Thriving in the Emerging Information Ecology
The following is adapted from Trillions: Thriving in the Emerging Information Ecology by Peter Lucas, Joe Ballay, and Mickey McManus (Wiley 2012). The authors are principals at MAYA Design, a leading pervasive computing design firm.
There are already many more computing devices in the world than there are people. In a few more years, their number will climb into the trillions. We are quickly figuring out how to make those processors communicate with each other, and with us. We are about to be faced with — not a trillion isolated devices — but a trillion-node network: a network whose scale and complexity will dwarf that of today’s Internet. And, unlike the Internet, this will be a network not of computation that we use, but of computation that we live in. The world of Trillions — a world that will be saturated with computation — must also be saturated with good design…
Architecture with a Capital “A”
“Technologies get obsolete within 1 year, applications are replaced in 10 years, but the strong visions would survive more than 100 years.”
Throughout this book we have invoked the notion of Architecture with a capital “A;” the idea being that, unlike architecture, which refers to the design and construction of buildings, Architecture refers to the organizational principles of a collection of objects, a concept or a system, which give it a basis for order, structure, change or growth. Architecture, in this sense, is one of the essential qualities of design in the world of Trillions.
Architecture as Organic Principles
Frank Lloyd Wright labeled his philosophy “organic architecture,” which has been described as an attempt to be “more natural than nature itself.” What could such a boast possibly mean? Many people assume that Wright’s choice of the term ‘organic’ was meant to imply an imitation of, or at least compatibility with the natural world — hills, trees, animals. Such an interpretation misses the point. Wright believed that his work reflected not idiosyncratic genius, but a genius based on an understanding of deep principles — the very principles manifest in nature’s patterns. Amplified by human reason, such principles, he hoped, could guide the creation of a rational, humane, and deeply beautiful built world.
When Wright used the term ”organic architecture,” he meant the discipline of designing buildings with an intrinsic integrity that stems from Architecture with a capital “A.” Buildings (or any other designed objects) that are informed by such a conception of Architecture will harmonize (interact) not only with nature but also with the rest of the “built” world.
Implicit in this way of thinking is the supposition that these rules are discovered, not invented. They are “out there”, existing a priori waiting to be discovered. This is to some extent a platonic view of reality. It is a view that is out of fashion in many circles. But we have never been able to understand the alternative. It seems obvious to us that patterns of possibility exist implicitly in the laws of nature, whether we apprehend them or not. Can it really be said that the pattern representing, say, an overhand knot, did not exist until some proto-human tied the first one? We think not. If knots are out there waiting to be discovered, are there not larger, more complex, and more abstract patterns out there as well? We think so.
Architecture as Model
One of the less obvious uses of the process of abstraction implicit in the idea of Architecture is as a means of description. Specifically, Architectural thinking permits us to create abstract models of reality that are far more powerful than more literal descriptions. Consider the difference between traditional architectural drawings of a house and a Computer Assisted Design (CAD) model of the same house. In the old days, an architect would draw floor plans, reflected ceiling plans, various elevations and details. Each of these drawings was intended to represent the same house, of course, but each was executed as a separate drafting task. The idea was to produce a consistent set of pictures of “the house in the designer’s head,” with the goal of communicating the specifics of that house to a builder. But because the pictures were all independent, their consistency was completely dependent upon the skill and attention of the draftsperson. There is nothing about such a system that guarantees that the various pictures will comprise a consistent description of a realizable object. In point of fact, no such set of drawings of any complexity are ever completely consistent. This is a fundamental problem with a view-based medium, not just with the process.
Now consider a representation of the same building made with a modern 3-D CAD system. Though one may use such a system to produce exactly the kinds of views that were formerly done by a draftsperson, those views do not themselves constitute the fundamental representation of the building. Instead they are simply renderings of something deeper: an intrinsically self-consistent model of the house completely separated from any particular view of it. The model itself is not a picture. It is abstract, and makes no assumptions about viewpoint or presentation. Each detail of the house is stored in the model and then brought into play as different views require it. No contradictions are possible, since there is only one model. And since the pictures generated by the CAD system are derived via a consistent process from a self-consistent model, they, too, are guaranteed to be consistent with each other.
