A 2012 conference at Oral Roberts University, "Engineering and Metaphysics," explored how the fields of engineering, mathematics, and computing can contribute to answering scientific questions, including those pertaining to cosmic and biological origins. Some of the technical papers that were presented have now been combined into a noteworthy volume, Engineering and the Ultimate: An Interdisciplinary Investigation of Order and Design in Nature and Craft, edited by Jonathan Bartlett, Dominic Halsmer, and Mark Hall.

Lead editor Jonathan Bartlett opens the volume by pointing out that the U.S. has been heavily influenced by the pragmatic philosophy of William James. As Bartlett puts it, "For pragmatists, the search for truth for its own sake is somewhat misguided because truth cannot be apprehended until it is applied to real-world problems. ... Therefore the ultimate test of knowledge is whether or not we can build something out of it." (p. 1) We see this kind of pragmatic thinking at work in the discourse adopted by many Darwin defenders. For example, in an online webinar last year by National Center for Science Education, NCSE staffer Joshua Rosenau counseled Darwin advocates to emphasize "the role of evolution in making advances in medicine and curing diseases." Presenting a slide from the National Academy of Sciences, Rosenau states:

Evolution is a core scientific principle that is foundational to many areas of science and helps scientists make technological developments, like curing disease.

Under Rosenau's highly pragmatic approach, if it helps you cure disease, then questioning it is both "wrong" and "harmful." (Never mind that to actually create drug cocktails or treatment strategies that can outsmart evolving bacteria, viruses, or cancer cells, biomedical researchers adopt strategies that bank on the fact that there are limits to how much change can occur by Darwinian processes--so we actually make medical progress towards fighting diseases by questioning the power of the Darwinian mechanism!)

Engineering and the Ultimate is quick to disclaim the notion that pragmatism is the only proper means of measuring the value of an idea. After all, Bartlett notes, "science, testability, and the fundamentals of physics all draw directly from speculative philosophy." (p. 2) Or to put it another way, just because a philosophy doesn't cure diseases doesn't mean it doesn't have real-world value. Bartlett's point is that in public discussions about truth, philosophy too must be considered.

But the fact that pragmatism isn't the only way of measuring value doesn't mean that intelligent design is of no use for understanding the world around us! In fact, some wonderful contributions in this volume help show the practical, pragmatic value that intelligent design offers to scientific investigation.

Chapter 2, "Reversible Universe: Implications of Affordance-based Reverse Engineering of Complex Natural Systems," lead-authored by engineer Dominic Halsmer, observes that many natural systems have a peculiar property that makes them very similar to human-designed technology: they can be studied and understood through reverse engineering. As the authors put it:

Procedures for reverse engineering and design recovery have become well-defined in several fields, especially computer software and hardware, where pattern detection and identification play important roles. These procedures can also be readily applied to complex natural systems where patterns of multiple interacting affordances facilitate the development, sustenance and education of advanced forms of life such as human beings. (p. 11)

If it isn't familiar, the term "affordances" basically means a useful output provided by some system (often to a user, or to some other system). The authors explain that "engineering concepts are playing a key role in deciphering the workings of complex natural systems such as the living cell and the human brain." (p. 11) Darwin defenders boast that their theory helps cure diseases (even though, as we saw, it might be argued that diseases are actually cured by the recognizing limitations to Darwinian mechanisms). Yet we see that engineering methods grounded in the assumption that living systems are intelligently designed, can help us make scientific discoveries. In other words, intelligent design has great pragmatic value.

The authors go on to explore in detail what it means to "reverse engineer" or undertake "design recovery" on a system, and they explore how these methods might help us understand natural phenomena like human consciousness, molecular machines, or the fine-tuning of the universe. An intelligent design paradigm leads to further questions, as they point out, "ultimately what reverse engineering and design recovery procedures were designed to detect: what was the original engineer thinking?" (p. 31) The conclusion is obvious:

The fact that the natural world is so readily and profitably reverse engineered suggests that the cosmos actually is an engineered system; it is the work of a Mind with extraordinary engineering expertise. Investigators should not hesitate to consider this perspective, since it only seems to facilitate discovery but may also provide a sublimely satisfying understanding of personal meaning and purpose. (p. 31)

Don't miss the import of that last sentence: a concept that has both great scientific utility for understanding the natural world, and helps answer important metaphysical questions facing humanity, ought to rate very high on the "pragmatism" scale.

But is pragmatism the only measure of truth? That question is effectively tackled in the Chapter 4, where Mark Hall investigates the "seven lamps of architecture" developed by Victorian art critic John Ruskin. As Hall recounts, Ruskin argued that when examining the merits of a piece of architecture, we find that a building can be far more than just a functional structure with walls and a roof. It is capable of communicating deep truths about ourselves and our history -- the "seven lamps" defined by Ruskin as "sacrifice," "truth," "power," "beauty," "life," "memory," and "obedience." Could such an understanding of designed structures help us making aesthetic discoveries about natural entities that were also designed to be more than mere functional systems?

Jonathan Bartlett offers two chapters, "Using Turing Oracles in Cognitive Models of Problem-Solving," and "Calculating Software Complexity Using the Halting Problem," to help us better understand how intelligent agents think, and perhaps even help us understand the basis of consciousness. He begins by observing, "At the core of engineering is human problem-solving," and notes that human minds have been called "an oracle machine," where an "oracle" is something that "enable[s] the modeling of processes in the mind which are not computationally based." (p. 99) In mathematics, there are certain problems which have not been solved, but there are also problems that were once thought unsolvable, but have now been solved. According to Bartlett, this could mean that the human mind may "have access to an oracle which is more powerful than finitary computational systems." (p. 113) He concludes: "There is good evidence human cognition goes beyond what has been traditionally considered as 'physical.'" (p. 118)

Chapter 7, "Algorithmic Specified Complexity," is authored by a familiar team of writers -- Winston Ewert, William Dembski, and Robert Marks. They explain that the classical method of detecting design seeks to find complexity and specified information (CSI) in nature. As the authors of this paper write, "Complexity refers essentially to improbability," and specification is defined as "conforming to an independently given pattern." The authors observe:

In order to infer design, and object must be both complex and specified. The probability of any given object depends on the chance hypothesis proposed to explain it. Improbability is a necessary but not sufficient condition for rejecting a chance hypothesis. Events which have a high probability under a given chance hypothesis do not give us reason to reject that hypothesis. (p. 133)

But how do we measure specification? A common objection to the idea of specification is that it is qualitative and not quantitative. While qualitative measures of specification aren't necessarily a barrier to determining that a natural event or structure is specified, this paper presents a new method of quantitatively defining specification in terms of Kolmogorov complexity. "The Kolmogorov complexity of an object," the authors write, "is the length of the shortest computer program required to describe that object." (p. 131) By defining specification in terms of Kolmogorov complexity, they hope to "precisely define and quantify the degree to which a binary string follows a pattern." Under this scheme, "The more compressible an object is, the greater the evidence that the object is specified." (p. 131)

However, Ewert, Dembski, and Marks recognize an immediate problem with this definition. Language has high CSI, and is not readily compressible. But in computer programming, the rules of language can easily be accounted for by encoding the "context," or rules by which a system operates. This allows them to calculate the algorithmic specific complexity, "which takes into account the probabilistic complexity as well as the Kolmogorov complexity." They apply their method to protein folding and functional amino acid sequences. The result is a quantitative method of determining whether an event or structure is specified.

There are other noteworthy contributions to the volume, and I highly recommend it to anyone who has wondered how engineering, computation, and mathematics contribute to the theory intelligent design, and vice versa.

Image source: Wikipedia.