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What connects these developments? Imagine a kind of conceptual tracking shot of life two or three years from now, a movement from scale to scale—like the wonderful Charles and Ray Eames film, Powers of Ten, which starts with a view of the Milky Way and steadily zooms all the way to a person lying in a park in Chicago, and then all way to the subatomic particles contained within that person’s hand.
Only in our long zoom do we find, at each scale, the same behavior repeating itself again and again. Begin on the scale of the city itself, its neighborhoods pulsing and thriving, as they have for centuries, sending signals out to the world, and drawing human beings into those neighborhoods, like massive global magnets. The flow of people through the city is now regulated by an intelligent traffic network, evolving and learning in response to patterns of automobile movement. You or I live in one of those immense systems, contributing to its continued development the way a single slime mold cell contributes to the larger aggregation—and as part of our life in that city we entertain ourselves by simulating the self-organizing energy of city life by playing a game on our computer screen, building virtual neighborhoods collectively with thousands of other networked players all across the world. On the scale of the city, and the scale of the screen, our lives embrace the powers of emergence.
Now zoom in another level, to the individual bits of information that convey our virtual city-building to our networked compatriots. These too find their way across the infosphere by drawing on the distributed logic of swarm behavior, building their complex itineraries from below. The network is smart, but its intelligence is the intelligence of an ant colony, not a centralized state. And how did these new smart networks come into being? Drop down one more level on the chain, to the neural networks of the human mind, and their extraordinary aptitude for pattern recognition. The mind of a researcher in Brussels sees a connection between the collective behavior of ant colonies and the routing problems endemic to large-scale information networks—sees the connection because his brain contains a marvelously agile device for detecting shared patterns in disparate fields. That device runs on its own kind of swarm logic, with no central office in command. One kind of decentralized intelligence (the human brain) grasps a new way to apply the lessons of another decentralized intelligence (the ants), which then serves as a platform (the network) for the transmission of another kind (the virtual cities), which we enjoy while sitting safely in our apartments in the neighborhoods of the planet’s largest man-made self-organizing system (the real city). It is emergence all the way down the chain.
Can that chain be extended in new directions—both on the atomic scale of digital information and the macroscale of collective movements? Will computers—or networks of computers—become self-aware in the coming years, by drawing upon the adaptive open-endedness of emergent software? Will new political movements or systems explicitly model themselves after the distributed intelligence of the ant colony or the city neighborhood? Is there a fourth stage in the developing web of emergence that takes us beyond the mind readers into something even more lifelike? Is there a genuine global brain in our future, and will we recognize ourselves in it when it arrives?
Certainly the world has never been better prepared for these developments to become reality; if we don’t enter the fourth phase of emergence in the coming decades, it won’t be for lack of trying. But it is both the promise and the peril of swarm logic that the higher-level behavior is almost impossible to predict in advance. You never really know what lies on the other end of a phase transition until you press play and find out. That is the lesson of Gerald Edelman’s recipe for simulating a flesh-and-blood organism: you set up a system of various pattern-recognition devices and feedback loops, connecting the virtual organism to a simulated environment. And then you see what happens.
Even the most optimistic champions of self-organization feel a little wary about the lack of control in such a process. But understanding emergence has always been about giving up control, letting the system govern itself as much as possible, letting it learn from the footprints. We have come far enough in that understanding to build small-scale systems for our entertainment and edification, and to appreciate more thoroughly the emergent behavior that already exists at every scale of our lived experience. Are there new scales to conquer, new revolutions that will make the top-down revolutions of the industrial age look minor by comparison? On the hundred-year scale, or the scale of millennia, there may be no question more interesting, and no question harder to answer.
STEVEN JOHNSON is the bestselling author of Interface Culture, Emergence, and Everything Bad Is Good for You as well as a columnist for Discover and a contributing editor at Wired. He lives in New York City with his wife and two sons, and can be reached via the Web at www.stevenberlinjohnson.com.
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NOTES
Without any apparent: “When Slime Is Not So Thick,” BBC News, August 27, 2000.
Anyone who has ever: Indeed, we know now that we are closer to the slime mold colonies that we initially thought: “Bacteria of several different kinds got together, more than a thousand million years ago, to form the ‘eucaryotic cell.’ This is our kind of cell, with a nucleus and other complicated internal parts, many of them put together from intricately folded internal membranes, like the mitochondria which I briefly pointed to in Figure 5.2. The eucaryotic cell is now seen as derived from a colony of bacteria. Eucaryotic cells themselves later got together into colonies.” Dawkins, 1996, 286–87.
