This guide has three parts: a series of questions and answers to provide the reader with an overview of the main themes of the book; a chapter-by-chapter summary; and finally a list of the books I found especially useful in researching and writing Smart World.
A. Some Questions Answered
1. What is Smart World: Breakthrough Creativity and the New Science of Ideas about?
It’s about how imaginative minds, using a combination of intuition, insight, and externally embedded intelligence, make creative leaps. The standard story about such leaps—printing with movable type, the discovery of DNA, the Apple iPod—is that they are the product of supremely gifted individuals, also known as geniuses. Unfortunately, mainstream psychology hasn’t been able to throw much light on what genius is. However, a new paradigm is emerging that directly challenges a major assumption of most current theories of creative thinking, namely that the intelligence that drives it is located exclusively inside the head. Leading philosophers and mind/brain scientists like Daniel Dennett and Andy Clark argue that, contrary to both the academic and commonsense view, the mind extends out into the world. As Clark succinctly puts it, “Our brains make the world smart so we ourselves can be dumb in peace.” Once we recognize the existence of external sources of intelligence, we can begin to conceive of creative thinking in a radically new way. Put briefly, creative breakthroughs typically occur when we successfully transfer part of the intelligence embedded in our smart world from one domain to another.
“Modern economies,” The Economist recently noted, “are not built with capital or labour as much as by ideas.” By some estimates nearly half America’s gross domestic product is based on intellectual property. As the knowledge economy rapidly morphs into the creative economy, it’s becoming more urgent than ever to understand creativity, especially those leaps that change the very nature of the game. Smart World addresses that need by examining multiple cases of creative leaps in business, including the rise of the personal computer, the invention of Barbie, the iPod, and more. Other illustrations, however, are drawn from science and the arts, including the discovery of DNA, Frank Gehry’s reinvention of architecture, and Turner’s revolutionary late paintings. This, then, is a book as much for the general reader as for business and professional people; it’s also for academics, students, entrepreneurs, investors, and consultants. These days, having a better understanding of creativity is an imperative for just about all of us.
2. So what exactly is this smart world we live in, and how is it structured?
The term smart world points to a major paradigm shift in our view of the mind and how it makes sense of the world. Anthropologists have long observed how cultures embody myths and rituals that help those immersed in them act meaningfully and effectively. Now philosophers, cognitive psychologists, neuroscientists, and artificial intelligence researchers are giving this insight a new edge. To quote Clark again, “We use our intelligence to structure our environment so we can succeed with less intelligence.” What he means is that we rely on all kinds of tools (slide rules), cultural artifacts (the Arabic number system), easy to use knowledge-embedded objects (maps), and so forth, to help lighten the computational load on our minds.
Smart World extends this approach through the core concept of idea-spaces. Simply put, an idea-space represents a world (in the sense of the world of modern art, venture capital, soccer), seen from the point of view of its embedded intelligence—the stuff we use, knowingly or not, to engage effectively with that world. For many teenagers, for example, the word cool invokes an idea-space having to do with a loosely connected collection of attitudes, fashions, taste in music, ways of talking, digital artifacts, websites, etc. Teens have no difficulty picking up not just what’s considered cool in their social group at any given time, but more importantly the basic precepts that drive the current trend. These precepts—the embedded intelligence of the cool idea-space—live external to any one individual, in the community that values being cool. Furthermore, they serve an important cognitive function, guiding teens in how to make sense of and act in new situations.
Again and again, if we’re paying attention, we’ll find that once we’ve become familiar with a world/idea-space, the intelligence embedded in it does most of the work for us.
3. I’m still a bit puzzled. Are you saying idea-spaces can somehow think?
Surprising as it may seem, yes! Here’s another example that may help. Marcel Duchamp once placed a snow-shovel in a museum. Seeing it there, no one is going to go looking for snow to clear away. The whole idea-space of a museum conjures up a completely different mindset. Instead we find ourselves asking, What is the hidden meaning of this? How should I respond to it? What is its value and importance? The space itself—the white walls, objects spaced well apart in rooms with a specific theme, the typically high entry price—all say, Pay attention, this is culturally meaningful! In short, the space of ideas thinks for us, telling us how we should respond differently to a shovel found on a museum wall as opposed to in a tool-shed. In the book, I discuss many examples of how idea-spaces think for us, from the mundane (business plans) to the sublime (the myth of Aphrodite).
4. How does this new smart-world paradigm provide fresh insight into creativity?
Chapter 1 opens with the story of Picasso’s artistic epiphany in the Musée d’Ethnographie du Trocadéro in Paris. Still trying to find himself as a painter, he is struck by something about the African masks there. Suddenly, he understands what it is: they were made by anonymous artists as a way to propitiate unknown threatening spirits. And in an instant he realizes that he shares this view of art. That same day, he begins thinking of Les Demoiselles d’Avignon, “my first canvas of exorcism,” and the picture that would effectively launch Cubism.
This is a good illustration of how a space of ideas, in this case one with a dramatic physical embodiment, can provoke a huge leap in creative thinking. There was no obvious counterpart in western art to either the non-representational geometry or exorcist function of the African sculptures. Picasso simply wandered into the space and “got it.” Much of the book is taken up with similar instances in which a major breakthrough results from transferring the intelligence embedded in one space to another, in the process transforming the latter.
