Darwin Among the Machines (36 page)

Read Darwin Among the Machines Online

Authors: George B. Dyson

The step-by-step expression of evolutionary intelligence, compared to the human attention span, is immeasurably slow. The evidence may become inescapable when speeded up. The invisible web of connections that bind an ecology—biological, computational,
or both—into a living whole begins to move at a visible pace when the machines evolve from year to year, new generations of software are exchanged in minutes, and control is exercised from one microsecond to the next. Samuel Butler saw that the intelligence of evolution and the intelligence of human beings were heading on a collision course. Butler knew, as did Barricelli, that our definition of intelligence is so anthropocentric as to be next to useless for anything else. “Nothing, we say to ourselves, can have intelligence unless we understand all about it—as though intelligence in all except ourselves meant the power of being understood rather than of understanding,” he wrote. “We are intelligent, and no intelligence so different from our own as to baffle our powers of comprehension deserves to be called intelligence at all. The more a thing resembles ourselves, the more it thinks as we do—and thus by implication tells us that we are right, the more intelligent we think it; and the less it thinks as we do, the greater fool it must be; if a substance does not succeed in making it clear that it understands our business, we conclude that it cannot have any business of its own.”
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As Darwinism was perceived as iconoclasm by the church, so any attempt to attribute intelligence to evolutionary processes is viewed with suspicion by those of orthodox Darwinian faith. Butler and his followers have not stopped at seeking recognition for species-level intelligence, but keep attempting to invoke unorthodox levels of life and mind: “The only thing of which I am sure is, that the distinction between the organic and inorganic is arbitrary; that it is more coherent with our other ideas, and therefore more acceptable, to start with every molecule as a living thing, and then deduce death as the breaking up of an association or corporation, than to start with inanimate molecules and smuggle life into them.”
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Contraband passes across the boundaries between life and nonlife as freely as between intelligence and nonintelligence. The traffic goes both ways, attributing life and intelligence to processes below our own level as well as to those above. Everywhere we look things are turning out to be more intelligent and more alive than they once seemed. The more we come to understand the information-processing systems epitomized by the human brain, the more we find them to be functioning as evolutionary systems, and the more we come to understand evolutionary systems, the more we discover them to be operating as information-processing machines.

Our faith in the intelligence of self-organizing, complex adaptive systems is reminiscent of William Paley's faith in the argument from design. Where we see the emergence of order, Paley saw the hand of
design. His protagonist, stumbling upon a watch, finds it utterly impossible “that there existed in things a principle of order, which had disposed the parts of the watch into their present form and situation. He never knew a watch made by the principle of order; nor can he even form to himself an idea of what is meant by a principle of order, distinct from the intelligence of the watchmaker.”
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Comparing watches, we find that Butler's watch was designed from within; Paley's watch was designed from without; Darwin's watch was designed by the accumulation of sheer coincidence over time.

To guard against mechanical error, eighteenth-century navigators carried three chronometers. When one chronometer differed, the other two were assumed to be correct. When you have three watches and no two of them agree, there is no way of telling which, if any, is right. The three differing interpretations of the argument from design given by Butler, Paley, and Darwin correspond loosely to the three different approaches to the design of complex computer systems represented by Leviathan, SAGE, and Pandemonium in 1959. The Romes' Leviathan embodied Butler's faith in nature's mysterious ability to intelligently organize its own design. The air force's SAGE embodied Paley's faith in a centralized, overruling intelligence that administered all instructions from above. Selfridge's Pandemonium embodied Darwin's faith in a tangled bank of subprograms flowering by natural selection out of computational mud.

Over forty years of software development, none of the three approaches has proved entirely wrong. Leviathan attempted a black-box approach to building systems that accumulate empirical knowledge through mechanisms whose details the designer doesn't necessarily understand—a process invoked, if not always admitted, by the authors of most large assemblages of code. SAGE's authoritarian, Grand Central Station approach to system development descended directly, via IBM, to the operating systems that ruled the mainframes of the 1970s and govern the desktops of today. Pandemonium descended, with modification, to the fertility of modular programming and the object-oriented languages and quasi-intelligent agents that are now replicating across the network as a whole. We have transcended the old argument over whether artificial intelligence should be built from linear, sequentially coded processes or incubated within massively parallel webs. Is life the result of linear strings of code-bearing DNA or the result of three-dimensional proteins swimming in auto-catalytic soup? The answer is not one or the other, but both.

The evolution of a diversifying computational ecology from simple strings of 0s and 1s embodies certain ideas in mathematical
logic concerning how formal systems evolve into higher types. “I am twisting a logical theorem a little,” admitted John von Neumann in a lecture on self-reproducing systems given in December 1949, “a theorem of Gödel that the next logical step, the description of an object, is one class type higher than the object and is therefore asymptotically longer to describe.”
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Evolution is a recursive process, and given the power of recursive functions, we should not be surprised at the complexity and intelligence exhibited by a language or genetic system operating repeatedly on itself. “The possibility of producing an infinite sequence of varieties of descendants from a single program is methodologically significant in a manner which might interest biologists more than artificial intelligencers,” remarked logician John Myhill in 1964. “It suggests the possibility of encoding a potentially infinite number of directions to posterity on a finitely long chromosomal tape.”
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In this lies the frustration, and the power, of coded instructions—you cannot always predict the results.