If we could: “It is, in fact, scarcely more than a philosophical anticipation of the cell theory, according to which most of the animals and plants of moderate size and all of those of large dimensions are made up of units, cells, which have many if not all the attributes of independent living organisms. The multicellular organisms may themselves be the building bricks of organisms of a higher stage, such as the Portuguese man-of-war, which is a complex structure of differentiated coelenterate polyps, where the several individuals are modified in the different ways to serve the nutrition, the support, the locomotion, the excretion, the reproduction, and the support of the colony as a whole.” Wiener, 155.
“I was at”: Interview with Evelyn Fox Keller, conducted July 2000.
While the field: “Alan was familiar with Schrödinger’s 1943 lecture, ‘What Is Life,’ which deduced the crucial idea that genetic information must be stored at molecular level, and that the quantum theory of molecular bonding could explain how such information could be preserved for thousands of millions of years. At Cambridge, Watson and Crick were busy in the race against their rivals to establish whether this was really so, and how. But the Turing problem was not that of following up Schrödinger’s suggestion, but that of finding a parallel explanation of how, granted the production of molecules by the genes, a chemical soup could possibly give rise to a biological pattern. He was asking how the information in the genes could be translated into action. Like Schrödinger’s contribution, what he did was based on mathematical and physical principle, not on experiment; it was a work of scientific imagination.” Hodges, 431.
1, 1, 2, 3, 5, 8, 13, 21, 34, 55, 89 …
in which each term was the sum of the previous two. They occurred in the leaf arrangement and flower patterns of many common plants, a connection between mathematics and nature which to others was a mere oddity, but to him deeply exciting.” Ibid., 207.
What if there: Evelyn Fox Keller, “The Force of the Pacemaker Concept in Theories of Aggregation in Cellular Slime Mold,” in Reflections on Gender and Science (Yale University Press, 1996).
Indeed, the pacemaker: Resnick, 122.
reigning model: “[The Keller-Segel model] received very little attention, and no critique ever appeared. Instead, attention shifted away from field-theoretic models toward models of the individual cell. In part, this shift of interest may have been due to the failure of the Keller-Segel model to predict wavelike global oscillation of the aggregation field… . But even more, the shift was probably due to a philosophical antipathy to holistic models.” Garfinkel, 187.
You can think: “The process of slime-mold aggregation is now viewed as one of the classic examples of self-organizing behavior.” Ibid., 51.
It also unearthed: In Death and Life of Great American Cities, Jane Jacobs describes the decentralizing mentality this way: “In principle, these are much the same tactics as those that have to be used to understand and to help cities. In the case of understanding cities, I think the most important habits of thought are these:
“1. To think about processes;
“2. To work inductively, reasoning from particulars to the general rather than the reverse;
“3. To seek for ‘unaverage’ clues involving very small quantities, which reveal the way larger and more ‘average’ quantities are operating.” P. 440.
Marvin Minsky in: Marvin Minsky, The Society of Mind.
In a more technical: Ilya Prigogine and G. Nicolis, Exploring Complexity.
By watching the: “Understanding something in just one way is a rather fragile kind of understanding. Marvin Minsky has said that you need to understand something at least two different ways in order to really understand it. Each way of thinking about something strengthens and deepens each of the other ways of thinking about it. Understanding something in several different ways produces an overall understanding that is richer and of a different nature than any one way of understanding.” Resnick, 103.
Self-organization became: The Santa Fe Institute is of course most famous for its work in the related field of “chaos theory.” “As noted by Farmer and Packard (1986), the study of self-organizing systems is, in some ways, the ‘related opposite’ of the study of chaos: in self-organizing systems, orderly patterns emerge out of lower-level randomness; in chaotic systems, unpredictable behavior emerges out of lower-level deterministic rules.” Ibid., 14.
But in the: Jane Jacobs describes these systems as “dynamically stable systems”: “Every kind of system that is neither inert nor disintegrated. This includes all living systems: ecosystems, organisms, cells composing organisms, microorganisms. It also includes many inanimate systems: rivers, the atmosphere, the crust of the earth. Human settlements, business enterprises, economies, governments, nations, civilizations—they’re all dynamically stable systems. Jacobs, 2000, 85.