Once we can accept that we live in a smart world made up of intelligence-bearing idea-spaces, then it should be obvious that such spaces represent a vast reservoir of untapped creative thinking. Interestingly, there’s a flip side to this. Idea-spaces reveal, giving rise to new ideas and imaginative vistas, but they also conceal. They thus help to explain why in case after case some gifted individual succeeds in making a breakthrough while other seemingly equally well informed and talented laborers in the same field remain blind to what in retrospect seems obvious. It all comes down to which idea-space(s) you’re immersed in.
To take one example discussed at length in the book, Erwin Chargaff, a distinguished American biochemist, couldn’t make anything of the fact that in all the samples of DNA he examined, A = T and C = G. Why was Chargaff blinded to what was obvious to Crick the minute he heard about it, i.e., that it revealed a structure characterized by complementary replication? Because Chargaff was too immersed in the idea-space of biochemistry (he spent much of his day doing chromatographic filtering of beef broth) to think in the abstract terms of genetic geometry pioneered by Gregor Mendel and Frederick Sanger. Mattel executives, stuck in the conventional world of baby dolls with fat legs and chubby faces, were similarly unable to see the possibilities of a slender doll with breasts when Ruth Handler first mooted the idea of Barbie to them. Idea-spaces think for you, not always with the best possible outcome.
5. What is the new science of ideas?
Idea-spaces and the embedded intelligence lying at their core form themselves into a vast series of dynamic, self-organizing, self-transforming networks. The emerging science of networks, a new and exciting discipline originating notably in the work of Steven Strogatz, Duncan Watts, and Albert-László Barabási, gives us a powerful new framework within which to study and gain insight into the dynamics of networked idea-spaces. In the book I’ve formulated nine laws, based on established principles of network science, that jointly characterize not only how idea-spaces emerge, link up, combine, integrate, expand, dominate other spaces, collapse, or simplify, but also how the mind’s imaginative faculties interact with these dynamics to produce creative breakthroughs. This approach to creativity is still in its infancy, and the “laws” the book sets out have for the most part yet to attain the level of hard-core laws of science. Nevertheless, we have to start somewhere, and using network science to ground empirical insights into the dynamics of our smart world and the human mind’s ways of imaginatively engaging with it looks a promising place to begin.
6. So bottom line, what will I get from reading this book?
Based on the laws and principles explored in the book, the last chapter sets out series of precepts and practices businesspeople, scientists, technologists, and other professionals can follow. Broadly, these have two practical aims. First, to help you to recognize radically new ideas, trends, and products as they emerge—in other words, to see the future before it arrives (in this era of what Andy Grove famously called 10x Internet time, seeing the future when it’s arrived is often already too late). Second, to enhance your own capacity to produce creative leaps, and/or to manage/collaborate with others in doing so. More generally, you should acquire a deeper understanding of the creative process, and of how the mind’s imaginative faculties interact creatively with the idea-spaces of our smart world.
B. Chapter-by-Chapter Summary
Introduction—The Mystery of Breakthrough Creativity
How does the mind work? It’s an important question and over the past seventy years we’ve made a lot of progress in answering it, but we’re still largely in the dark about how the mind’s creative faculties operate. Attributing breakthroughs like the discovery of DNA, cubism, the personal computer, printing with movable type, and the iPod to pure genius doesn’t grant much real insight. As the knowledge economy morphs into the creative economy, understanding how we make creativity leaps is becoming ever more important.
Over the past two decades, three important developments in philosophy and the mind/brain sciences have begun to transform this picture. First, we now recognize that the mind extends beyond the brain into a world we ourselves have made smart with embedded intelligence. This smart world, formed by an endless series of overlapping, culturally and socially embodied idea-spaces, makes available a vast reservoir of creative energy, resources, and potential insight to those able to navigate it effectively. Creative leaps typically occur when some new source of intelligence is tapped into and transferred to a different domain.
Second, there has been a surge of scientific interest in the mind’s imaginative faculties. Centuries of intense study of analytical reasoning, the basis of most incremental scientific and technological advances, have shed little light on truly creative achievement. Recently, however, imagination, intuition, and insight, long neglected by mainstream philosophy and psychology in spite of their obviously central role in creativity, have finally started being given their due in academic research. This has been prompted in part the rigorous study of various forms of analogical reasoning and transfer, whose holistic powers of organization and structure make up for the deficiencies of purely linear thinking in creative endeavors.
Third, mind/brain scientists are rapidly developing a fully networked view of the mind. As a result, the emerging science of networks, still less than a decade old, can begin to provide powerful insights into mental operations, including those involved in leaps of the imagination. Drawing on well established principles of network science, it becomes possible to formulate a series of laws capable of tracing the arc of the imaginative intelligence as well as the self-organizing transformations of our smart world on which it piggybacks.
The integration of these three developments leads to the emergence of a radical new, powerfully insightful paradigm of breakthrough creativity, one that can finally provide the basis for something truly useful and exciting: a new science of ideas. This new science helps explain achievements that have previously been regarded as the unfathomable products of genius: Jobs’ and Wozniak’s success in bringing the personal computer into the mainstream, Crick and Watson beating out Linus Pauling in solving the enigma of DNA, Ruth Handler’s transformation of the doll industry, Frank Gehry’s revolution in architecture.