But there is another difference as well: CAD models are (or at least they can be) parametric. A parametric model is factored into constants and variables. Together they form a scaffolding on which all information about the model hangs. The constants are its essence, its Architecture with a capital “A,” the boundaries of its ‘design space.’ The parameters (variables) are adjustable. They are like knobs we can turn, and in turning them we can produce an infinite number of particular house-variations, all manifestations of the same underlying Architecture. In doing so, we not only get lots of different houses (which may or may not be good houses), but we also achieve a much deeper understanding of our own Architectural efforts.
By now it should be clear that the application of this approach is not limited to the description of physical objects. We can create parameterized abstract models of computing devices, of network topologies, of user interfaces, of social networks. And most importantly, we can create such models of patterns of information. The metaphor of a parametric CAD-style model for Cyberspace can help us crystallize the fog of information.
Architecture as “Style”
Yet another way to conceptualize Architecture with a capital “A” is as a matter of style — ‘style’ in the sense of Gothic, or Art Deco, or Postmodern. As Walter Dorwin Teague put it, “at those historical moments when a dominant style exists…a single character of design gets itself expressed in whatever is made at the time, and not a chair, a teapot, a necklace or a summerhouse comes into existence except in a form which harmonizes with everything else being made at that time.” If one were to call a furniture store and — sight unseen — order a room full of, say, Mission Style furniture, the result might not merit coverage in Architectural Digest, but it would likely hang together pretty well.
Where do styles come from? Well, they don’t come from committees, and (at least in general) they don’t come from lone engineers. Rather, they emerge as rough shared consensus among communities of practice — more specifically among communities of designers. When designing at the scale demanded by pervasive computing, we will inevitably be forced to abandon our dreams of perfect rigor, and when we do, the only remaining alternative to chaos is the loose but pervasive consensual shared agenda that we refer to as deep Architecture.
Architectural thinking should be particularly attractive to business leaders because it is the one true path to genuine and sustainable innovation. The infinite combinatorial possibilities that are implicit in a generative Architecture constitute the wellspring of design potential. To a Design Scientist, a specific innovation is never a one-off stunt, never the result of luck or hacking, but rather the tip of an architectural iceberg. The “fast followers” and knock-off artists may imitate the product you ship today, but they can copy only what they see. It didn’t take long for Apple’s competitors to produce shallow knock-offs of the iPod, but they couldn’t anticipate Jobs’s plans for the coming iPhone, much less the iPad. In a sense, Jobs couldn’t see them, either. But what he could see was a path forward. He had a plan; a plan in the form of an Architecture. For the architect (and his or her client), there’s always more where that came from, and it doesn’t require starting over from scratch; your next innovation results naturally from adjusting the parameters of the principles you’ve put in play.
But the Trillion-Node Network will require the emergence of another distinct kind of style, namely a style of Information Architecture (IA). Lying just above systems architecture (which deals with how the information devices themselves are built) and just below User Interfaces (which is about how systems are presented to users), IA deals with the design of the information itself. The Trillion-Node Network is not a thing. It’s a vast, heterogeneous worldwide ‘dataflow’ of information. The only commonality across its vastness is information, and it is here that we must concentrate new design effort if we are to achieve a semblance of global integrity.
Don’t confuse information architecture with the more basic concept of Architecture with a capital “A”. IA is an application of “capital A” principles in a particular domain — the domain of information. Information architecture is the specification of abstract patterns governing the relationships among information objects. Of course, all information is itself abstract, so IA represents a second order of abstraction — patterns of patterns.
So, if the Industrial Revolution gave rise to industrial design, just so, information design is the natural outgrowth of the Information Revolution. That thought might prompt you to ask, “You can’t design information, can you? It’s immaterial, what is there to design about it?” True, information has no form. And if you think of design as only “look and feel,” then the idea of designing information makes no sense. Information doesn’t have a look and feel. You can’t see information. So what exactly would you “design” about it?
