Excerpt from my book Machine Nature
Science and engineering have traditionally proceeded along separate tracks. The scientist is a detective who’s up against the mysteries of Nature: He analyzes natural processes, wishing to explain their workings, ultimately seeking to predict their future behavior. Scientists ask questions such as: What goes on inside the Sun? And how long will it keep on burning? How does the weather system work? And how can we predict whether it will rain tomorrow or not? What are the fundamental physical laws that underpin the workings of the known universe?
The engineer, on the other hand, is a builder: Faced with social and economic needs, she tries to create useful artifacts. Engineers ask questions such as: How can we build a car with a cruising speed of 150 kilometers per hour, a fuel consumption of 20 kilometers per liter, and a price tag of no more than $8000? How do we design a computer chip that is twice as fast as the fastest extant chip? How can we build an autonomous lawn mower? “To put it briefly,” wrote Lewis Wolpert in The Unnatural Nature of Science, “science produces ideas whereas technology results in the production of usable objects.” And if I may add my own little epigram, science is about making sense whereas engineering is about making cents ...
In a chapter entitled “Technology is not Science,” Wolpert discussed the differences between the two, noting that technology is very much older than science, and that science did almost nothing to aid technology until the nineteenth century. “Technology may well have used a series of ad hoc hypotheses and conjectures, but these were entirely directed to practical ends and not to understanding,” he wrote. Humans have been able to construct artifacts — such as tools and arms — and improve their existence via agriculture and animal domestication thousands of years before the arrival of modern science (in the sixteenth and seventeenth centuries). Though engineers have only recently begun to put science to use, scientists had always relied on the existing technology. To quote Wolpert: “Science by contrast has always been heavily dependent on the available technology, both for ideas and for apparatus. Technology has had a profound influence on science, whereas the converse has seldom been the case until quite recently.”
The emergence of technology long before science is not at all surprising. “The goals of the ordinary person in those times,” wrote Wolpert, “were practical ends such as sowing and hunting, and that practical orientation does not serve pure knowledge. Our brains have been selected to help us survive in a complex environment; the generation of scientific ideas plays no role in this process.” Thomas S. Kuhn considered science and technology in one of the most influential works in the philosophy of science, The Structure of Scientific Revolutions, writing: “Just how special that community must be if science is to survive and grow may be indicated by the very tenuousness of humanity’s hold on the scientific enterprise. Every civilization of which we have records has possessed a technology, an art, a religion, a political system, laws, and so on. In many cases those facets of civilization have been as developed as our own. But only the civilizations that descend from Hellenic Greece have possessed more than the most rudimentary science. The bulk of scientific knowledge is a product of Europe in the last four centuries. No other place and time has supported the very special communities from which scientific productivity comes.” So perhaps we should count ourselves lucky to have science at all!
During the twentieth century the use of scientific knowledge in advancing the state of the art of our technology has picked up quite dramatically. Today all but the simplest artifacts rest on strong scientific foundations, everything from computer chips to automobile tires, through T-shirts, sugarless bubble gum, and space shuttles.
Science and engineering go hand in hand nowadays, both drinking from and helping to fill the other’s fountain. We’ve seen how engineers not only apply our current scientific understanding of Nature in order to build better artifacts, but are indeed coming full circle, trying to make these objects more Naturelike. Biology serves as a source of inspiration, with processes such as evolution, learning, and ontogeny implemented in artificial media. Nature can even be directly co-opted for engineering purposes, as with the use of DNA molecules to solve problems in computing.
The betrothal of science and engineering, and the ensuing period of blissful courtship, have finally led, in my opinion, to marriage. I believe that the recent years have seen the rise of a new kind of professional (and profession): the scigineer, a combination of both scientist and engineer, holding a test tube in one hand and a proverbial slide rule in the other.
What is a scigineer? Let me go about explaining this by way of example. In Chapter 2, we saw how computer programs in the form of trees can be evolved, noting that evolution tends to produce “spaghetti” programs: huge trees with lots of weird branches and offshoots. If the program works to your satisfaction, you can of course simply go ahead and use it; if you want to understand what makes it tick, though, then you’re in a position that’s rather like that of a biologist trying to decode our own program (the human genome). We even noted that when you delve into these evolved programs, you frequently find loads of “junk”: computer code that is of no use at all, a situation which is similar to Nature. Our genomes also contain junk code: unused portions of our DNA program.
The scigineer has two hats — that of a scientist and that of an engineer — which she constantly alternates. First, she puts on the engineer’s hat, picks up her slide rule, and sets the stage, say, for the evolution of computer programs; then, she puts on the scientist’s hat and the white coat, setting out to analyze the creatures (programs) that have emerged in her artificial universe.
The robots of Chapter 4 also constitute a case in point. They are an artifact created by the scigineer, who subjects them to an environment in which they evolve and learn. We saw how they can come to avoid obstacles, but exactly how do they accomplish this? Though we’re talking about an artifact — an object created by humans — it has evolved into something that we do not fully comprehend. Even though as stage designers we seem to have a privileged position, the actors have taken their own routes so as to better themselves. The scigineer must now take out his scientific toolbox in order to analyze this little robotic creature, just as a scientist analyzes a cockroach. Though such a current-day robot is still a far cry from a cockroach, it’s already complex enough to require the donning of a white coat.