Chapter 1—Outing the Mind
When Picasso wandered into the seedy Musée d’Ethnographie du Trocadéro in Paris one day in 1906, he was still trying to find himself as an artist. When he emerged, he later reflected, “I understood why I was a painter.” Already Les Demoiselles d’Avignon, the revolutionary painting that would launch Cubism, was beginning to take shape in his mind.
What had happened to produce this extraordinary epiphany? The museum mostly contained bric-à-brac brought back from France’s new-found colonies—spears, beads, musical instruments, loincloths. What caught Picasso’s attention, however, was a series of African masks. Suddenly, it had come to him: the masks were intercessors, serving to exorcise an essentially hostile reality. Enthusiastically embracing the insight, Picasso immediately embarked on his own form of exorcist painting.
Picasso’s experience in the dusty halls of the Trocadéro was characteristic of what happens to many highly imaginative thinkers—artists, scientists, and businesspeople alike: he encountered a powerful new idea-space and began to let its strangely compelling logic think for him. The space of ideas thinks for you. That is the mantra of this book.
Common sense tells us that thinking takes place inside the brain. However, anthropologists, philosophers, and mind/brain scientists are now challenging that basic assumption, producing a major paradigm shift in how we think about the mind. The lead thinker here is Andy Clark, who wittily refers to these new ideas as “outing the mind.” As he points out, we use everything from slide rules to the Arabic number system to think for us. Extending this approach through the concept of networked idea-spaces enables us to conceive of what he calls “the extended mind” as a highly dynamic, rich source of creative energy and substantive ideas for those skilful enough to surf it imaginatively and intelligently.
We can think of an idea-space as a world (as in the world of art, baseball, etc.) seen from the point of view of the intelligence embedded in it. Grasping this intelligence (consciously or not) is what enables us to operate effectively in that world. Idea-spaces take many forms: scientific paradigms, art movements, myths, business plans, social institutions such as market-oriented capitalism—the list is endless.
What is interesting about idea-spaces is that they clearly form themselves into dynamic networks—they’re all interconnected, in one way or another. Hardly a surprising fact, but it means that we can bring to bear on their structure and organization the emerging science of networks. Thanks to the work of pioneers like Albert-László Barabási, we now understand that dynamic networks are self-organizing—they drive their own transformation. This turns out to be true, whether we’re studying networks of brain cells or of websites on the Internet. In the case of idea-spaces, this dynamism is clearly a major source of creative energy, for those who can tap into it.
Drawing on some well established principles of network science, it’s possible to formulate nine laws that govern the interaction of the idea-spaces of the extended mind. Within the framework provided by these laws, including the law of spontaneous generation, the laws of fitness, the law of hotspots, the law of small-world networks, and the law of minimal effort, we can finally begin to crack the enigmatic code of creativity and start down the path toward a new science of ideas.
Chapter 2—Spaces to Think With: Reason, Imagination, and the Discovery of DNA
“We have discovered the secret of life,” Francis Crick announced to a bemused lunchtime audience at the Eagle pub in Cambridge on Feb. 28th, 1953. A few weeks later, on April 25th, Crick and Watson would publish their famous 800-page paper in Nature. Their Nobel prizes followed in 1962. Fifty years on, with the human genome project behind us, and the new frontier of epigenetics now the focus of attention, the discovery of the structure of DNA retains its ability to fascinate and astonish us. When Crick and Watson started out, it wasn’t even accepted that DNA was the genetic material. When they were done less than two years later, biology had gone through a tipping point as big as the one physics went through in 1905 with the publication of Einstein’s four papers.
How did they pull off this extraordinary feat? And perhaps no less important, why did their rivals in the race, notably Erwin Chargaff, Rosalind Franklin, and Linus Pauling, fail? Innate intelligence was hardly the issue—Chargaff and Franklin were both at the top of their professions, and Pauling was destined become a double Nobel laureate. And if Pauling and Chargaff lacked access to Franklin’s more detailed results, all three had sufficient data to have hypothesized the DNA molecule’s central features. Yet none was even close.
Idea-spaces reveal but they also conceal. Chargaff and Franklin both adhered strongly to an experimentalist approach to science that eschewed a more theoretical stance. “We are going to let the data tell us the structure,” Franklin told Crick when he urged her to speculate more freely about DNA, using theory as a guide. But neither she nor Chargaff were able to make sense of crucial patterns in their own lab results. Pauling applied the physicist’s methods of bold theoretical speculation and model-building to the problem. Both proved essential to solving the enigma of DNA, but something more was still needed that Pauling, in thrall to his prior success, failed to grasp.
Unraveling the secret of DNA’s structure required a whole new space of ideas to guide hypothesis formation and data interpretation. That space was genetic geometry. A genetic approach to the problem revealed that somehow, the structure of the DNA molecule had to solve the paradox of identity in difference: in other words, replication demanded the identical copying of an infinitely varying amount of genetic information. Crick, who had thought long and hard about the genetic aspects of the problem, and who had also mastered the theoretical/model-building approach, let his thinking be guided by these powerful spaces of ideas. It was the integration of these two idea-spaces that enabled him to: appreciate instantly the significance of Chargaff’s results, which revealed precisely the anticipated identity-in-difference; interpret Franklin’s complex data as indicating a double reversed helix; and look for ways in which the inherently one-dimensional genetic code could be embodied in a three-dimensional structure. In the end, it was Crick’s choice of idea-spaces to guide his thinking that let him and Watson succeed where other talented scientists had failed.
