The burgeoning field of “systems biology,” as defined by the National Institutes of Health (NIH),

is an approach in biomedical research to understanding the larger picture — be it at the level of the organism, tissue, or cell — by putting its pieces together. It’s in stark contrast to decades of reductionist biology, which involves taking the pieces apart.

I’m sure that statement is designed to make systems biology sound radical and exciting, and it succeeds. It’s especially exciting for proponents of intelligent design, because ID theorists have been arguing against reductionism in biology for a long time. 

But we need to be careful. We don’t want to make an argument based on an equivocation. The word “reductionism” is thrown around a lot, but it can mean several different things. It’s not as simple as saying, “Biologists are learning that reductionism is bad!” 

As it turns out, the move away from reductionism in systems biology is significant for the ID debate, but not simply by word-association. So I want to take some time to suss out the different meanings of the word “reductionism” and what they have to do with intelligent design.  

There are two kinds of reductionism that are relevant to this discussion: methodological reductionism and ontological reductionism. (For a third kind, epistemological reductionism, see this cartoon.) The opposing philosophies are, respectively, methodological antireductionism and ontological antireductionism. The terms are a bit eye-splitting, but they aren’t difficult to understand. 

Methodological Reductionism      

Methodological reductionism is the idea that a thing can best be understood by breaking it down into its parts. The contrary philosophy, methodological antireductionism, says that a thing can be best understood by looking at it as a whole. 

The opposing views are summed up nicely in a conversation between the wizards Saruman and Gandalf in The Lord of the Rings. Saruman shows Gandalf his new rainbow-colored outfit and tells him that he has decided to stop going by “Saruman the White” and go by “Saruman of Many Colours” instead.  

“I liked white better,” says Gandalf. 

“White!” Saruman sneers. “It serves as a beginning. White cloth may be dyed. The white page can be overwritten; and the white light can be broken.” 

“In which case it is no longer white,” says Gandalf. “And he that breaks a thing to find out what it is has left the path of wisdom.” 

Saruman is a methodological reductionist and Gandalf is a methodological antireductionist. 

Methodological reductionism: “The white light can be broken.” 

Methodological antireductionism: “He that breaks a thing to find out what it is has left the path of wisdom.”

Ontological Reductionism 

Ontological reductionism, on the other hand, is not about the best way to study something, but rather about what that thing “really is” at the deepest level. Ontological reductionism says that a thing can be reduced to its most basic parts, and that’s what it is — nothing more. According to this theory, a tree is a collection of cells, which in turn are collections of molecules, which are collections of atoms, which are collections of subatomic particles. So in the final analysis, a “tree” is a collection of subatomic particles. 

This view, and its antithesis, is expressed in C. S. Lewis’s Voyage of the Dawn Treader. On an island near the edge of the world, the characters meet a being named Ramandu who claims to be a star.

“In our world,” Eustace Scrubb objects, “a star is a huge ball of flaming gas.”

“Even in your world, my son,” replies Ramandu, “that is not what a star is but only what it is made of.”

Eustace is an ontological reductionist and Ramandu is an ontological antireductionist. (And if Ramandu’s statement seems mind-bending or baffling, that’s because most of us were educated into ontological reductionism.)

Ontological reductionism: “A star is a huge ball of flaming gas.”

Ontological antireductionism: “That is not what a star is but only what it is made of.”  

Gandalf Points to Ramandu

The field of systems biology is methodologically antireductionist. It does not have to be ontologically antireductionist. So, systems biologists do not necessarily reject materialism or physicalism. They do not have to believe in minds, or be willing to posit neo-Platonic souls of cabbages, or think the true meaning of a mushroom can only be found in its wholeness. 

They have simply found it to be the case that looking at living organisms as complete systems yields better results than only taking them apart to focus on their bare components. Researchers are coming to realize that it is more productive to think about the plan of an organism than simply about its physical structure or components. 

But this is important, because whether systems biologists always admit it or not, methodological antireductionism implies ontological antireductionism. Gandalf agrees with Ramandu, not Eustace.  

That’s not to say that ontological antireductionism logically follows from methodological antireductionism, or vice versa. In theory, you could have one without the other. But the success of methodological antireductionism fulfills a prediction of the hypothesis of ontological antireductionism.

That is: if there really is a plan, then you would naturally suppose that looking for a plan would turn out to be a great strategy, and that proceeding as if there were no plan would not be a great strategy. And that is the reality. It turns out that when you take a creature apart to see what it’s parts are, you see a bunch of parts; but when you take a step back and look for a plan, you find a plan.

This Is What Intelligent Design Predicts

Intelligent design is a sub-type of ontological antireductionism. To be exact, it is one way of answering the question “if a thing isn’t just the sum of its parts, then what is it?” ID proposes that (at least some) natural entities are more than the sum of their parts because they are ultimately an expression of an idea in a conscious mind. If this is true, then you would predict those entities to be best understood by grasping the idea behind them; you would try to see the scheme, the purpose, the outline, the plan. 

The neo-Darwinian model, in contrast, does not inherently lead to this prediction, because the mechanism of natural selection and random variation is, by definition, an uncoordinated piling-up of useful features, whereas a “plan” is the coordination of useful features. (Michael Behe’s three books and Marcos Eberlin’s Foresight explore this idea in depth.)

This is not proof of the design hypothesis, but it is evidence for it. In fact, this sort of evidence is one of the pillars of the scientific method: the strength of a scientific hypothesis depends on its ability to make predictions that are borne out by investigation. Based on that criterion, the hypothesis of intelligent design is doing very well. The hypothesis of mindless evolution is not doing so well, because although mindless processes might generate great complexity, they do not make plans.

Some systems biologists may want to reject Saruman but stay with Eustace; to reap the practical benefits of methodological antireductionism while avoiding the philosophical costs. But they may find that stance difficult to maintain. An unwary systems biologist could easily drift over to Ramandu’s Island, where the ID theorists are waiting.