Darwin could not have anticipated, for example, the work of physicist Lee Smolin of the Perimeter Institute for Theoretical Physics in Waterloo, Ontario. Smolin has utilized Darwinian concepts to shape a theory of the universe that he calls “cosmological natural selection.” He developed a theory that posits the existence of a vast number of unseen universes, each generated by the collapse of a black hole. The conditions of those collapses bestow each universe with its own set of fundamental parameters, such as the masses of its various subatomic particles. Just as life diversified on Earth, the “multiverse” in Smolin’s theory evolved from simple beginnings into a complex and varied assemblage of universes, each exhibiting a distinctive set of traits.
Art gives a selective advantage because it organizes cooperative behavior. The same idea applies to religion.
Cosmological natural selection could help to solve one of the main conundrums in physics: the seemingly arbitrary values of the fundamental constants in our universe. Why is a neutron, for example, more massive than a proton rather than the other way around? If a wealth of universes with unique parameters exists, Smolin says, then our own case does not seem so special or so unlikely. In fact, cosmological natural selection specifically favors universes—like ours—in which massive stars can form and give rise to new black holes. “By using Darwinian methodology, I was able to get an explanation for the improbable complexity of our universe,” Smolin says.
Another application of evolutionary theory outside biology is the computer-programming technique known as genetic algorithms. This approach “evolves” solutions to problems that resist linear thinking by generating populations of different solutions and then testing those scenarios against programmed constraints. Just as natural selection works on living populations to ensure that the organisms best adapted to their environment survive and reproduce, genetic algorithms winnow out the “unfit” solutions and refine the ones that best match performance requirements. In one notable example, contractors used genetic algorithms to design the jet engine for the Boeing 777. In another, researchers at New Mexico State University designed a “faceprint” program for criminal identification that recombines facial features until they match an eyewitness’s recollection of the perpetrator’s visage. “We’re getting Darwin’s ideas to run faster and jump higher,” says David E. Goldberg, director of the Illinois Genetic Algorithms Laboratory in Urbana-Champaign.
John Holland, a professor of psychology and computer science at the University of Michigan, is considered a father of genetic algorithms. He is currently working on a new generation of software tools that can not only optimize design but also adapt to changing constraints as the system elements themselves evolve. Such programs will be able to simulate complex adaptive systems—the stock market, say, or Internet traffic—in which the behavior of participants is not governed by fixed rules. In Holland’s models the resemblance to biological systems is not incidental; it is explicit.
Truer still to the biology model is the work of Nobel laureate Gerald Edelman, director of the Neurosciences Institute in San Diego. In the 1960s he used evolutionary theory to explain how the immune system rapidly creates antibodies targeted to pathogens it has never encountered. He learned that a variation in the DNA of the cells that make antibodies results in a variety of cell types, each with a unique antibody molecule on its surface. When challenged by a toxin or infection, the immune system screens this population for a match, then swiftly multiplies the clonal cell line that produces the matching antibody. Utilizing a kind of natural selection, the immune system chooses the cell line that is highly equipped to deal with an environmental challenge. “One of the most important ideas Darwin had was population thinking,” Edelman says. “It’s the Darwinian two-step: variation and selection, variation and selection, and so on, down the generations.”
In the 1980s Edelman applied the same kind of thinking to brain wiring, showing how memories could be created when interactions with the environment preferentially strengthen the connections between certain populations of neurons. The connections that are not used die out. He calls the theory Neural Darwinism. “My whole career seems to be dominated by Darwin’s thought,” he says. (See the DISCOVER Interview with Gerald Edelman from the February 2009 issue.)
Edelman’s work demonstrates the remarkable applicability of Darwin’s ideas to all aspects of living things. Darwin wrote about how evolution shapes the destiny of whole organisms, but its principles apply to individual cells, too. Cancer cells, for example, compete with native cells for the body’s resources, and the best-adapted ones grow so quickly that they become tumors. “Cancer evolves in our bodies according to principles dictated by natural selection,” says Randolph Nesse of the University of Michigan, a pioneer in the field of evolutionary medicine. Practitioners of evolutionary medicine analyze patterns of disease and morbidity by considering the deep history of our species. From that perspective, it becomes clear that humans are prone to obesity because our bodies evolved in an environment of scarcity, where consuming as much high-energy food as possible was a useful survival strategy. (In a fast-food restaurant, not so much.) An evolutionary perspective also suggests why men die, on average, seven years earlier than women: The factors that maximize their reproductive success also interfere with their long-term health. “Without an evolutionary background, you really can’t get a grasp on why the body isn’t designed better,” Nesse says. “It allows you to answer questions that you otherwise would not be able to answer at all, such as ‘Why does aging exist?’ and ‘Why does sex exist?’?”
According to Helen Fisher and other proponents of evolutionary psychology, the theory of evolution helps them address questions like “What is love?” and “Why do we vote the way we do?” Many evolutionary psychologists believe that the cognitive and emotional makeup of human beings represents an adaptation to our ancestral environment. Biologist Edward O. Wilson of Harvard University launched the discipline in 1975 with one slim chapter in his book Sociobiology: The New Synthesis, suggesting that insights into animal behavior afforded by evolutionary theory could apply to human animals, too.
Today the evolutionary worldview has expanded into analyses of economics and politics as well as of human mating behavior. It has enriched the “rational choice” model long espoused by economists to explain human behavior in the marketplace. Traditional economic models assume that people act exclusively in their self-interest, just as traditional evolutionary theory describes competition among individuals. But cooperation and altruistic tendencies also show up routinely in studies of economic behavior. People who stand to lose from progressive taxation, for example, may still vote for it. “You can’t predict how people will vote on the issue of income redistribution based on their income,” says economist Herbert Gintis of the Santa Fe Institute in New Mexico.