Crick and Watson’s triumph was also testimony to the powerful role of the mind’s imaginative faculties in making breakthrough discoveries. “The most important requirements in theoretical work,” Crick asserted, “are a combination of accurate thinking and imaginative ideas.” Analytical reasoning applied to empirical data could demonstrate the accuracy of a hypothetical model, but as Crick fully appreciated, creating the model in the first place was the work of the imagination. As the story of DNA shows, and as the narratives in the remainder of the book will further demonstrate, the imagination doesn’t create in a vacuum. Rather, guided by intuition, it accesses those idea-spaces that will provide insight into the problem.
Chapter 3—Genius, Imagination, and the Nature of Mind
Most of us still attribute great creative achievement to genius, while admitting we have little idea what this really means. As Peter Kivy notes in The Possessor and the Possessed, antiquity gave us two views of genius. Plato held that inspiration for great art came from a divine source, Longinus that it came from within. Longinus’ view, subsequently modified by Kant, has prevailed. Whatever genius is, it still comes from within, and of a piece with the mind-inside-the-head model of cognition.
How does the mind work? No simple answer is possible, but if we’re interested in creativity, then we’d better have at least some conception of this. In recent years, in spite of the complexity of the question, a surprisingly broad consensus among philosophers and cognitive scientists has emerged. No one has articulated the current view better than Harvard psychologist Steven Pinker. He dubs it the “computational theory of mind.” Put simply, the mind is made up of a series of innate mental modules that mirror key features of how the external world is structured. Together with innate powers of analytical reasoning and progressive accumulation of empirical data, we gradually build up our knowledge of the world. The crucial property of this cognitive apparatus is that it constructs the knowledge base we use to act intelligently in strictly linear, step by step fashion (reason brooks no leaps), always moving inferentially from the simple to the more complex. Pinker is so confident of the computational model of cognition that he boldly proposes that “intelligence has become intelligible. It may not be too outrageous to say that at a very abstract level of analysis the problem has been solved.”
The flaw in this approach is that it makes no allowance for intelligent thought being involved in creative leaps, which by their very nature are non-linear. As Thomas Kuhn pointed out in The Structure of Scientific Revolutions, major shifts in scientific paradigms happen holistically, like a gestalt switch, not analytically in step-by-step fashion. Kuhn’s paradigms are essentially types of idea-spaces. What Kuhn lacked to further develop his insightful ideas about paradigms and their role in scientific breakthroughs was a theoretical basis to account for their emergence and dynamic interaction.
Network theory, as developed by Barabási, Steven Strogatz, Duncan Watts, and others, is beginning to provide an insightful way to explain the sudden non-linear shifts—jumps from one web of ideas to another, transformations of a whole space of ideas by another—that characterize successful acts of creative intelligence. The imaginative faculties of the individual mind, surfing the networked idea-spaces of the mind out there in search of powerful new patterns of embedded intelligence, are guided by the same laws that govern the dynamics of the extended mind.
The following chapters examine in detail eight laws of network dynamics that provide real insight into how imagination, intuition, and insight work, and how they drive the intelligent thinking that underlies creative breakthroughs. These laws give us for the first time a way to describe the familiar but seemingly inscrutable processes that underlie creative thought: the leaps of the imagination, linking previously unconnected idea-spaces; the framing effects of dense hubs; the pattern-recognition characteristic of intuition; and the sudden tipping points marking the shift from complex to simple that is so typical of insight. For the first time, we have the possibility of a real science of ideas.
Chapter 4—The Fools on the Hill: Tipping Points and the Microcomputer Revolution
In January 1975, the cover of Popular Electronics, a leading hobbyist magazine, announced the arrival of the Altair, the first programmable computer available in kit form for under $500. Within 18 months, a dozen similar machines were available, and the race to build the first truly effective mass market home computer was on. Even as this was occurring, Xerox PARC was developing a similar-sized computer of far greater power and sophistication, the Alto. Yet the Altair and its competitors easily won the race. The Alto was a complete flop.
The personal computer was the original Next Big Thing in high tech. Its story raises two key questions: How can we see the future before it arrives? And why are some able to grasp and participate successfully in huge creative opportunities even as they unfold, while others remain blind to them? More specifically, why did such major players in the computer industry as IBM, HP, and DEC fail to see the personal computer coming? And why did a rag-tag band of hobbyists and counter-culture idealists beat out the powerful Xerox Corp. and its brilliant research team?
The major computer companies were blind to the rise of the personal computer because, like Crick and Watson’s rivals, they were operating in the wrong idea-space: a business model that took as axiomatic that the only real customers for computers were business and research organizations. The sudden emergence and exponential growth of a market for a home computer was simply not on their radar—a classic case of a disruptive technology in Clayton Christensen’s sense.
