Intelligent Design as a Positive Research Program

Criticism, however, is never enough. I'm fond of quoting the statement by Napoleon III that one never destroys a thing until one has replaced it. Although it is not a requirement of logic that scientific theories can only be rejected once a better alternative has been found, this does seem to be a fact about the sociology of science -- to wit, scientific theories give way not to criticism but to new, improved theories. Concerted criticism of Darwinism within the growing community of design theorists was therefore only the first step. To be sure, it was a necessary first step since confidence in Darwinism and especially the power of natural selection needed first to be undermined before people could take seriously the need for an alternative theory (this is entirely in line with Thomas Kuhn's stages in a scientific revolution). Once that confidence was undermined, the next step was to develop a positive scientific research program as an alternative to Darwinism and more generally to naturalistic approaches to the origin and subsequent development of life.

In broad strokes, the positive research program of the intelligent design movement looks as follows (here I'm going to do a conceptual rather than a historical reconstruction):

1. Much as Darwin began with the commonsense recognition that artificial selection in animal and plant breeding experiments is capable of directing organismal variation (which he then bootstrapped into a general mechanism to account for all organismal variation), so too the intelligent design research program begins with the commonsense recognition that humans draw design inferences routinely in ordinary life, explaining some things in terms of purely natural causes and other things in terms of intelligence or design (cf. archeologists attributing rock formations in one case to erosion and in another to design -- as with the megaliths at Stonehenge).
2. Just as Darwin formalized and extended our commonsense understanding of artificial selection to natural selection, the intelligent design research program next attempts to formalize and extend our commonsense understanding of design inferences so that they can be rigorously applied in scientific investigation. At present, my codification of design inferences as an extension of Fisherian hypothesis testing has attracted the most attention. It is now being vigorously debated whether my approach is valid and sustainable (the only alternative on the table at this point is a likelihood approach, which in forthcoming publications I have argued is utterly inadequate). Interestingly, my most severe critics have been philosophers (e.g., Elliott Sober and Robin Collins). Mathematicians and statisticians have been far more receptive to my codification of design inferences (cf. the positive notice of my book The Design Inference in the May 1999 issue of the American Mathematical Monthly as well as mathematician Keith Devlin's appreciative remarks about my work in the July/August 2000 issue of The Scientist : "Dembski's theory has made an important contribution to the understanding of randomness -- if only by highlighting how hard it can be to differentiate the fingerprints of design from the whorls of chance"). My most obnoxious critics have been Internet stalkers (e.g., Wesley Elsberry and Richard Wein), who seem to monitor my every move and as a service to the Internet community make sure that every aspect of my work receives their bad housekeeping seal of disapproval. As a rule I don't respond to them over the Internet since it seems to me that the Internet is an unreliable forum for settling technical issues in statistics and the philosophy of science. Consequently, I have now responded to critics in the following three forums: Philosophy of Science (under submission), Christian Scholar's Review (accepted for publication), and Books & Culture (accepted for publication). I shall also be responding to critics at length in my forthcoming book No Free Lunch: Why Specified Complexity Cannot Be Purchased Without Intelligence (Rowman & Littlefield) as well as offering there a simplification of my concept of specification. Yet regardless how things fall out with my codification of design inferences, the question whether design is discernible in nature is now squarely on the table for discussion. This itself is significant progress.
3. At the heart of my codification of design inferences is the notion of specified complexity, which is a statistical and complexity-theoretic concept. Provided this concept is well-defined and can effectively be applied in practice, the next question is whether specified complexity is exhibited in actual physical systems where no evolved, reified, or embodied intelligence was involved. In other words, the next step is to apply the codification of design inferences in (2) to natural systems and see whether it properly leads us to infer design. The most exciting area of application is of course biology, with Michael Behe's irreducibly complex biochemical systems, like the bacterial flagellum, having thusfar attracted the most attention. In my view, however, the most promising research in this area is now being done at the level of individual proteins (i.e., certain enzymes) to determine just how sparsely populated island(s) of a given functional enzyme type are within the greater sea of non-functional polypeptides. Preliminary indications are that they are very sparsely populated indeed, making them an instance of specified complexity. I expect this work to be published in the next two years. I am withholding name(s) of the researcher(s) for their own protection.
4. Once it is settled that certain biological systems are designed, the door is open to a new set of research problems. Here are some of the key problems:

• Detectability Problem -- Is an object designed? An affirmative answer to this question is needed before we can answer the remaining questions. The whole point of (2) and (3) was to make an affirmative answer possible.
• Functionality Problem -- What is the designed object's function? This problem is separate from the detectability problem. For instance, archeologists have discovered many tools which they recognize as tools but don't understand what their function is.
• Transmission Problem -- What is the causal history of a designed object? Just as with Darwinism, intelligent design seeks historical narratives (though not the just-so stories of Darwinists).
• Construction Problem -- How was the designed object constructed? Given enough information about the causal history of an object, this question may admit an answer.
• Reverse-Engineering Problem -- In the absence of a reasonably detailed causal history, how could the object have come about?
• Constraints Problem -- What are the constraints within which the designed object functions optimally?
• Perturbation Problem -- How has the original design been modified and what factors have modified it? This requires an account of both the natural and the intelligent causes that have modified the object over its causal history.
• Variability Problem -- What degree of perturbation allows continued functioning? Alternatively, what is the range of variability within which the designed object functions and outside of which it breaks down?
• Restoration Problem -- Once perturbed, how can the original design be recovered? Art restorers, textual critics, and archeologists know all about this.
• Optimality Problem -- In what sense is the designed object optimal?
• Separation of Causes Problem -- How does one tease apart the effects of intelligent causes from natural causes, both of which could have affected the object in question? For instance, a rusted old Cadillac exhibits the effects of both design and weathering?
• Ethical Problem -- Is the design morally right?
• Aesthetics Problem -- Is the design beautiful?
• Intentionality Problem -- What was the intention of the designer in producing a given designed object?
• Identity Problem -- Who is the designer?

To be sure, the last four questions are not questions of science, but they arise very quickly once design is back on the table for serious discussion. As for the other questions, they are strictly scientific (indeed, many special sciences, like archeology or SETI, already raise them). Now it's true that some of these questions have analogues within a naturalistic framework (e.g., the functionality problem). But others clearly do not. For instance, in the separation of causes problem, teasing apart the effects of intelligent causes from natural causes has no analogue within a naturalistic framework.

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