Emergence: The Connected Lives of Ants, Brains, Cities, and Software
By Steven Johnson. Scribner, 288 pages, $25.00
It's easy to see why there aren't more books like Steven Johnson's Emergence: Only Johnson knows how to write them. Johnson was a founder and editor of Feed, one of the Web's first and best "zines" (now moribund, unfortunately, thanks to the economic downturn). Feed aimed to show that there was no contradiction between maintaining high literary standards and creating online community, and it succeeded, in large part, because Johnson himself is both media savvy and a skilled writer. Johnson's first book, Interface Culture (1997), was probably the single most memorable volume to come out of the Internet explosion of the 1990s. It was an intellectually bold, often exhilarating read, full of unexpected perspectives on culture and digital media. The new book is exactly the volume Johnson needed to write next. It takes up the earlier arguments, expands them in the light of a body of fascinating material, and winds up being, if anything, still more of a tour de force.
If this book could be said to have a main character, slime mold would be the leading contender.
You get a feeling for what's to come from the book's first page, a diagram of a human brain positioned above a map of Hamburg. The two shapes are strikingly similar, which, as Johnson sets out to show, is no accident. Nature and society overflow with correspondences. To see, from Johnson's viewpoint, how such correspondences come about and how we have learned to recognize and, lately, make use of them entails a survey of ant life; Roman settlements; subways; Manchester England; the early work of Friedrich Engels; the career of Alan Turing; ants again; cybernetics; and video games--with a stop in there for how the "shrieking of the demons" in John Milton's Paradise Lost spurred one complexity theorist on to a major insight.
Johnson defines emergence as "the movement from low-level rules to high-level sophistication." Emergent systems are "not top-down. They get their smarts from below." Like the emergent systems it describes, the book starts simply, with a discussion of the one-celled creatures known as Dictyostelium discoideum, or slime mold. Johnson doesn't just begin with slime mold; he comes back to it again and again. If the book could be said to have a main character, slime mold would have to be it. To grasp the workings of Dictyostelium discoideum is, as Johnson takes no small delight in affirming, to effect a revolution in thinking. It is to finally correct the mental error that has for so long kept us from understanding why birds flock and liver cells don't turn into spleen cells. Johnson calls that error the "pacemaker hypothesis." The hypothesis assumes that complex behavior depends on some form of centralized authority. In the case of ants, it would be that the colony is governed by the queen. In the case of slime mold, it would be that the decision to cohere as a swarm is triggered by the dictates of alpha slime cells.
Both assumptions couldn't be further from the truth. The ant queen is kept literally in the dark, way underground, far from the decisions about foraging and fighting in which she plays no part. Similarly with slime cells: Their trademark behavior does consist of assembling into a swarm that crawls "across the garden floor, consuming rotting leaves and wood as it moves about," only to disintegrate back into individual units when conditions change. Slime mold manages this trick--what complexity theorists call a "phase change"--without benefit of a higher authority. "All slime mold cells," as researchers were puzzled to discover, "are created equal." They also equally obey certain rules. And they monitor one another's behavior constantly. Therefore, when the weather gets cool and food becomes abundant, each cell notices that the one and only slimy thing to do is to swarm suddenly. What it comes down to in the molecular fine print is a chemical that the cells emit. The more a cell senses that chemical, the more heartily it contributes to the chemical chorus. And what sufficient quantities of that chemical say in terms no slime cell can resist is: "Swarm."
Self-organizing behavior is no stranger to scientists today. But in 1969, when Evelyn Fox Keller and Lee A. Segel put it forward as an explanation for slime swarming, biologists were mystified. The idea of complexity resulting from bottom-up interactions had been explored in urban planning by Jane Jacobs and in mathematics by Alan Turing, among others. In fact, Turing's late musings about how complex organisms could arise from simple cells jogged Keller into conceiving the new slime paradigm. But for the most part, biologists remained prejudiced in favor of cellular authority. For them, complex behavior was an orchestra led by its conductor rather than, say, a string quartet whose members listen to one another well. It was no small matter that biologists were stuck on pacemakers; it meant they really didn't have a handle on how the governing idea of their discipline--Darwinism--actually worked. In a sense, it was as if they held back from admitting the full implication of natural selection: namely, that it requires no outside agitators, no presiding spirits, no--as the philosopher Daniel Dennett puts it--skyhooks. In fact, evolution is the best possible illustration of what Johnson means when he writes about "complex adaptive systems that display emergent behavior."; Evolution is the showcase example of simple things becoming more complex, dull things becoming smarter under pressure to survive.
It took a while, but biologists caught on. It didn't hurt that computer scientists soon learned to model adaptive behavior on-screen. One of the more amazing stories that Johnson tells concerns Danny Hillis's experiment with genetic algorithms. Unlike traditional computer programs, which are static, genetic algorithms change over time. The ones best suited to solving a given problem are allowed to survive and, in effect, to reproduce; the others, in a digital simulation of extinction, are deleted. Hillis's idea was to set some undistinguished bits of software loose on the problem of sorting data. Sorting data--in alphabetic order or by any other index--is a task that takes even computers a lot of time when the data set is large enough. Not surprisingly, computer scientists have devoted considerable energy to devising the most efficient sort, the one that can get the job done with the fewest computer instructions. In the Hillis experiment, programs that managed the job best passed their code on to a next generation, after being subjected to a bit of random mutation (à la cosmic rays) and code-swapping (à la sex) with other promising miniprograms. Hillis, a founder of Thinking Machines Corporation, had the company's supercomputers at his disposal and was able to churn through thousands of evolutionary cycles in mere seconds.