The developers of the personal computer, including Steve Jobs, Steve Wozniak, Bill Gates, and Paul Allen, were all members of the celebrated Homebrew Computer Club, which drew its main inspiration from two idea-spaces that had little connection with the corporate world: hobbyist electronics, whose ethos was to make it possible for amateurs and professionals alike to build their own machines at home, no matter how crude the resulting functionality might be; and the counter-culture whose idealists (many of them also hobbyists) embraced the mantra of computer power to the people.
The law of tipping points states that in an open dynamic network, at some point more is different: quantitative change suddenly becomes qualitative transformation. Barabási’s research on networks has demonstrated that hubs—densely interconnected nodes—play a major role in triggering tipping points, which by their very nature characterize many creative leaps. The development of the home computer, initially quite chaotic, was powerfully organized by the interaction of the twin hubs (i.e., networked idea-spaces) of the hobbyist and counterculture communities in Northern California. Jointly these hubs, constantly fed by one another via feedback loops and virtually inaccessible to the major high-tech companies, triggered a series of tipping points that not only largely determined the development trajectory of the home computer, but also helped generate its explosive growth.
Chapter 5—Darwinian Networks, Or Why the Fit Get Rich
“Nobody really knew what was going on. So many things would have obviously needed to be done if you’d had the vision back then. Nobody had the view of the market,” noted Bill Gates, looking back on that extraordinary period in the late 1970s when the hobbyist home computer morphed into the personal computer. For a time, over a dozen firms vied for leadership. And yet by the start of the new decade the outcome was already decided. The Apple II had trounced the competition, in the process largely defining what the personal computer would be. By 1982 its phenomenal success put Steve Jobs on the cover of Time under the headline “Striking It Rich,” as Apple became the first personal computer company to exceed $1b in annual sales. When Apple entered the Forbes 500 in 1983, it was already the fastest growing company in Wall St. history.
Was it luck? Genius? No doubt a combination of these played their part. But what separated out Jobs and Wozniak wasn’t smarts per se (their competitors were no mental slouches), nor even their share of good fortune, but rather their intuitive grasp of a well established law of networks. As Barabási has demonstrated, in growing markets, the conventional wisdom of first-mover advantage and the rich get richer is superceded by the law of the fit get rich. This law, which applies universally to dynamic networks, accounts for the fact that nodes will preferentially attach to other nodes or hubs that they relate to in terms of fitness. Over time, feedback loops, especially between hubs, can cause a networked idea-space to tip.
In the overall emergent idea-space of the personal computer, a series of emerging patterns relating to technical specifications, organizational development, and consumer concerns (price, reliability, documentation, and the availability of software programs) began to develop. The two Apple founders’ special talent was to grasp, in the midst of a maze of possibilities, these emerging vectors of fitness and align their design and marketing efforts with them. In doing so, they made their share of mistakes (e.g., they initially missed the importance of Dan Bricklin’s VisiCalc program and its fit with growing market of entrepreneurially minded businesspeople). Better than most, however, Jobs and Wozniak grasped not only these patterns of fitness, but the synergies between them. Inevitably, the law of the fit get rich drove the Apple II’s extraordinary growth. Together with the law of tipping points, to which it is closely related, this law played a major role in shaping the idea-space of the personal computer. One of the biggest creative leaps in the high tech industry turns out to have been largely a function of network dynamics.
Chapter 6—The Mathematical Ecology of Creativity
If the growth of the personal computer industry was impressive, it was by no means unique. The Internet underwent a similar pattern of exponential growth, as did Napster, eBay, and the New Economy itself. The laws of tipping points and the fit get rich were operating here too. But beneath the dynamic growth they produced we may detect the operation of a deeper law of great generality and power, the law of spontaneous generation, which holds that structure arises spontaneously in dynamic networks.
It was Cantor who first discovered the principle underlying this law: there are always more sets of things than things. Put differently, for any given set of objects, there will always be more ways of relating or combining them than there are objects themselves. In network terms, there are always more links between nodes than nodes. This seemingly abstruse mathematical truth has surprisingly practical applications. Cantor’s insight underlies Metcalfe’s law, for example, identified as the driving principle behind the growth of so-called viral marketing on the Web. Similarly it plays a critical role in what the mathematical ecologist Stuart Kauffman calls “order for free,” the seeming spontaneous emergence of coherence in biological systems independently of evolutionary pressures. Economist Paul Romer has relied on this same principle in theorizing about the inexhaustible stream of ideas that fuel the emerging creative economy. We can even see spontaneous generation occurring in Cubism, whose abstract geometry of lines and curves invite the viewer to form and reform a painting’s pictorial significance. In a Cubist painting, there are always more relationships, more ways of grouping things together, than there are things.
The law of spontaneous generation demonstrates that in any dynamic network of elements, new relationships will form autonomously. This emergent order for free lightens the individual burden of creativity. The space itself possesses creative powers. Of course, many of the new connections and gestalts created will be relatively meaningless, but a significant subset will possess the potential of meaningful development. The task in a maze of possibilities, as Jobs and Wozniak showed, is to combine imagination, intuition, and insight in finding the right ones. And that, as they say in network science, is a navigation problem.
