Complex Specified Information

Just What is Complex Specified Information? William A. Dembski is as multi-degree holding individual who advocates intelligent design as an alternative, and in some cases supplement, to current evolutionary theory. He holds Ph.D.'s in mathematics and philosophy, and other degrees in statistics, theology, and psychology. Not only is he a well-learned individual, but he has published numerous books and countless papers on a subject he believes should revolutionize science, this subject being Complex Specified Information (CSI). Complex Specified Information is not a phrase that Dembski has originated, but as a specific property, he has spent more time than anyone developing and trying to implement it into science. In various works, including The Design Inference: Eliminating Chance through Small Probabilities, No Free Lunch: Why Specified Complexity Cannot Be Purchased without Intelligence, and Intelligent Design: The Bridge Between Science and Theology, Dembski has developed the concept of CSI very technically and with mathematics, and in other cases has provided a more layman definition of the concept. The purpose of this paper will be to decipher the meaning of CSI, how it is significant, and decide if it is usual to science. First of all, a definition of what exactly CSI is should be discussed. But an exact definition of CSI would be long, drawn out, and complex, so it is be better to actually establish a strong criterion for how CSI Is used. Dembski uses a number of ingredients to formulate CSI, listed here: 

“a probabilistic version of complexity applicable to events”

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“conditionally independent patterns”

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“probabilistic resources”

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“a specificational version of complexity applicable to patterns”

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“a universal probability bound”

Each of these five different properties taken together form an analytical way to detect design, according to Dembski. In the following paragraphs, each one of these ingredients will be explored thoroughly.

For most circumstances, probability and complexity can be viewed as forms of each other. In fact, one can view it this way. Probability and complexity are analogous of each other, and in fact, share an inverse proportionality. This means that the more complex something is, the less probable it is, or vice versa. In Specified Complexity (the same thing as CSI), the complexity denotes improbability. This is not to say, though, as many people misunderstand that just because something is complex, even extremely complex, that it shows CSI. In a forest, there are many trillions of trillions of trillions of ways for each individual tree and plant to be arranged, making their combined arrangement outlandishly complex, but, if it is a natural forest, one not planted by humans, there will be no specification, which will be elaborated on soon. For a complex pattern to show intelligent design, it must be “independent of the event whose design is in question,” according to William Dembski. This means that the patterns cannot be placed on an event after it has already happened. If a pattern were given after the event takes place, then this pattern is not separate from the event, we would thereby take away the probability of the event, and then cannot reasonably conclude anything about said event. What this means is, there must be a prespecified rejection region in place before an event happens, which eliminates chance as a hypothesis, making the conclusion of specificity possible. These patterns, which eliminate the possibility of an event happening by chance give an event specificity. Another ingredient for CSI is probabilistic resources, which “refer to the number of opportunities ...an event [has] to occur or be specified.” In other words, if something has a high improbability of happen over a relatively short period of time, it probably will not happen. But if it is not a necessity for the event to not happen, then given a very large amount of time, the event may become exceedingly more likely to happen, and may happen on a number of occasions. If there is not enough time for the event to even happen once, then there are not enough probabilistic resources to allow the event to become probable, and therefore it is very unlikely to happen. Specification also has a property related to probabilistic resources, known as specificational complexity.

A pattern can display differing amounts of complexity. By extension, differing amounts of complexity can show up in a specification, making the event more probable, or less so. The magnitude of complexity of a specification evinces just how many specificational resources eliminate chance. A lot of specificational resources are factored in as a pattern becomes markedly more complex. It may seem nonintuitive at first, but the simpler the pattern, the more specified it is, and the more likely it is that it has been designed. It has low specificational complexity, but it has to be complex too. A universal probability bound is needed to define if something is probable to have happened, happened, or will happen in the known Universe. This number can be found using simple mathematics and known, or estimated, numbers. To find the universal probability bound, Dembski uses three numbers. First, scientists estimate that in the entire Universe, there are 10^80 elementary particles. Also, “the properties of matter are such that transitions from one physical state to another cannot occur at a faster rate than 10^45 times per second.” That number is related to Planck time, or the smallest, meaningful amount of time. Finally, the Universe is approximately 10^25 seconds old. If these numbers are multiplied together, they give a product of 10^150. What this means is, if something has a chance of less than 1 in 10^150 of happening, then it has not happened, and will not happen until such a time as found will be reached. There are not enough probabilistic resources in the entire Universe to let such an event happen. Dembski claims his number is more conservative than that of other statisticians and mathematicians by noting some people have proposed universal probability bounds as low as 10^50. The universal probability bound is applicable to CSI because if something shows specification as defined above, and has a probability of happening that is less than the universal probability bound, than it shows Specified Complexity. Complex Specified Information is only significant, though, if it is reliable. Otherwise, there would be no reason for even considering it, and it could be totally ignored. The main claim is CSI is a reliable detector of design. First of all, a “criteria attempt[s] to classify individuals with respect to a target group. The target group for [CSI] compromises all things intelligently caused.” First and

