate change, inequality, pandemics, political breakdown, and more—demand no less.

Designers must pick up where Alexander left off and develop new ways to think about and apply complexity science in our work, for three main reasons:

1. Reality is complex. We design within reality.

As I have mentioned, Alexander described good design as a proper fit between form and context. If the context is complex (as it often is) then the design of form must understand the nature of complexity. Rigid, non-adaptive, centralized, and machinistic solutions are a path to crisis.

Appropriately, complexity science may be rising in relevance due to evolutionary pressures. If we are to survive as a species in a changing environment, unfit mental models must be eclipsed by better adaptations to the world around us. And, if we are to survive, then those who design the systems around us need to be plugged into this new scientific revolution.

2. Design for emergence leverages distributed intelligence.

Emergent outcomes cannot be planned in advance, just like cities don’t follow one large blueprint and only the complex process of coevolution can create a rainforest.

This reality is not a threat to designers, but an opportunity. In many cases, thousands of minds are exponentially better than one. The final outcome may be one the original designer never imagined, and that’s exactly the point: design for emergence leverages the unique intelligence of end-users to adapt solutions to their unique contexts. This kind of design can create something wonderfully complex like a rainforest—an ecology of heterogeneous agents evolving and co-evolving novel problem solving strategies within a complex web of relationships.

Consider the wide range of adaptive outcomes made possible by digital spreadsheets, in which the simple relationships of cells (which can only contain a small handful of data types) can be combined to create highly complex systems. Digital spreadsheets have eclipsed thousands of would-be single purpose software tools because a general purpose tool designed for emergence can fulfill a wide variety of potential niches.8

Alexander attempted to leverage this kind of local intelligence by creating widely accessible tools like A Pattern Language.9 In Systems Generating Systems, Alexander describes this kind of design as a “kit of parts.” We might think of these kits as innovation-enabling innovation, from which entire ecologies of ideas and solutions might emerge.

3. Design benefits from interdisciplinary mental models

In 1969, Ludwig von Bertalanffy outlined the major aims of general system theory (a precursor to complexity theory):

1. There is a general tendency towards integration in the various sciences, natural and social.

2. Such integration seems to be centered in a general theory of systems.

3. Such theory may be an important means for aiming at exact theory in the nonphysical fields of science.

4. Developing unifying principles running 'vertically' through the universe of the individual sciences, this theory brings us nearer to the goal of the unity of science. This can lead to a much-needed integration in scientific education.

This integration is also necessary in design. The human experience is so exceptionally multidimensional that it forces us to bring together established mental models from diverse fields. Complexity theory combines these many fields, in part because it offers a shared language for collaborating across distinct areas of study and drawing value from these differing perspectives. Ecologists are sharing ideas with economists, physicists are collaborating with political scientists, and computer scientists are engaged with epidemiologists—all with promising results.

What would happen if designers joined the exchange?


1 To be fair, Alexander also had a hard time putting his ideas into words. A central idea in The Timeless Way of Building is “the quality without a name”

2 Alexander never laid out his ideas like this, it’s just how I’ve come to think of them (and the only way I can think of to condense them this much while still conveying the way they interrelate.)

3 See Portugali's The Construction of Cognitive Maps (1996) for an interesting comparison of Alexander's pattern language with Noam Chomsky's linguistic theories.

4 For a deep dive on the failure pattern of the modernist approach, see James C. Scott’s Seeing Like a State (1999).

5 Alexander’s work is sometimes described as drawing from Eastern philosophy, especially populist ideas like those found in Taoism. Complexity theory has also been described as fundamentally parallel to Eastern philosophy. Western philosophy was largely shaped by mind-body dualism, which conceives a plane of abstraction and platonic ideals divorced from material reality. Eastern philosophy, on the other hand, portrays a more embedded and cohesive conception of metaphysical reality and an orientation around interconnected relationships over categorical objects. For more on the subject check out Jeremy Lent’s The Patterning Instinct: A Cultural History of Humanity's Search for Meaning (2017).

6 Meredith Davis discusses this survey further in Teaching Design (2017)

7 On the other hand, the design of chairs may also play a role in complex adaptive systems. In the 1970’s, William Whyte made astute observations of the way people behaved with movable chairs (with which the user becomes a sort of “co-designer” by deciding the precise position of the chair) vs. stationary seating: “[movable] chairs enlarge choice: to move into the sun, out of it, to make room for groups, move away from them. The possibility of choice is as important as the exercise of it.” By making chairs light and movable, the end-user is given the agency to integrate local, temporal, and highly contextual social knowledge into an extended design process that adapts the final configuration of seating to their precise needs in that moment.

8 More examples of this sort abound in the universe of end-user programming.

9 This also helps explain why the design community didn’t embrace him—his idea was to demote them. In The Timeless Way of Building he wrote, “It is essential only that the people of a society, together, all the millions of them, not just professional architects, design all the millions of places.”

Kasey KlimesComment