How does everything evolve?

Mark Vellend

Everything Evolves reveals how evolutionary dynamics shape the world as we know it and how we are harnessing the principles of evolution in pursuit of many goals, such as increasing the global food supply and creating artificial intelligence capable of evolving its own solutions to thorny problems. Taking readers on an astonishing journey, Mark Vellend describes how all observable phenomena in the universe can be understood through two sciences. The first is physics. The second is the science of evolvable systems.

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In your book, you argue that the theory of evolution applies far beyond the confines of biology – an argument that has been made before. What’s different about your perspective?

Mark Vellend: Your question itself actually hints at my answer. One key obstacle to generalized evolutionary theory gaining the recognition it deserves is the fact that we always start with biology and work our way out from there. Before people like Jean-Baptiste Lamarck, Alfred Russel Wallace, and Charles Darwin started devising theories to explain the evolution of life, linguists, economists, and observers of technology had articulated ideas about change that were unambiguously evolutionary, in the modern sense of that term. The evolutionary biologist Stephen Jay Gould went so far as to say that “Darwin may have cribbed the idea of natural selection from economics.”

Starting with biology gives the false impression that the version of evolution happening in the realm of language or technology or economics is a kind of weak version, a poor cousin. But evolutionary processes are agnostic to the substrate they work on. They produce a great diversity of things – organisms, technologies, cultural practices – that are fit for a particular function. The perspective I offer is that once we see that biology as just one manifestation of a more general process of evolution, we can better understand, build, and apply the general theory.

Your shorthand for this general theory of evolution, used throughout the book, is “the Second Science”. Where does that expression come from?

MV: The term was coined by evolutionary biologist Graham Bell. It is a play on the expression “The Second Sex”, the title of Simone de Beauvoir’s most famous book. The idea is that just as women have been defined in relation to, and subordinated by, men, evolution has not been recognized as a pillar of science that is of equal importance to physics. When I first started reading philosophy of science, I was struck by the degree to which physics was considered the model for how we should view, and how we should do, all kinds of science. The underlying sentiment was that if we did science right, we would eventually be able to predict what evolution will do next, just as we can predict the next time Halley’s Comet will next come within viewing distance of Earth, decades from now. But evolution involves some fundamental unpredictability.

Bell also makes the provocative claim that physics (along with its downstream applications in chemistry, physiology, or geology) and evolution (of life, culture, economics, and so on) are the only two general types of process we need to understand all of the natural world. Physical laws can tell us how a cell phone or an elephant works, but it is largely silent on how those things came to be in the first place. For that we need the science of evolution. I hope to help lift the Second Science out of its subordinate position in the scientific enterprise.

You said that evolution is unpredictable. What do you mean by that exactly?

MV: Think about biological evolution. The human genome has roughly 3 billion DNA base pairs, and each of those can change in three different ways (there are four kinds of base pair). So, there are 9 billion possible ways for the next mutation to occur. We could imagine one day understanding things well enough to predict the fate of any such mutation in terms of what effect it has on our physiology or morphology. The problem is that the effects of the next mutation after that can depend on the first, and the number of possible pathways to get to a new species is astronomical.

For a sequence of just two mutations there are 8.1 × 10¹⁹ possibilities (9 billion × 9 billion), and even close relatives like humans and chimpanzees are separated by a sequence of millions of such steps. We can walk through the same kind of calculations for the evolution of language, for example by imagining that the English language, with roughly 500,000 words or phrases, evolves one word or phrase at a time. In short, evolution is a process of trial and error in which you don’t know what trials are coming next, each step is contingent on the last, and the number of possible pathways is unimaginably large.

You argue that generalized evolutionary theory – the Second Science – has been held back by what you call the “Darwinian Distraction”. How could Darwin, often called the father of evolution, somehow be a problem for the advancement of evolutionary theory?

MV: Darwin himself is not the problem. Darwin nailed the basic explanation for how biological evolution works, he communicated it with exquisite skill, and he is eminently deserving of his place in the pantheon of scientific giants. The problem starts when the admiration that contemporary scientists have for Darwin veers into obsession. The frequency with which Darwin gets name dropped into the titles or introductions of books and articles is astounding when you start to pay attention. But the modern theory of evolution that bears Darwin’s name – neo-Darwinism – includes some details of genetics about which he knew nothing, and some assumptions, such as the completely random generation of new variation, that do not apply universally, even within biology.

Proponents and critics of generalized evolutionary theory often argue about whether cultural evolution is specifically Darwinian. For example, they might look for some equivalent of genes in culture, or they might argue about non-randomness in the way new cultural variants are generated. But this distracts us from the core commonalities across all evolutionary systems. The defining features of an evolutionary system are variation generation (e.g., a new cell phone design, a new word), inheritance (characteristics are passed on through time), and differential success (some variants do better than others). It doesn’t matter if some new variants were produced with intent, or of there are no gene-like things involved. It no more important for a giraffe to have something like verb tenses than it is for a language to have something like genes. It’s all still evolution.

It’s somewhat surprising to hear that neo-Darwinian assumptions don’t apply universally in biology. Can you offer an example?

MV: My favorite example comes from an immune defense system in bacteria called CRISPR, which is best know for having been coopted by scientists for doing genetic engineering. In the bacteria themselves, infection by a virus prompts a bacterial cell to grab a piece of the viral DNA and incorporate it into its own genome. The next time a similar virus shows up, the bacterial cell can recognize the virus and chop up its DNA into useless bits. In short, a mutation in the bacterium – incorporation of viral DNA – is advantageous in the face of the very same situation – viral attack – that caused the mutation in the first place. People have argued about how to view this situation in the light of evolutionary theory, but I see no way this could be anything but a violation of the assumption that mutations always happen at random with respect to their effects. But again, while it might create a headache for the neo-Darwinian view of evolution, it really doesn’t matter for the Second Science. It’s all still evolution.

Let’s say we agree that it’s all still evolution. Why is it important for people to appreciate and understand the Second Science?

MV: Grappling with and understanding some of humanity’s greatest current challenges requires a firm grasp of evolution. To start with one that is perhaps not obvious to everyone, consider artificial intelligence. When computers recognize faces or generate human-like conversation, they are not executing instructions given to them by people, as they are when you use a spreadsheet, for example. Rather, computers are executing an algorithm that they evolved themselves. In essence, programmers figured out how to harness the power of evolution inside computers to solve previously near-impossible challenges.

In addition, tipping points, like those involved in the collapse of an economy or an ecosystem, are fundamentally about triggering a runaway evolutionary process. Changes in the Earth’s cultural and biological diversity, and the consequences of those changes, are also the outcome of evolutionary processes. Finally, once we realize the breadth of application of evolutionary processes, we also realize us that keeping evolution out of schools – still an issue in some places – deprives people not only of an understanding of how life came to be, but also of how their own cultures, languages, and customs came to be as well.

About the Author

Mark Vellend is professor of biology at the Université de Sherbrooke and a fellow of the Royal Society of Canada. He is the author of The Theory of Ecological Communities (Princeton).