The case for design is muscular?

The Incredible Design of Muscles

Andrew McDiarmid  

To understand the limitations of evolutionary mechanisms, we have to “bite the bullet of complexity,” as biochemist Michael Behe writes. And to appreciate complexity, we have to experience it. On a new episode of ID the Future, Dr. Jonathan McLatchie takes host Andrew McDiarmid on a deep dive into the structure and biochemistry of muscles to gain a better understanding of their incredible design properties.

McLatchie provides an overview of the key parts of muscles, including muscle fibers, connective tissue, and tendons. He describes the two different types of muscles — antagonists and synergists — and provides examples of each. Then he explains the integration of muscle function: how muscle contraction involves the nervous, respiratory, circulatory, and skeletal systems all working together in tandem. 

Did you know our brain predicts and corrects discrepancies between our intended and actual muscle movements? McLatchie explains this remarkable feature and also describes muscle sense and muscle memory. He gives us a taste of the complexity of muscle function at the biochemical level. And while we’re reeling from all that, he explains why all this engineering prowess is fiendishly difficult to explain through evolutionary mechanisms but hardly surprising within an intelligent design framework. Download the podcast or listen to it here.

Hippos vs. Darwin

 Notes on the Mysterious Origin of Hippos

Wolf-Ekkehard Lönnig

Please consider the Abstract of my recently published paper, “Hippo Origin: Accidental DNA Mutations or Ingenious Design?”

Abstract

“To call hippos ‘charming’ may seem a bit of a stretch,”  comments,national Geographic “but they are most certainly among the classic charismatic megafauna of the African continent.” Although the hippos (Hippopotamus amphibius L.) are not a major focus of attention in evolutionary biology, it may nevertheless be quite revealing to appreciate some points about the history of these powerful animals:

The family Hippopotamidae appears abruptly in the fossil record — like all the other groups that I have so far investigated in detail. See here for many more examples.

As compared to the variation possible within living species such as humans and others (see below), the two subfamilies and most of the hippo genera and species, which have been determined solely on the basis of anatomical and morphological criteria, may simply have been special populations of Mendelian recombinants from a genetical point of view (i.e., according to the genetical species concept). These recombinants (putative new subfamilies, species, and genera) also appear abruptly in the fossil record.

The evolutionary derivation currently favored by most paleontologists, of the Hippopotamidae from Anthracotheriidae, has been disproved by the detailed investigations of researcher Martin Pickford (for instance 2009, 2011, 2022). However, his alternative, the Doliochoeridae as ancestors of the hippos, is equally doubtful. 

All three families mentioned above appear abruptly in the fossil record and subsequently display constancy or stasis over long periods of time.[1] In no case is there any documentation of a continuous evolution of one family from another by “infinitesimally small changes” (Darwin) or by mutations with “slight or even invisible effects on the phenotype” (Mayr). Otherwise, there would be no contradictory evolutionary derivations.The popular rejoinder asserts the incompleteness of the fossil record as the reason for these phenomena. But this rejoinder has in principlebeen refuted by (among many others) paleontologist Oskar Kuhn. As Kuhn states, “in many animal groups such a rich, even overwhelming amount of fossil material exists (foraminifers, corals, brachiopods, bryozoans, cephalopods, ostracods, trilobites, etc.), thatthe gaps between the types and subtypes must be viewed as real.” There is no reason that it would be different in the hippos if we had more fossils. The evolutionary “ghost lineage” will forever continue to consist mostly of “ghosts.”

Evolutionary hypotheses and derivations reflect circular reasoning, and cladistics has not refuted this objection. Note that, “Decisions as to whether particular character states are homologous, a precondition of their being synapomorphies, have been challenged as involving circular reasoning and subjective judgements.” And now according to transformed cladistics “it is a mistake to believe even that one fossil species or fossil ‘group’ can be demonstrated to have been ancestral to another” (Nelson).

The truth about hippo origins — apart from the abrupt appearance of this (and virtually all other) families in the fossil record, and drawn from their ingenious blueprints involving structures of irreducible complexity in probably all groups and generally enormous amounts of specified complexity on all biological levels (morphology, anatomy, physiology and genetics) — points to intelligent, ingenious design. Indeed, Georges Cuvier, as the “founding father of paleontology,” as well as renowned researchers such as Louis Agassiz, have argued for “One Supreme Intelligence as the Author of all things.”

You will find a discussion of these and many other  at  “Hippo Origin: Accidental DNA Mutations or Ingenious Design?”