Chapter 7—Sex and the Single Doll: Barbie, Ruth Handler, and the Navigation Problem
When Ruth Handler first proposed producing a teenage doll in the mid-1950s, Mattel executives (including her own husband) were not amused. The future surely lay in continuing to make baby dolls, which had sustained the market since the 1920s. Everyone knew that what little girls wanted more than anything else was to play at being mothers. Handler’s intuition, based in part on watching her daughter Barbara play dolls with her friends, told her otherwise. On a trip to Switzerland, she found exactly what she was looking for, the so-called Bild Lilli doll, based on a risqué newspaper cartoon character. Returning home brandishing Lilli, she overcame Mattel’s objections, and Barbie was shortly launched to an adoring public. The rest is, well, herstory!
Entrepreneurs need luck in making their creative leaps, and Handler’s chance encounter with Lilli was certainly fortunate. But there’s more to Barbie’s success than that. Barbie quickly drew imitators such as Tammy, Tressy, and Bizzie Lizzie, all of which failed. So how did Mattel, as they developed and refined the Barbie concept, find the right path in the midst of so many possibilities? How did they navigate their way to success?
The law of navigation says that the bigger the search space in a network, the harder it is to find a specific location within it. In dynamic networks, the law of spontaneous generation exacerbates the navigation problem by geometrically increasing the number of links between nodes, thereby ensuring that the number of possible configurations of nodes (and hence idea-spaces) constantly increases.
Entrepreneurs have to overcome the law of navigation by developing a successful stratagem for finding just the right configuration of product features in an ever expanding maze of possibilities. In Mattel’s case, the solution lay in connecting up to an existing idea-space with a high degree of fitness in relation to the existing zeitgeist. As Mattel developed Barbie in the 1960s and early 1970s, a huge shift was taking place in how women defined themselves in relation to domesticity and sexuality. In many ways the outcome—balancing power and innocence, romance and marriage, sexual charm and tenderness—was mirrored in the Aphrodite myth that has played such a powerful role in shaping western conceptions of the feminine. Whether Mattel’s marketing team (led by Handler herself) consciously tapped into this idea-space, or whether they were responding to its embodiment in the culture, they shaped many of Barbie’s characteristics in accord with its dictates.
The fit get rich. The fundamental coherence between Barbie and the emerging zeitgeist, sustained by the timelessness of a Greek myth, served Mattel well (the doll is now a $4b global business). Other ways to solve the navigation problem include: exploiting accidents (penicillin, the transistor, Coke, vulcanized rubber, the Slinky toy, even Kandinsky’s initial conception of abstract art, all started out when an individual recognized the power embodied in a chance happening); tinkering (mountain bikes, the zipper, the phonograph, Watson’s matching up the DNA bases using cardboard cutouts); and making an analogy to an existing idea or artifact (Levis, Velcro, television, and the jogging bra).
However you get there, the trick is to allow the intelligence embedded in the space to guide your thinking. The more powerful the space, the more likely it is that, one way or another, you’ll be pulled towards it. Which brings us to the subject of hotspots in the networked idea-spaces of the extended mind.
Chapter 8—Think Different: Frank Gehry and the Law of Hotspots
Frank Gehry was awarded the Pritzker Prize, the Nobel of architecture, in 1981. The popular equivalent of this honor was his inclusion alongside the likes of Einstein and the Dalai Lama in Apple’s Think Different campaign. Why Gehry?
As the New York Times architecture critic Herbert Muschamp put it in his review of Gehry’s most celebrated building, the Guggenheim Museum Bilbao, the late 1970s marked the beginning of a period when “American architecture spectacularly lost its way.” If Gehry wasn’t single-handedly responsible for architecture’s revival of confidence and vibrant new creativity, following the stagnation of late modernism and an ineffectual rebellion by postmodernism, he certainly played a leading role in the revolution. The swooping, titanium-clad curves of his exteriors, coupled with the complex but always harmonious geometry of his interiors, have opened up a vast new space of possibilities for architecture to unfold in.
Hotspots, radiant with the energy of their embedded intelligence, draw creative minds to them. Crick was fascinated by Pauling’s introduction of the bold methods and theories of physics into the relative backwater of late 1940s biology. Jobs, with his Zen training, was a card-carrying member of the counter-culture community. Handler, inspired by an emergent feminism, dared to think about the place of sex in little girls’ fantasies about adult life. Gehry, who started out as an art student, and who counted among his friends many of Los Angeles’ leading pop artists, found in the idea-space of 1960s art a series of ideas—multiple meanings, viewer involvement, the integration of time and space, and a highly innovative use of materials—that he ably incorporated in his architecture.
Supremely sensitive to context, Gehry also discovered in LA another highly empowering source of embedded intelligence: the CAD/CAM systems used in the aerospace industry. Now Gehry had the technological means to build his first unquestioned masterpiece, the Guggenheim/Bilbao, in the process setting both American and international architecture on a bold new path.
The law of hotspots states that the potential transformative power of a hotspot relative to another idea-space is a function of fitness combined with distance. When Gehry began practicing his profession, architecture, still in the grip of a rigid modernism in thrall to the dictates of industrial production methods, was further away from art than at any time since the Renaissance. Correspondingly, despite modernism’s machine ethic, its methods of producing drawings and managing manufacturing processes and costs were hopelessly out of date. Gehry’s genius was to find the fit between art, CAD/CAM, and architecture, and integrate them in a glorious new synthesis.
