The ID movement is officially agnostic about the identity of the D/designer, but that’s a bit disingenuous. None of them are working under the assumption that the designing mind will turn out to be just another biological life-form. As it puts us in an endless regression of designers, I’m going to speak to the capital-D theory. Much of the work done under the Intelligent Design label is scientific in some sense. A small handful of scientists have written books and papers that are at least academic enough that I don’t understand them, so I admit that investigating the question under ID does involve doing science. What I claim is that the hypothesis itself is not really scientific. Let me explain.

Criteria for scientific viability

There are three really good criteria for evaluating a potential science such as memetics, psychoanalysis, or Intelligent Design: explanatory power, experimental success, and fecundity.  Explanatory power is the ability of a theory to explain a breadth of phenomena. The atomic theory of magnetism has greater explanatory power than the tiny-invisible-purple-rope theory of magnetism (TIPR-theory, for short) because the latter is obviously ad hoc and unconnected to the rest of the world. It might explain why two pieces of metal are attracted to each other, but not much else. A scientific hypothesis should do more than answer a single question. It should provide an interpretive model of the world, even if only a small piece of it.

Experimental success as a criterion is obvious, and it goes without saying that a theory must be testable to be evaluated at all. Even though I made it up, I’m at a loss as to what kind of experiment would be a fitting test for TIPR-theory, particularly if I further qualified the tiny invisible purple rope as undetectable by modern means and not causally related to anything detectable. If it were testable, it would need to succeed in predicting the results of multiple experiments, or at least explain why it didn’t do so; and we’re back to explanatory power.

Fecundity is related to the first two criteria, and it has to do with the ability of a theory to generate new questions and experiments. The atom hypothesis leads both up and down the chain of hard sciences, to physics and chemistry, provoking questions and suggesting experiments. A classic example is the prescient ‘discovery’ of non-extant elements, filling in the periodic table with the identity and properties of materials known only through the model. TIPR-theory, in contrast, wishes simply to end the questioning. It suggests no new directions. Here’s the important part: This is because of the kind of thesis that it is, not because it’s wrong. And if it turns out to be right, remember that I came up with it. © Todor 2009.

So what about Intelligent Design? I think it’s a fantastic answer, of far-reaching explanatory power; but by its very nature it’s a poor question. Science thrives on questions, accepts answers only provisionally, and digs for deeper ones. If an ultimate answer is reached, science comes to an end, for there is no where else for it to go. This is precisely what finding Design, or the Designer, means. The capitals indicate an ultimate explanation, not a provisional one. This is not analogous to finding a watch and inferring a designer, because that answer to the question, Why is this as it is?, provokes the question, Where did the watchmaker come from? ID theorists stop at Design. It’s simply the nature of their thesis. Science may lead a researcher to the question, Is this Design?, but it cannot adjudicate an affirmative answer.

Here I have to revise an earlier statement. I’ve not yet seen ID people really investigate questions so much as debunk certain answers. They have done an excellent job at exposing the problems of the consensus view of the origin and diversity of life, but little has been done to build a rival hypothesis, a different interpretive model that makes better sense of the data. The explanatory power of ID is breathtaking, but there are no forthcoming experiments for it, and it doesn’t seem to be spawning other scientific work. This is not because there is no Designer, but because ID ends the scientific process.

Full-fledged ID science?

This is all a bit abstract, but I think it can be cleared up looking at it practically. What would we expect to see if ID were a science? Rather than just exposing holes in other theories, which itself is a big part of the process, there would be measurable work done in building rival models. I would think there is enough money in the social movement to set up think tanks, institutions (The Discovery Institute is more of  a public relations arm for the movement), or endowed fellowships (at a sufficiently conservative school), and a peer-reviewed journal where ID scientists would publish papers working out precisely where the Design is, how we know it when we see it, what experiments should be performed, and how the results of other experiments should be reinterpreted. Is Design at the level of species? phylum? DNA? Can there be multiple levels of Design? There are a lot of questions, and nothing resembling a consensus in the literature available to me. What is more, an emerging consensus should start to show greater experimental success than rival theories—it should simply work better.

Don’t get me wrong, what they’re doing now is ok. I’m happy to see anyone throw stones at Goliath—it’s better for everyone in the long run—and if the Discovery Institute and others can get him to fall, all the better. Maybe there’s an Einsteinian revolution in the offing for biology. But right now the Intelligent Design movement is pouting about being disrespected in the scientific community. If you’re doing good science the work speaks for itself, and you don’t need to be in the good graces of the National Academy of Sciences. So either do the science better than everybody else, or start playing a different game.

