Wikipedia’s infamously biased, rule-violating, and error-filled entry on intelligent design states that “any appeal to an intelligent creator is explicitly excluded for the paralyzing effect it may have on the scientific progress.” But what if scientists are already using intelligent-design reasoning to study life? What if they are treating biological systems as if they are designed, and what if this approach turns out to be scientifically fruitful?
What if many scientists are doing this and they don’t even realize it? What if this has been going on for years, and it has been one of the most successful methods for investigating biology? Welcome to the field of systems biology. In a new peer-reviewed paper at BIO-Complexity, “Systems Biology as a Research Program for Intelligent Design,” University of Pittsburgh physicist David Snoke makes this point powerfully:
Opponents of the intelligent design (ID) approach to biology have sometimes argued that the ID perspective discourages scientific investigation. To the contrary, it can be argued that the most productive new paradigm in systems biology is actually much more compatible with a belief in the intelligent design of life than with a belief in neo-Darwinian evolution. This new paradigm in system biology, which has arisen in the past ten years or so, analyzes living systems in terms of systems engineering concepts such as design, information processing, optimization, and other explicitly teleological concepts. This new paradigm offers a successful, quantitative, predictive theory for biology. Although the main practitioners of the field attribute the presence of such things to the outworking of natural selection, they cannot avoid using design language and design concepts in their research, and a straightforward look at the field indicates it is really a design approach altogether.
(David Snoke, “Systems Biology as a Research Program for Intelligent Design,” BIO-Complexity, Vol. 2014 (3).)
Snoke outlines some basic differences between an ID approach to studying origins and a Darwinian one:
If both viewpoints tend to focus on material causes and effects in presently existing systems, where do they diverge in their predictions? Consider the two cases mentioned above, namely a very good human designer and a very bad human designer. The bad designer may, for example, be a Darwinian designer who simply tries all kinds of things and throws out the attempts that don’t work. How would we expect their products to differ?To start, we would expect the good designer to produce products with few non-functional elements. This is related to the expectation that good design will have a high degree of optimization, or efficiency.
It is possible to imagine that a bad designer could also obtain some degree of optimization by simply trying many times, and always keeping the most efficient version. This is the Darwinian explanation of the efficiencies that may exist in biological systems. A bad designer could make random changes to existing designs, and toss away the less optimal versions each time. But even a short consideration tells us that such an approach would probably have some non-functional or non-optimal elements, and that we would expect more of them than we would in a truly well-designed system. Thus, proponents of Darwinism have historically argued for “junk” in living systems, such as “vestigial” organs or “junk” DNA.
A good-design assumption also leads us to expect other attributes besides just the lack of non-functional elements. In well-designed systems we expect to find subtle and elegant methods. By contrast, in badly designed systems we expect to find “kludgy” and “brute force” methods, i.e., methods that involve gross inefficiencies but get the job done. Proponents of Darwinism have often argued that the kludgy, inelegant methods that exist in biology are evidence that biological systems are not designed by an intelligent agent.
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