Let me give you another well-known example, that of the Tierra world. Tierra is a virtual universe — embedded within a computer — that was set up in an attempt to explore the idea of open-ended evolution. It comprises computer programs that can evolve; unlike those of Chapter 2, however, where an explicit goal (and hence fitness criterion) is imposed by the user (for example, compute taxes), the Tierran creatures receive no such guidance. Rather, they compete for the natural resources of their computerized environment: time and space. You may remember from Chapter 6 that a standard computer consists of two major elements, the processor — that actually runs the program and the memory — the storehouse that acts as a repository for programs. These two components represent Tierra’s natural resources, and — just as in Nature — they are limited: The processor can only run one program at a given moment, and the memory can contain no more than a certain number of programs. This gives rise to a fierce battle for survival, the Tierran creatures having to vie for the processor’s precious time and for a place in the jungle known as memory. Failure means death: A program that is unsuccessful in procuring these resources disappears from the evolutionary stage.
Tierra was invented not by a computing scientist but by an ecologist, Thomas Ray, who had worked for years in the Costa Rican rain forest before turning from natural evolution to digital evolution. Ray inoculated his Tierran world with a single organism — a self-replicating program called the “ancestor,” which was able to co-opt the processor to produce copies of itself elsewhere in memory. This organism, a program written by Ray himself, was the only engineered (human-made) creature in Tierra. The replication process is not perfect: Errors, or mutations, may occur, thus driving the evolutionary process. Ray then set his system loose and witnessed the emergence of an ecosystem-in-a-bottle, right there inside his computer, including organisms of various sizes, and such beasties as parasites and hyperparasites. Ray wrote that “much of the evolution in the system consists of the creatures discovering ways to exploit one another. The creatures invent their own fitness functions through adaptation to their biotic environment.”
Large programs such as the ancestor have several instructions that form part of their “body”; these program instructions are used to copy the organism from one memory location to another, thus effecting replication. The evolved parasites are small creatures (programs) that use the replication instructions of such larger organisms to self-replicate. In this manner they proliferate rapidly in the memory jungle without the need for the excess replication code. As in Nature, the evolved ecology exhibits a delicate balance: If all large creatures were to disappear, then the parasites would die, having no replication code to appropriate. Tierra had even managed to outdo its creator, who wrote: “Comparison to the creatures that have evolved shows that the one I designed is not a particularly clever one.”
Ray first engineered this world, which he then proceeded to analyze as a scientist: “Trained biologists will tend to view synthetic life in the same terms that they have come to know organic life. Having been trained as an ecologist and evolutionist, I have seen in my synthetic communities, many of the ecological and evolutionary properties that are well known from natural communities.” (If you’re interested in learning how the humble Tierran beginnings ultimately lead to the rise of the “TechnoCore” artificial intelligences [AIs], I recommend The Rise of Endymion — the final volume of Dan Simmons’s Hyperion tetralogy.)
In April 1998, while leafing through the weekly issue of Science, I was surprised to find two out-of-the-ordinary articles. Science, one of the top two scientific journals (the other being Nature), publishes almost exclusively hard-core scientific papers in physics, chemistry, biology, and the like. If your paper is good enough to grace Science’s pages, then it’s probably about the natural world — the object of scientific study. Yet in browsing this particular issue, I suddenly came across a couple of articles that dealt with an artificial world, created entirely by humans: the World Wide Web. One article looked into the efficiency of search tools, while the other studied patterns of behavior as information foragers move from one hyperlinked document to the next. It’s almost as if we were talking about a tropical jungle.
This is a cogent example of scigineering that is totally unrelated to biology or biological inspiration. Here is a universe created entirely by humans, which has become so complex — much more so than a car or an elevator — and so interesting in and of itself, that it merits the attention of scientists — and the consecration of Science. We’ve engineered the World Wide Web, and then we turn to study this brave new world. The era of scigineering is upon us.
The rival journal, Nature, waited until August 1999 to finally “give in.” In an article entitled “Genome Complexity, Robustness and Genetic Interactions in Digital Organisms,” Richard Lenski, Charles Ofria, Travis Collier, and Christoph Adami explored the effects of genetic mutations in both simple and complex digital organisms, which inhabited the artificial, Tierra-like world called “Avida.” Commenting on their work, Inman Harvey from the Centre for the Study of Evolution at the University of Sussex cautioned that “considerable debate can be expected before a consensus is reached on just what is necessary for results from a synthesized world to be seen as relevant to the natural world.” The scigineer might study her world and glean much about it, but she must be cautious in applying her conclusions to the world at large.
The scigineer has one up on the scientist in that he can render his world easier to analyze, whereas a scientist must make do with what Nature affords him. Evolutionists would love to have the entire Tree of Life at their disposal, including all the lost species, yet this is but wishful thinking; geological reality, alas, is harsher on them, revealing but bits and pieces of the whole story. With artificial worlds, though, wishes are granted: You can easily save the entire evolutionary history of your artificial creatures to later analyze it at your leisure.
Remember from the previous chapter how the protagonist of Permutation City describes the result of the Autoverse experiment — the result of billions of years of evolution in this artificial world? He says: “All demonstrably [my emphasis] descended from a single organism which lived three billion years ago ...” In this artificial planet, one can demonstrate that all the organisms have descended from a single origin since the entire evolutionary trace is available. The scigineer might not possess perfect knowledge of his engineered world, but he at least has the power — unlike scientists — to render his analysis job easier.
In reminiscing about his illustrious career, Isaac Newton remarked: “I do not know what I may appear to the world; but to myself I seem to have been only like a boy playing on the seashore, and diverting myself in now and then finding a smoother pebble or a prettier shell than ordinary, whilst the great ocean of truth lay all undiscovered before me.”
We’re no longer content to walk the shores of Nature’s oceans of truth, finding whatever pebbles may have been laid for us. We’re now creating new oceans, and with them we beget new shores to walk.