At least that’s my take on everyday usage. Thanks to the miracle of language, a fascination of mine since I was first learning English at six years of age, we understand each other just fine. This common usage, though, can let us down when discussions take us into higher levels of critical thinking. Failing to discern that we’re using the hard ’scientific’ or ‘technical’ language instead of the plastic ‘everyday’ language can lead to misunderstanding. Words such as argument and criticism have a negative connotation in everyday-speak because most people don’t want to be criticized or get into arguments, but as we flip that mental switch to higher thinking we realize that they are emotively neutral. They’re just part of the parlance of intellectual engagement.

Let’s take a closer look at this language, starting with facts. Julius Caesar crossed the Rubicon in 49 BC/BCE. Fact. I just checked on Wikipedia. But how does the Great Wiki know? Probably out of a standard encyclopedia or a survey of Roman history, but then where did they get if from? Ok, so at some point down the bibliographic chain a classicist actually read Remus Suitonicus Romanus Historicus, and he said so. But that’s not right either, because whatever he said, it was not “49 BC.” Someone had to ‘exegete’ the date based on whatever was written in the text. How was that interpretation carried out? What were the assumptions it was based on? Did it immediately correspond to other information? What is the weakest link in the limiting data? And remember that “crossing the Rubicon” is not a plain statement of an event, but is rich in significance. Did the reader get the significance right? What role does that part have in understanding the whole?

It turns out that facts are not non-debatables, they’re just the bits and pieces of the historical, philosophical, or scientific models we build. In the latter case those are sometimes literal models. You can crank on the cogs of a heliocentric model of the solar system and see why it works better at explaining the retrograde motion of celestial bodies than the geocentric model does. Most of the time, though, models are conceptual or mathematical. Meteorologists program computers with a model—their systematic body of knowledge of how weather systems respond to heat, wind, moisture, and so on—and the computer uses that information to answer their questions (What’s going to happen to these clouds when the sun rises in the morning?). Their forecasting success depends on how well their model corresponds to reality.

Note that it isn’t a right or wrong situation: they may at times, using the same model, make better predictions than other times. Those successes and failures tell them where the model works well, and where it doesn’t. Note, too, that as the scientist reads incoming data, the ‘facts,’ he understands them based on his over-arching understanding of the whole system.That understanding is a theory, a coherent bundle of propositions that attempt to explain something and which, when unfolded, becomes a model that can be applied to interpret data or make predictions.

How do you prove it? Or if there are multiple competing theories, how do you know which one is right? We have to get beyond the popular conception of simply lining up our non-debatables against a measuring stick. Those facts, the data, have to be interpreted against the model. The better theory is the one that best explains the data.

In biblical studies there are multiple theories about the “historical Jesus”—itself a phrase that juxtaposes the Jesus of history with the Jesus of the Gospels—ranging from God Incarnate to Jewish philosopher. The data is the same, more or less. The question is which understanding of Jesus makes the best sense of the evidence. If one hypothesizes that Jesus was a Jewish philosopher who merely encouraged high ethical standards, then the problem becomes explaining the rise of Christian martyrdom. If one hypothesizes that Jesus was God and encouraged his own worship, then the problem becomes explaining the late split of Christianity from Judaism. And, of course, I’m simplifying: there are many more problems and many other approaches (I picked the two extremes, but I believe neither of them). There is no theory, in science or the humanities, that is without its problems, that has no holes to fill, that needs no further thinking or articulation. There is nothing that is completely settled. There is only the illusion of this at a popular level.

Understanding the rules of the road is the only way to get anywhere, to have a sincere and open exchange of ideas. Purposefully or accidentally we can throw up roadblocks. When the creationist says, “Evolution is just a theory,” or the atheist says, “Religion is a about faith, science is about facts,” they’re both playing a language game, and playing it badly. The arguments fail catastrophically, imploding by their own circularity. Words can and should be tools for dialog and persuasion rather than simply clubs for bludgeoning, and it starts with a neutral vocabulary.

I touched on another example a moment ago: the Copernican and Ptolemaic models of what we now know of as the solar system. The most interesting part of the story is that at first the Ptolemaic model, although it had built complication upon complication to make sense of the apparent motion of the planets, actually did the math better than Copernicus’ conceptually superior system. The Ptolemaic model was complex and ingenious, the Copernican simple and profound. A priori, which would you have chosen?