The technology of JEHOVAH?

 

Design deniers remain gatekeepers of the agrora?

 Healthy Debate? No Thanks, Says National Association of Biology Teachers

Herman B Bouma

A recent article here by Wesley J. Smith highlighted how mainstream science seeks to stifle opposition instead of encouraging open and honest debate. The article reminded me of a recent experience I had involving the Board of Directors of the National Association of Biology Teachers (NABT).

Nothing Unscientific About Design

When I attended the annual conference of the NABT in November 2023, I met Amanda Townley, the president-elect of the NABT. During our conversation I mentioned I had a proposal for amending the NABT Position Statement on Teaching Evolution and I asked her what was the procedure for proposing an amendment to a Position Statement. She asked what it concerned and I said it was a clarification that there is nothing unscientific about a theory of design, including in the field of biology. She said only members of the Board of Directors could propose Position Statements or amendments thereto, but she said she would be willing to present my proposal at an upcoming meeting of the Board. She asked me to send her an explanation of the proposal. The explanation I sent to her is set forth below.

Proposal by Herman B. Bouma for Amending NABT Position Statement on Teaching Evolution

I highly recommend that the NABT Position Statement on Teaching Evolution be amended to make clear that there is nothing inherently unscientific about a theory of design, including in the field of biology.

Suppose an American geologist went to England to study its rock formations and happened to come upon Stonehenge. As a scientist, is he precluded from theorizing that Stonehenge is the result of design? If he cannot refer to design, then he might come up with a theory that Stonehenge is the result of a volcanic eruption or the result of deposition by an ancient river. Those are certainly theories, but not very good ones. 

As a scientist, the geologist might have a predilection to explain Stonehenge in terms of natural processes. However, given what he knows about natural processes and given the layout of the stones in Stonehenge, and realizing science should not rule out any logical possibility, he would rightly conclude that design is the best explanation.

Many well-known scientists have had no problem theorizing about design in biology:

Darwin himself theorized that the first forms of life (at most, 8-10 forms) were the result of design;

Alfred Russel Wallace, who came up with a theory of natural selection at the same time as Darwin, later abandoned that theory and instead subscribed to a theory of design;

Louis Agassiz, a leading naturalist at Harvard University and “the father of the American scientific tradition,” opposed Darwin’s theory of natural selection and subscribed to a theory of design;

Even Richard Dawkins, the evolutionary atheist, has theorized that DNA might be the result of design (by space aliens);

Dr. Sudip Parikh, the CEO of the American Association for the Advancement of Science, addressed the concept of design when he spoke at the National Press Club on April 5, 2021. A questioner noted that Darwin himself theorized that the very first forms of life were the result of design and asked Dr. Parikh if theorizing about design in nature is unscientific. Instead of stating that it is unscientific, he said we should be teaching our students to follow the evidence, “wherever that evidence takes them.”

Of course, if a theory of design is presented in a science classroom of a public school in the United States, then, given the separation of church and state required by the First Amendment to the U.S. Constitution, the theory cannot identify the designer with any particular religion.

Acknowledging that there is nothing unscientific about a theory of design in biology would go a long way toward restoring trust in science, which is now seen by many as ignoring the obvious (design).

In an email to me on February 8, 2024, Ms. Townley (now the president of the NABT) informed me that she presented my proposal for amending the NABT Position Statement on Teaching Evolution at the January 2024 meeting of the Board of Directors. She said, “The board heard the proposal and voted to decline the amendment.”

I replied, “Could the Board give me its reasons for declining the amendment? In particular, could it respond to the arguments set forth in my statement supporting the proposal? That would be much appreciated.”

She replied, “The board declined discussion of the amendment and unanimously declined to amend the statement, therefore there are no counter arguments available to share.”

No Debate, Please; We’re Biology Teachers

In an email on February 9, 2024, I replied that I was “very disappointed the Board wasn’t interested in engaging in a healthy debate on the issue of design, especially since Louis Agassiz and Charles Darwin thought there was nothing unscientific about it.” I stated that scientists and science teachers should be interested in promoting debate, not stifling it. I also noted, “If the NABT is sincerely interested in promoting diversity, equity, and inclusion, it should promote the inclusion of those who share the perspective of Louis Agassiz and Charles Darwin, i.e., that design is a legitimate scientific concept.”

In an email to Ms. Townley on February 22, 2024, I again expressed my disappointment that the Board did not give any reasons for its rejection of my proposal and stated that “I would find it very helpful if you, or someone else at the NCSE [National Center for Science Education], could prepare for me a brief response to the arguments I presented in my proposal.” (I should note that, in addition to being the new president of the NABT, Ms. Townley is now also the new executive director of the NCSE.)