Hillis found that the most efficient routine achieved a 72-step sort, as compared with the 60 steps required by the fastest human-coded algorithms. Not satisfied with this gap, however, he introduced predators into the simulation. Predators didn't allow programs to rest on 72-step laurels; they forced the sorting routines to risk getting slower on the chance of getting faster. (As the poet Rainer Maria Rilke has observed, "abiding is nowhere.") With predators at their heels, some routines drove on to a 62-step sort. The astonishing thing about those 62-steps was that Danny Hillis couldn't make heads or tails of them. Hillis had figured out how to link up 64,000 cheap microprocessors so that running in parallel they were competitive with the best supercomputers Cray or Fujitsu had to offer. But how a mere 62 lines of code whose function was already known did their job remained mysterious to him. The simulation seemed to have goosed into being an utterly alien approach to problem solving.
So much for the old adage that a program can do only what its programmers tell it to do. From here on, in Johnson's view, programs that are so constrained will be considered the dullards of software. The really interesting problems will be treated to genetic algorithms. Programmers will adopt the Hillis method: "Mix, mutate, evaluate, repeat." And be amazed. This is how, for example, in 1999 the computer scientist Marco Dorigo approached the notoriously difficult "traveling salesmen" problem. What is the shortest route between n stops that goes through each of them once and once only? When n gets large enough, as happens on telephone and computer networks, there's no surefire answer, only educated guesswork. Dorigo found that genetic algorithms guess better than humans can. Johnson reports that France Telecom, British Telecommunications, and MCI now let emergent software solve their routing problems.
Johnson calls such applications examples of artificial emergence and thinks that we are on the threshold of an age that will be defined by them. We now not only understand the ways of slime mold, we can simulate them; and beyond that, we can harvest the results. In Johnson's view, the influence of artificial emergence is or soon will be making itself felt not only on software but in politics, mass media, corporate structure, and the shape of the movement against globalization. In phrases calculated to set off echoes, he writes: "Up to now, the philosophers of emergence have struggled to interpret the world. But they are now starting to change it."
Johnson's account of the prehistory of emergence--how it itself has emerged from urban planning, entomology, information theory, cell biology, neuroscience, and other disciplines to became a discipline of its own--is a masterful piece of storytelling, but only a sort of warm-up for him. Artificial emergence is his real terrain. Feed's experiments with interface design and online community gave him experience not only in studying but in shaping it. The author's experience as a maker of the phenomena he describes distinguishes Emergence from a book like James Gleick's Chaos: Making a New Science, to which it in other respects bears comparison.
Johnson's discussion of artificial emergence elaborates on points he made in Interface Culture. There he had claimed great things for the computer interface: It was about to became the platform for a twentieth-first century avant-garde that would filter and interpret reality for us as novelists did for the nineteenth century. The "Victorians," he wrote, "had writers like Dickens to ease them through the technological revolutions of the industrial age." The computer interface would similarly guide us through "the virtual cities of the twenty-first century."
In the years since Interface Culture, I, for one, have wondered if this prediction was another of those flights of optimistic fancy, like the notion that the Dow Jones average would plateau at 36,000, that had best be forgotten in the light of new realities. After all, despite hits from the Justice Department, Microsoft Windows still straddles the desktop like an ancien régime. No sign of emergence there: Microsoft is one of the places the pacemaker hypothesis holds true. And not even the most fervent supporters of the open-source alternative to Windows would count the computer interface as among it strengths. Where, then, is the Johnsonian avant-garde?
As Emergence makes abundantly obvious, it is flourishing in the world of games, such as SimCity and its sequel The Sims, and in the articulation of online communities, such as Slashdot. Lest video games be derided as inconsequential as compared to Windows and the novel, Johnson stresses the opposite view: Video games are poised to replace pornography itself as the leading engine of technological development. "Because part of their appeal lies in their promise of new experiences," he writes, "and because their audience is willing to scale formidable learning curves in pursuit of those new experiences, games often showcase cutting-edge technology before the tech makes its way over to the red-light district. Certainly that has been the case with emergent software."
In Emergence, Johnson has put some powerful ideas through a literary feedback loop that will, in all likelihood, accelerate and magnify their effect on our culture. Does he occasionally display some of the tics and tremors that come with believing you are hot on the trail of a theory of everything? Absolutely. He thinks emergent software, and not, say, more public transportation, is the solution to traffic jams. "Make the traffic lights smart," he writes. "You can conquer gridlock by making the grid itself smart." This is not the technorealism Johnson was once known for espousing as a middle road between technophiles and technophobes. Nor is it necessarily technorealistic to imagine that Bach-like music composed by emergent code will lack for nothing to seem to us as "sweet" as Bach's own works. But these aberrations or, in the second case, serious complications, which call for more reflection, in no way compromise the value of the book.
Interface Culture gave me food for thought for years. I expect the same from Emergence. I keep coming back to that sorting routine Danny Hillis couldn't parse. That was only 62 lines of code. What 10-million-line piece of emergent intelligence now slouches toward a compiler to be born? Will it be a rough beast at least vaguely familiar to us? In other words, will it illuminate an aspect of intelligence latent in the human mind? Or will it prove to be as alien and inscrutable as a Hillis sort?
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