As von Neumann explained to the Hixon Symposium in 1948, “this fact, that complication, as well as organization, below a certain minimum level is degenerative, and beyond that level can become self-supporting and even increasing, will clearly play an important role.”
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This statement is less an echo of Charles Darwin's
Origin of Species
of 1859 than of Robert Chambers's
Vestiges of the Natural History of Creation
, published in 1844: “The idea, then, which I form of the progress of organic life upon the globe—and the hypothesis is applicable to all similar theatres of vital being—is, that the simplest and most primitive type, under a law to which that of like-production is subordinate, gave birth to the type next above it, that this again produced the next higher and so on to the very highest, the stages of advance being in all cases very small.” Chambers, writing anonymously and without a scientific reputation to protect, added, “and probably this development upon our planet is but a sample of what has taken place, through the same cause, in all the other countless theatres of being which are suspended in space.”
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What leads organisms to evolve to higher types? (Darwinian evolution, as Stephen J. Gould, among others, has pointed out, does not “progress” toward greater complexity, but Darwinian evolution, plus symbiogenesis, does.) Is a global electronic intelligence something new, or merely the materialization, on a faster scale, of an intelligence that has existed all along? Natural selection is based on the death, or favored survival, of individuals, and its speed is limited by the time it takes to proceed from one generation to the next. In the age of information the pace of orthodox Darwinism is being left
behind. Darwinian evolution, in one of those paradoxes with which life abounds, may become a victim of its own success, unable to keep up with non-Darwinian processes that it has spawned. Erasmus Darwin may turn out to be right.

We have been moving in this direction for some time. “Cultural patterns are in a sense a solution of the problem of having a form of inheritance which doesn't require killing of individuals in order to evolve,” observed Nils Barricelli in 1966. “You can evolve them by selecting for cultural patterns, and in this respect it would be a much faster evolutionary phenomenon.”
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The same goes for digital organisms, which do not need to die in order to evolve, although, if memory is limited, the threat of death may help. It also applies to biochemical circuits, such as the molecular hypercycles that preceded the origin of life, or to the topology of an electronic network—a pattern of connections that persists over time, transcending the individual lifetimes of the components from which it is formed. Individual cells are persistent patterns composed of molecules that come and go; organisms are persistent patterns composed of individual cells that come and go; species are persistent patterns composed of individuals that come and go. Machines, as Butler showed with his analysis of vapor engines in 1863, are enduring patterns composed of parts that are replaced from time to time and reproduced from one generation to the next. A global organism—and a global intelligence—is the next logical type, whether we agree with the diagnosis, the terminology, or the assumption of life and intelligence or not.

“I have been trying to think of the earth as a kind of organism, but it is no go,” wrote physician Lewis Thomas in 1971. “I cannot think of it this way. It is too big, too complex, with too many working parts lacking visible connections. The other night, driving through a hilly, wooded part of southern New England, I wondered about this. If not like an organism, what is it like, what is it most like? Then, satisfactorily for that moment, it came to me: it is most like a single cell.”
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What appeared to be a single cell in 1971 appears to be something more than a single cell today. Contemplating an ant colony, Thomas wrote that “you begin to see the whole beast, and now you observe it thinking, planning, calculating. It is an intelligence, a kind of live computer, with crawling bits for its wits.”
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Comparing human beings to the ants, Thomas observed that “we are linked in circuits for the storage, processing, and retrieval of information, since this appears to be the most basic and universal of all human enterprises. It may be our biological function to build a certain kind of Hill.”
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With computer networks still in a tenuous, experimental stage, it was
nonetheless obvious to Lewis Thomas that “all 3 billion of us are being connected by telephones, radios, television sets, airplanes, satellites, harangues on public-address systems, newspapers, magazines, leaflets dropped from great heights, words got in edgewise. We are becoming a grid, a circuitry around the earth. If we keep at it, we will become a computer to end all computers, capable of fusing all the thoughts of the world.”
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As a physician and biologist, Lewis Thomas placed the health of human beings and their fellow creatures first. “The most profoundly depressing of all ideas about the future of the human species is the concept of artificial intelligence,” he later wrote. “That these devices will take over and run the place for human betterment or perhaps, later on, for machine betterment, strikes me as wrong in a deep sense, maybe even evil. . . . Machines like this would be connected to each other in a network all around the earth, doing all the thinking, maybe even worrying nervously. But being right all the time.”
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Thomas's caution is understandable. On another level, the level of an earth that “seen from the right distance, from the corner of the eye of an extraterrestrial visitor . . . must surely seem a single creature, clinging to the round warm stone, turning in the sun,”
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his concerns may be misplaced, or at least no more unsettling than the tyranny of any nervous system over an individual organism's component cells. As Nils Barricelli demonstrated with the growth of his numerical symbioorganisms at the Institute for Advanced Study in 1953, safety in numbers is a fact of life—perhaps
the
fact of life from which all other facts of life evolved. “An organic being is a microcosm,” observed Charles Darwin in 1868, “a little universe, formed of a host of self-propagating organisms, inconceivably minute, and numerous as the stars.”
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From atoms through metazoans to spiral galaxies, the laws of nature form a hierarchy we have yet to comprehend. The ten million transistors now engraved on a single square centimeter of our earth share their digital lifeblood with billions of fellow microprocessors, weaving a fibrous cocoon that spans the globe with a web of light. “If you take a cubic foot of sea water, you might very well find a small flounder in it,” Philip Morrison pointed out. “That is hopelessly far from the steady-state. . . . In a cubic mile you could find a submarine full of crew members and software, a still more complex configuration.”
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This hierarchy extends in both directions: in a cubic centimeter you might find a protozoan; in a cubic astronomical unit you might find a single collective organism, clinging to a warm planet, turning slowly in the sun.

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