foremost, a problem for CSI is detecting things that are not designed. It will provide many falsenegatives. This happens because intelligent causes can simulate naturally driven causes. Also, it takes an intelligent agent to recognize the work of an intelligent cause. Therefore, some kind of background knowledge is essential. The fact that an intelligent agent can hide its work, whether on purpose or not, or when a detecting intelligence does not have the knowledge essential to detect design, gives CSI two of its limits. The fact is, according to Dembski, CSI can detect design, even if it cannot show something is not designed or show that every designed object is actually designed. If CSI is able to figure out if some things are designed, “we can have confidence that whatever [CSI] attributes to design is indeed designed.” CSI must avoid false-positives, though, if it is going to be considered. The justification that CSI always shows something is designed only when it actually is, is as follows, according to William Dembski: “where direct, empirical corroboration is possible, design actually is present wherever specified complexity is present.” This also leads to the conclusion that material mechanisms cannot explain events that exhibit Complex Specified Information. Dembski then states that material mechanisms besides the ones we do know about cannot explain the emergence of events that show Specified Complexity. This clearly shows that either find an event that has CSI, or there are no events that have the property of CSI. Therefore, CSI is a reliable criterion for detecting design some of the time (but not all of the time), but it cannot always detect if something is not designed, which does not diminish its usefulness. How can CSI be applied to science, though, particularly biology? Almost any student will learn of Darwinism in elementary biology classes, for it is biology's main claim to fame, and was one of the most successful theories showing how apparent design comes about by purely mechanical mechanisms. What intelligent design theorists wish to show is that intelligence is needed to explain “questions ...not reducible to such [mechanical] mechanisms.” By using the design-finding criterion of Complex Specified Information, it is possible to shows if there are any structures or events that cannot have possibly come into existence through mechanical

mechanisms, which would point to something beyond Darwinism. If something were to show, through CSI, markers of intelligence, then the current mechanical mechanisms, specifically Darwinism, would have to come under scrutiny as to how adequate mechanical mechanisms are at explaining biological complexity. But the only way to show that an intelligence is involved in providing specified complexity is through the criterion of CSI. Are there any structures which can only be adequately explained by intelligence because they possess CSI? Howard Berg, a Harvard biologist, has exclaimed that the bacterial flagellum is “the most efficient machine in the universe.” If you do not know, a bacterial flagellum is not something created by humans. In fact, it is the appendage on some bacterial that help them navigate liquid environments. According to Darwinism, this structure, along with everything else inside the cell that helps it live, must have come about through some mechanical mechanism, such as natural selection. Most evolutionary theorists employ a concept called co-option to explain the evolutionary pathway of a bacterial flagellum. Careful not to get into too much detail, as this subject has been explored throughout the scientific and ID literature. What we see here, then, is a limitation of natural selection, Darwinism's means of bringing about complexity, because the bacterial flagellum shows CSI. This is how CSI is such a revolutionary idea in biology. It makes the claim that Darwinism, the once universally accepted method of bringing about apparent design in creatures, is in fact inadequate to fulfill the claims it makes. It must now be established that since these features do not come about by mechanical mechanisms, this also means that a combination of chance and necessity, or chance and necessity by themselves cannot bring about events or structures that show CSI. All available evidence, according o Dembski, says that the probabilities of complex structures like the bacterial flagellum emerging from Darwinist mechanisms is so low as to render it practically impossible for such structures to exist except through the aid on an intelligence. Darwinists try to sidestep the supposed problem by hoping on unknown naturalistic mechanisms, but most logical people agree that you can only make assertions