The first section: “The dynamics of ant colony life has some features in common with many other complex systems: Fairly simple units generate complicated global behavior. If we knew how an ant colony works, we might understand more about how all such systems work, from brains to ecosystems. Because we don’t yet comprehend any natural complex system, I think it is premature to say how general a theory we may eventually achieve. The intriguing question about task allocation is how might an ant react to local events, in a simple way, that in the aggregate produces colony behavior? The same kinds of questions come up, over and over, throughout biology: How do neurons respond to each other in a way that produces thoughts? How do cells respond to each other in a way that produces the distinct tissues of a growing embryo? How do species interact to produce predictable changes, over time, in ecological communities? These are the big, general questions of biology, and many of us dream that when we have the answers, from different fields of biology, it will be possible to see similar processes at work from cells to ecosystems.” Gordon, 141–42.
The epic clash: Norbert Wiener makes a parallel observation in Cybernetics: “This desire to produce and to study automata has always been expressed in terms of the living technique of the age. In the days of magic, we have the bizarre and sinister concept of the Golem, that figure of clay into which the Rabbi of Prague breathed life with the blasphemy of the Ineffable Name of God. In the time of Newton, the automaton becomes the clockwork music box, with the little effigies pirouetting stiffly on top. In the nineteenth century, the automaton is a glorified heat engine, burning some combustible fuel instead of the glycogen of the human muscles. Finally, the present automaton opens doors by means of photocells, or points guns to the place at which a radar beam picks up an airplane, or computes the solution to a different equation.” Wiener, 39–40.
“And then we”: Interview conducted with Gordon, September 1999.
“It would be”: Gordon, 117.
The harvester ants: As the legendary biologist W. D. Hamilton argued in a famous paper from 1964, the social cohesion of ant colonies is interestingly tied to their genetics: while you share on average half of your genes with your siblings, the sister ants that populate a colony share three-quarters of their genes, due to a complicated process of sex determination in ant societies. Those shared genes imply a greater communal interest in preservation—even greater than the connection between parent and child. Being in the same “genetic boat” tends to lead toward greater cooperation: “Whether you are a bunch of genes or a bunch of memes, if you’re all in the same boat you’ll tend to perish unless you are conducive to productive coordination. For genes, the boat tends to be a cell or a multicelled organism or occasionally, as we’ll see shortly, a looser grouping, such as a family; for memes, the boat is often a larger social group—a village, a chiefdom, a state, a religious denomination, Boy Scouts of America, whatever. Genetic evolution thus tends to create smoothly integrated organisms, and cultural evolution tends to create smoothly integrated groups of organisms.” Wright, 257.
In other words: The distinction between the colony’s being dependent on the queen, and being actually controlled by her, has been obscured by some commentators drawing on insect societies as a way of thinking about human social organization. “Apart from human communities, war exists only among the social insects, which anticipated urban man in achieving a complex community of highly specialized parts.
“As far as external observations can show, one certainly does not find religion or ritual sacrifice in these insect communities. But the other institutions that accompanied the rise of the city are all present: the strict division of labor, the creation of a specialized military caste, the techniques of collective destruction, accompanied by mutilation and murder, the institution of slavery, and even, in certain species, the domestication of plants and animals. Most significant of all, the insect communities that exhibit these traits boast the institution I have taken to be central in this whole development: the institution of kingship. Kingship, or rather, its feminine equivalent, queenship, has been incorporated as a supreme biological fact in these insect societies; so that what is only a magic belief in early cities, that the life of the whole community depends on the life of the monarch, is an actual condition in insectopolis. On the queen’s health, safety, and reproductive capacity the continued existence of the hive does in fact depend. Here and only here, does one find such organized collective aggression by a specializ
ed military force as one finds first in the ancient cities.” Mumford, 1961, 46.
This constitutes one: Information about the history of Manchester from Marcus, 5–6.
“From this foul”: Quoted in Marcus, 15. “Considering this new urban area on its lowest physical terms, without reference to its social facilities or its culture, it is plain that never before in recorded history had such vast masses of people lived in such a savagely deteriorated environment, ugly in form, debased in content. The galley slaves of the Orient, the wretched prisoners in the Athenian silver mines, the depressed proletariat in the insulae of Rome—these classes had known, no doubt, a comparable foulness; but never before had human blight so universally been accepted as normal: normal and inevitable.” Mumford, 1961, 474.
His three years: “ … it is difficult to conceive of how Engels could have made this exceptionally profound and enduring investment of himself had there not been much in the past on which he could continue to rely. On the one hand, he was a young man intent upon burning his bridges behind him. On the other, he knew in some part of himself that those bridges were built of fireproof material. We can put it another way. It does not detract too much from the existential reality of his decision to say that he was jumping into the abyss with a parachute. Or perhaps it does; perhaps that is one of the ways of distinguishing between the qualities of existential and historical choices in their classical modes, between the post-Hegelian Kierkegaard and the post-Hegelian Marx and Engels.” Marcus, 128.
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