Chapter 9—The Networked Dynamics of Risk: Printing and the Law of Small-World Networks
Suppose you’re a VC looking for the Next Big Thing. Investing in the future is always a risky business, and an awful lot of good ideas fail. So how do you pick? How do you learn to differentiate between likely winners and losers, between say eBay and Pets.com? When Johann Fust, a wealthy Mainz goldsmith and ambitious investor, was first approached in 1449 by Gutenberg in regard to becoming his partner in a business start-up, he must have asked himself that question. Was he really onto a good thing? Evidently Fust liked what he saw. Of course, being shown a working demo of a spanking new technology always impresses, and Gutenberg probably ran the numbers by him as well. In retrospect, the upside looked awfully good—by 1500 there were between 15 and 20 million printed books produced using movable type. In any event, Fust gave Gutenberg 800 gulden (a second round of financing would shortly follow), and the biggest NBT of all was off and running.
When Fust made his bet, neither he nor Gutenberg knew that Gutenberg’s invention wasn’t the first attempt at this type of printing. The Chinese had gotten there several centuries earlier, shortly to be followed by the Koreans. The fact that neither effort had become economically viable (scribes, the main form of competition, were cheaper and faster) might well have given Fust reason to reconsider. So why did Gutenberg’s press succeed in the market where they failed, becoming a massive tipping point that finally put a thousand-year old scribal institution out of business in just two decades?
The law of small-world networks says that in a dynamic network, a series of hubs whose interrelationships manifest high fitness narrowly define a potential emergent idea-space. The more strongly the hubs are present at a given time, the more likely the emergence of the new space. Feedback loops will cause the space to tip and expand exponentially.
As Brown and Duguid point out in The Social Life of Information, new technology, however great a creative leap it may represent, doesn’t per se guarantee breakthrough innovation. Successful uptake in the market typically requires a whole array of highly interrelated social, cultural, business, and ancillary technical factors—i.e., networked idea-spaces—to be aligned with one another. In the case of printing, no less than seven key factors were required to achieve a technologically effective, economically viable product. These included an alphabet, widespread use of paper, both stamping and high-volume molding technologies, the availability of investment capital, a guaranteed market (Church schools), and a standard the competition couldn’t meet (texts produced by scribes were full of copying errors). Previous attempts failed to achieve market viability because one or more of these necessary idea-spaces was lacking.
Gutenberg deserves credit for reinventing and improving an existing technology. But his real genius, abetted by Fust, was to have recognized that the necessary idea-spaces had finally come into alignment. The hubs these interlinked spaces formed, together with a series of feedback loops between them, created the space in which printing could finally take off. The virtual space they created also guided Gutenberg’s own thinking, from key elements of design to financing to how the new technology was marketed.
The law of small-world networks, often working in conjunction with laws such as spontaneous generation, navigation, hotspots, and the fit get rich, also played a role in the emergence of the home computer, the discovery of DNA, the significantly more rapid growth of Silicon Valley in the 1980s and 1990s as compared with the Boston area’s Rte. 128, and the explosive impact of the Beatles’ music during their first visit to the U.S.
Chapter 10—The Triumph of the Imagination: New Art, the New Economy, and the Law of Integration
In 1966, the Museum of Modern Art in New York did something it had never done before. It honored with a solo exhibition an artist not born in the previous hundred years. The English painter J.M.W. Turner was born in 1775, and yet his late canvases, pure washes of color depicting the radiant energy of sunrises and sunsets over water, could easily vie for attention alongside the latest pictures of the Abstract Expressionists. What fed Turner’s imagination, enabling him to leap far beyond his own time and place?
Although a Romantic, Turner was profoundly interested in Romanticism’s antithesis—industrial technology (especially steam power), and the rapidly expanding domain of 19th century science. Fully conversant with Faraday’s experiments in electromagnetism, he began depicting magnetic lines of force in his paintings. Gradually, mass dissolved into pure light, itself the visible sign of massless, radiant energy. Turner was the first artist to grasp the scientific truth about apparently solid objects, in the process initiating a profound and lasting change in how artists use color and represent visible reality. Yet he was able to integrate this radical discovery into the reigning Romantic ethos of his day, with its worship of natural beauty and pantheistic beliefs in the immanence of the divine in the material world.
The law of integration holds that a tipping point—i.e., the unanticipated emergence of a qualitatively new space that is sustainable and continues to grow over time—cannot be produced exclusively through the creation of a new idea-space; rather, it arises from the integration of an emergent space into an existing one. Turner’s late paintings seemed radical at the time (contemporary critics harshly rejected them), and yet part of their ability to impress themselves on modern artistic sensibilities arises from Turner’s integration of emerging scientific ideas into conventional Romantic pantheism, producing a dialectical tension that resurfaces in the spiritual dimension latent in the abstract color paintings of Mark Rothko, Barnet Newman, and their contemporaries. Correspondingly, Gehry integrated his new architectural ideas and techniques back into modernism’s commitment to the purity of materials and machine ethos; Barbie’s introduction of sex into the world of children’s dolls took place in the context of an age-old myth of the feminine.