based on existing evidence, not on evidence that may come to light. In fact, it does not even seem fruitful for Darwinians to appeal to unknown mechanisms anyway because a recent study titled ”Extreme functional sensitivity to conservative amino acid changes on enzyme exteriors” published in the Journal of Molecular Biology seems to say that any changes made to a biological structure destroys its current function and keeps it from taking on any other function. The idea of CSI, the way Dembski sees it has been around for a number of years now, and it has its many detractors. One would hope that their critiques would be worthwhile to read through, but many of them are pure rubbish, even to a layman, and seem to indicate that many of them are biased towards Darwinism and will not give intelligent design, or any of its prevalent theories a decent look through. Some people bring up some good points, and Mr. Dembski will hopefully address those points, if he has not already. A paper by Wesley R. Elsberry and Jeffrey Shallit titled “Information Theory, Evolutionary Computation, and Dembski's “Complex Specified Information”” tries to debunk many of Dembski's claims. First of all, they note that scientists do not throw design out the window arbitrarily. They are skeptical of adapting “rarefied” design, though, which is a “design inference based on ignorance of both the nature of the designer and regularities that might explain the observed phenomena.” They believe this is a good assertion by scientists because “empirically gained knowledge of designers and the artifacts which they create permit us to recognize regularities of outcomes, leading us to make an “ordinary” design inference in such cases. With an “ordinary” design inference, a designer becomes just another causal regularity. This is not so with a “rarefied” design inference, which Dembski urges us to make in ignorance of the properties of any putative designer and also of other causal regularities which may be operative.” They go onto explain that in the science of archeology design can be deduced from such methods as signs of something having worked on an artifact, which eliminates chance, since the object has been manipulated, and can be attributed to human artisans because we know from experience that they work and make such objects.

Next, Elsberry and Shallit argue that Dembski's induction for the desing inference is “completely unjustified.” They quote Dembski here: “In every instance where the complexityspecification criterion attributes design and where the underlying causal story is known (i.e., where we are not just dealing with circumstantial evidence, but where, as it were, the video camera is running and any putative designer would be caught red-handed), it turns out design actually is present; therefore, design actually is present whenever the complexity-specification criterion attributes design.” For instance, they say it put such a heavy load on finding any counterexample, that “Dembskian induction seems intelligently designed to rule out a naturalistic explanation of biological complexity.” Dembskian induction rules out anything, or so Elsberry and Shallit say, that does not have it's casual history known to an extremely high precision. They argue that a video-camera would have to be running on somethings entire casual history, then, to debunk the design inference. Shallit and Elsberry seem to put some of Dembski's conclusions in to doubt, unless he refines his theory. In fact, near the end of their paper, they challenge him, or some other intelligent design advocate, to come up with a rigorous definition of CSI. Far more interestingly, they challenge Dembski to use CSI to infer design on an artifact not known to be made by humans, and then, by other means, prove it had a human design history. I believe that if Dembski takes up these challenges, it will only strengthen CSI, and by collusion, also strengthen intelligent design. It could also prove fatal to CSI, but not necessarily intelligent design, if CSI cannot actually predict anything, as is needed to make it scientifically rigorous. In conclusion, William Dembski has put forth a noteworthy case for intelligent design through his concept of complex specified information. What is needed now is a more mathematically rigorous definition to prove CSI in such things as biological structures and maybe even predict human design in artifacts not once known to be a human artifact. CSI has a long rode ahead of it, but it could very well help supply intelligent design with the means of uprooting fanatical Darwinism, and make science free, as it should be.

Works Cited Dembski, William and Ruse, Michael. Debating Design. UK: Cambridge, 2004. Dembski, William. The Design Revolution: Answering the Toughest Questions About Intelligent Design. Illinois: IVP, 2004. Elsberry, Wesley and Shallit, Jeffrey. “Information Theory, Evolutionary Computation, and Dembski's “Complex Specified Information” 2003. The Talk Origins Archive