To the casual observer, design is about the skin. Talking about the design of a hardcover book means the appearance of the dust jacket. And if you exclude the jacket, you might hear, “What do you mean, the design of it? It’s a book.” But books have a great deal of design — much of it having nothing to do with appearance. When an author organizes topics into an outline, that is an act of design. The choice of voice and expository tone are design issues. None of these things are “content,” they are decisions that structure and organize the content.
But, books don’t just have design, they also have Architecture. The outline and specific expository decisions of a book are specific to that particular book, hence we call them ‘design’. But there are patterns that transcend the design of any single book. We structure books into chapters. We start them with prefaces and end them with epilogues. We put tables of contents in front and indexes in the back. These are decisions that float above not just the content, but also above the design. They are acts of Information Architecture.
These examples provide a concrete illustration of how the articulation of abstract patterns (like the idea of ‘chapters’) can permit us to bring coherence and familiarity to an open-ended set of books — even books that have not been written yet. But books are relatively simple things. How much more important is it to provide coherence and familiarity to the vast and burgeoning universe of data that is the Internet? If that universe still consists largely of chaotic collections of disconnected, independent data silos and safe but sterile walled gardens, it is the absence of virtually anything worthy of the name information architecture that we have to blame. If we have managed to make the Web useful without such sophistication, credit is due to amazingly clever and subtle techniques of search engine design combined with virtually unlimited amounts of brute force computing power and storage. But these are stopgap measures. We can do much better and we will. The trends that we have been exploring throughout this book will require it.
We should caution the reader that although we are prepared to defend our usage of the term “Information Architecture” in the specific sense that we have defined, such usage is not universal. People talk about the IA of a website or of a visualization. But many of such usages in fact refer, not to an architecture at all, but merely to relatively superficial (or at least case-specific) decisions concerning the stylistic features and coordinated ‘look and feel’ characteristics of ensembles of coordinated designs. We have no quibble with this kind of design; it is productive and important. It is just that it isn’t Architecture. To be worthy of this term, a pattern must transcend a single project and a single designer. Designs belong to individual designers, Architecture belongs to communities of practice.
We earlier posed the question “How does one design an emergent property?” We are now prepared to offer an answer. It involves two steps: First, develop and perfect an Architecture. Second, subject your Architecture to market forces. This recipe, of course, is flippant. But it captures an essential point. Architecture and evolutionary processes are the Yin and the Yang of complexity design. We believe that this is how Nature works, and that it is the only tractable approach to designing any system whose aggregate complexity vastly exceeds the bounds of human cognition.
Information Architecture transcends almost every other issue in the field. By its use, one can give information an essential structure that permits it to flow and recombine freely, much as the structures of genetic code provide a corresponding liquidity for the information of life. Getting it right is vitally important because the result will be an incalculable increase in the value of all the world’s information as we move onto Trillions Mountain.
Joe Ballay is former head of the School of Design at Carnegie Mellon University and a founding principal of MAYA Design. An interdisciplinarian, he holds an MFA in design from Carnegie Mellon University, a BFA in industrial design from the University of Illinois, and a BS in industrial management from Carnegie Institute of Technology. He has taught design at universities throughout the world, including Georgia Tech, Virginia Tech, Samsung Design Institute in Seoul, and Lund University in Sweden.
Mickey McManus is president and CEO of MAYA Design, a technology design and innovation lab focused on “taming complexity.” He leads a team of cognitive psychologists, ethnographers, computer scientists, electrical and mechanical engineers, mathematicians, visual and industrial designers, architects, game designers, and filmmakers. This interdisciplinary team focuses on designing for people in a trillion-node world.
Dr. Peter Lucas is founding principal at MAYA Design, which he cofounded in 1989. He is also adjunct associate professor of Human Computer Interaction at Carnegie Mellon University. He holds a PhD from Cornell University, where he studied educational and cognitive psychology and psycholinguistics. He served on the Committee on Networked Systems of Embedded Computers of the National Research Council.