Entrepreneurs ignore the law of integration at their peril, as the late but unlamented dot.com boom illustrates. It too seemed radically new, but quickly burned out. The tipping point promised by the so-called New Economy, whose mantra was New Rules, New Leaders, New Business, never really materialized. One of the main reasons is that most theorists and practitioners of the new digital economy explicitly declared that it had little or no connection with the old material economy. Atoms didn’t mix with bits and bytes, and such standard wisdom as the need to make a profit or avoid over-expansion was laughingly ignored. Lacking self-reinforcing feedback loops into the existing idea-space of the mainstream economy, the New Economy failed to tip, spun out of control, and disintegrated almost as rapidly as it had arisen.
Chapter 11—Poets, Robots, and the Law of Minimal Effort
The Longinian-Kantian conception of genius holds that all great achievement comes from the extraordinary mental powers of the individual. In the humanities, the towering genius of Shakespeare is often cited as a classic example of this. In 1920, T.S. Eliot wrote an essay in which he set out to undermine this view. The artist, Eliot claimed, lives in “a current of ideas in the highest degree animating and nourishing to the creative power.” In other words, artists draw their creativity from being immersed in rich cultural idea-spaces. Such spaces constitute a kind of collective cultural “mind” that the great artist comes to see as “much more important than Gutenberg his own private mind.” “How little each poet has to do” as a result, Eliot notes. Even Shakespeare, immersed in the immensely rich cultural, linguistic, and artistic environment of Elizabethan England, was able to exercise a real “economy of effort.”
The law of minimal effort has been implicit from the outset in our theorizing about the networked idea-spaces of the extended mind and the intelligence embedded there: The space of ideas thinks for you. This has been the mantra of this book. The imagination intuitively seeks out embedded intelligence existing in spaces outside itself in order to make creative leaps. The formation of new emergent idea-spaces that arise from this contact is shaped by the laws of dynamic networks, often working in conjunction with one another. The logic of imaginative thought is inherently non-linear.
As Andy Clark notes, we encounter this same logic at a much more mundane level in recent work in robotics. Increasingly, AI researchers and robot designers are abandoning the old linear, central processing model of cognition in favor of one in which intelligence is seen as embedded in the environment itself. Robots facing novel situations make the creative leap to new understanding not through huge amounts of internal processing, but by reacting to cues embodied in their surroundings. The result is that internal cognitive operations—the robot’s thinking process—is minimized. The exterior world is already intelligently structured, allowing the robot, like us, to be dumb in peace.
In the final analysis, the law of minimal effort comes down to saying that most of the time, the system does the work for you. It’s to be found operating in domains as diverse as the Cambrian explosion, perimenopause, Maya Lin’s design for the Vietnam Veteran’s War Memorial in Washington, D.C., and John Holt’s development of the idea of homeschooling.
Chapter 12—Leadership, Imagination, and the Art of the Long Bet
If there’s one thing most business leaders would agree on, it’s that we live in an increasingly complex and volatile business environment. In Confronting Reality: Doing What Matters to Get Things Right (Crown 2004), Bossidy and Charan pose a critical question:
How can you anticipate change before it’s too late? Is it really possible to know, in Wayne Gretsky’s famous phrase, not where the puck is but where it’s going to be? The answer is yes, but only if you learn how to look around corners by understanding the realities outside your walls in more breadth and depth than ever before.
Figuring out the future, never an easy accomplishment, is getting harder. The conventional response is: Do more analysis. But as we’ve seen, analytical reasoning won’t get you there. Making the creative leap into the future, whether in science, art, or business, takes imagination, intuition, and insight.
In previous chapters we’ve explored the foundations of an emergent new science of ideas that reveals how the laws of network dynamics, operating on the idea-spaces of the extended mind, delineate how the mind’s imaginative faculties achieve creative leaps. This final chapter offers some very practical advice to the creative among us (including not just business leaders but anyone bent on achieving a breakthrough in their field) to enable us to put these laws to good use. Precepts include: learning to recognize when your thinking is trapped in the wrong idea-space; assessing the potential fitness of an emerging hotspot with your own area of activities; anticipating potential tipping points; and learning to “read the world” in terms of networked idea-spaces.
The aim of the book has been to both challenge and enlarge on the core assumptions that characterize the prevailing western conception of mind: that the mind is inside the head, that intelligence is inherently linear, and that major creative achievement is the result of innate genius. Creative leaps, from the mundane level of everyday life to the extraordinary achievement of great men and women, come from surfing the idea-spaces of the extended mind, looking for opportunities to exploit the intelligence embedded there. The mind’s imaginative faculties jump far beyond the limits of its rational/analytical capabilities, piggybacking on the vast creative dynamics of the mind out there. If you’re up for the ride, the space of ideas, shaped by the laws of network dynamics, will do most of the thinking for you.
What do jazz musician Dave Brubeck, Apple's Steve Jobs, Barbie creator Ruth Handler, and architect Frank Geary all have in common? Not just that they are credited with some of the most inventive products and innovations of the last century — the classic jazz album Time Out, the iPod, Spain's spectacular Guggenheim Museum — but their stories are unique in the way these creative leaps came about. Each used imaginative intelligence for certain, yet were able to combine this intelligence with networks outside of their own minds to reach true creative breakthroughs. This type of creativity gives credence to the idea that not all brilliant breakthroughs come from the minds of individual geniuses. On the contrary, our world is made up of intelligent networked spaces that, if navigated correctly, can lead us to breakthrough ideas.