What Is the Positive Case for Intelligent Design?
Editor’s note: We are delighted to present a new series by geologist Casey Luskin on “The Positive Case for Intelligent Design.” This is the first entry in the series, a modified excerpt from the new book The Comprehensive Guide to Science and Faith: Exploring the Ultimate Questions About Life and the Cosmos. Find the full series so far here.
Intelligent design (ID) is a historical scientific theory that uses the scientific method to make testable claims about the origin of various features of nature. But on a scientific level, ID is much more than that. The positive case for design allows the theory of ID to serve also as a heuristic — a paradigm that can inspire scientific research and help scientists make new discoveries. This chapter will elaborate on how the case for design in nature uses positive arguments in multiple scientific fields, based upon finding in nature the type of information and complexity that, in our experience, comes only from intelligence — and explain how these positive arguments are turning ID into a fruitful paradigm to guide twenty-first-century scientific research.
What’s a Positive Argument?
To understand how ID makes a positive argument, it’s helpful first to appreciate what positive and negative arguments look like in historical sciences. Simply put, negative arguments in science proceed by saying, “Theory X is false; therefore, Theory Y is true.” This form of argument only gets you so far because evidence against one theory does not, in and of itself, necessarily therefore constitute positive evidence for another theory. A positive argument proceeds by saying, “Theory X predicts Y. Y is found. Therefore, we have evidence that is inferred to support Theory X.” Such a positive argument uses abductive reasoning, where one infers a prior cause based upon findings its known effects in the world around us. As paleontologist Stephen Jay Gould put it, historical sciences use this kind of reasoning to “infer history from its results.”1
Affirming the Consequent?
Some might claim that such a positive, abductive argument commits the logical fallacy of affirming the consequent, where one wrongly infers a particular cause from its known effects because there might also be other causes that can potentially account for the data. The solution is to compare known causes which have the potentiality to explain the data and determine which one explains the most data. This is what ID theorist Stephen C. Meyer and other philosophers of science call making an “inference to the best explanation.”2
But where do historical scientific explanations come from in the first place? Another important method of historical sciences is the principle of uniformitarianism, which holds that “the present is the key to the past.” Historical scientists apply this principle by studying causes at work in the present-day world in order, as the famous early geologist Charles Lyell put it, to explain “the former changes of the Earth’s surface” by reference “to causes now in operation.”3 To put it more simply, historical scientists study causes at work in the present day, and through these they investigations can then make testable and falsifiable predictions about what we should expect to find today if a given cause was at work in the past. When these predictions are fulfilled, we have positive evidence that a particular cause was at work. The cause that accounts for the most data is inferred to be the most likely to be correct. This is how historical scientists make an inference to the best explanation.
Let’s Consider an Everyday Example
Imagine that you took your 4×4 truck off-roading and you returned home with the truck covered in mud. You drop the truck off at a car wash to have it cleaned, and an hour later, return to pick it up. This may seem like a silly exercise, but how could you apply the scientific method of historical sciences to determine whether the truck was washed? Well, you could use your past experiences with car washes to make predictions about what you would expect to find if the truck was washed, and then you could test those predictions.
For example, your experiences with car washes have taught you that after a car goes through a car wash, it’s completely free of dirt and mud, and has soapy residue on its paint. Thus, if the truck was washed, then you might predict that there will be no mud left on the exterior and it would even be spotless. This prediction could be tested by a simple visual analysis. If you see chunks of mud remaining, then you refute your hypothesis that the truck was washed. You could also undertake a more technical analysis, predicting that if the truck was washed, then there should be small amounts of soap residue left on the paint surface. You could scrape material off the surface of the truck and perform a chemical analysis to confirm or refute this hypothesis. If you find that there are no chunks of mud on the truck, and soap residue is present on the truck’s paint, you would have positive evidence that the truck was washed.
But is a car wash the best explanation? A competing hypothesis, the “rain washed the car” hypothesis, might explain a general lack of mud, but would not leave the car spotless and could not explain the presence of the soapy residue. We use this positive argument to infer that the best explanation for the observed data is that the truck went through a car wash.
Let’s now try a scientific example from my field of geology. The theory of plate tectonics predicts that continents were once joined as a single supercontinent, often called Pangea. Plate tectonics predicts that continents that are now widely separated by oceans might show similar rocks and fossils — especially along the edges where they were once thought to be linked. This is in fact what we find, with plate tectonics making a successful prediction that provides evidence for the theory (Figure 1). No other theory made this prediction, making plate tectonics the best explanation for the evidence. This is a positive argument for plate tectonics.
As a historical scientific theory, ID works in much the same way, making predictions that can be tested to provide positive evidence for the theory.
Next, “Outlining Intelligent Design’s Positive Argument.”
- Stephen Jay Gould, “Evolution and the triumph of homology: Or, why history matters,” American Scientist 74 (1986), 61.
- Stephen C. Meyer, Signature in the Cell: DNA and the Evidence for Intelligent Design (New York: HarperOne, 2009), 154.
- Charles Lyell, Principles of Geology: Being an Inquiry How Far the Former Changes of the Earth’s Surface Are Referable to Causes Now in Operation (London, UK: John Murray, 1835).