In a response the same day, Ms. Townley thanked me for my email but stated, “As noted previously, the Board deemed that the matter did not warrant discussion or debate and unanimously declined discussion. Your disappointment at that outcome is noted, however, no further discussion or argumentation will be provided.” Like the Board, neither she nor the NCSE had any interest in discussing or debating the question of whether design is a legitimate scientific concept in the field of biology.

It is clear that one way mainstream science seeks to stifle opposition is by simply refusing to discuss or debate opposing views. 

The body's war machine vs. Darwin.

 Newly Discovered War Machines in the Immune System

David Coppedge

An armored terrorist lurks in the city. Suddenly, thousands of pieces of sticky rope fly at him from all directions. They bind together, immobilizing him in a net. The net dissolves the intruder’s armor, and simultaneously signals for miniature robotic snipers who land on the net, using it as a scaffold. They fire armor-penetrating bullets through the net and into the terrorist’s compromised armor. Reinforcements install kill switches inside his body, forcing the terrorist to commit involuntary suicide.

Something like that describes a newly discovered molecular machine that helps fight infectious pathogens in our body cells. The news from Yale University says:

Yale scientists have discovered a family of immune proteins, which they describe as a “massive molecular machine,” that could affect the way our bodies fight infection. 

The immune proteins forming the net around the pathogen are called guanylate binding proteins, or GBPs. They have been known for a decade, but their mode of operation was only recently uncovered by Yale researchers. A short video shows these GBP1 proteins (the sticky ropes) as yellow pillar-shaped dimers rushing in, unfolding and linking up, surrounding the outer membrane of a bacterium (its armor). In short order the bacterium is surrounded with an inescapable straitjacket. There can be up to 30,000 of these proteins enclosing the pathogen in a type of body bag.

“What we found is among the most impressive examples of a biological machine in action that I’ve ever seen,” said John MacMicking, a professor of microbial pathogenesis and of immunobiology at Yale, and an Investigator of the Howard Hughes Medical Institute. MacMicking is senior author of the study.

The bacterial cell wall armor is no match for the immune system’s armor-piercing bullets. Even bacteria able to modify the lipopolysaccharides (LPS) that comprise the outer membrane (OM) have no chance. GBP1 knows all the configurations.

Human GBP1 still targeted cytosolic Stm [Salmonella enterica serovar Typhimurium] irrespective of bacterial size, shape, motility, or OM composition; the latter spanned LPS chains of different length, charge, and chemical structure. Such broad ligand promiscuity may help GBP1 combat gram-negative pathogens that modify their LPS moiety in an attempt to evade innate immune recognition and antimicrobial killing.

With the pathogen’s armor covered, the GBP proteins work to disentangle the lipopolysaccharide threads of the outer membrane. Having detected the help signal, reinforcements come in, firing caspase-4 grenades and interferon-γ kill switches into the bacterium, forcing it to commit pyroptosis, a form of programmed cell death.

“We are literally observing Mother Nature at work, looking at how these proteins operate in 3-dimensional space and at a particular location,” said MacMicking. “In just a few minutes they unfold and insert into the bacterial membrane to form a truly remarkable nanomachine and innate immune signaling platform.”

The bacteria coated with GBP straitjackets can be as small as 750 billionths of a meter (nanometers). The scientists found that this body-bag method works on bacteria regardless of shape. It works on viruses, too.

Imaging Design in Detail

This discovery was only made possible by recent advances in imaging technology. With cryo-electron microscopy, the researchers were able to “slice” whole live cells that had been quick-frozen. The resulting slices were assembled into tomograms, giving glimpses of heretofore unseen realities at work inside our body cells.

Our immune system mobilizes numerous proteins to detect viruses and bacteria — and to bring them under control. But until recently, limits to research technology have thwarted scientists’ understanding of how to prevent different pathogens from occupying and replicating within specific parts of our cells in the first place.

Harnessing the latest cryo‐electron microscopy techniques to look inside human cells, researchers at the Yale Systems Biology Institute have identified a family of large immune proteins that assemble into a massive signaling platform directly on the surface of microbial pathogens.

The researchers say they found thousands of GBPs building what amounted to a coat of armor (GBP1 coat complex) around the bacteria, allowing other defense proteins to recognize and kill encapsulated bacteria as well as mobilize immune cells for protection.

This reinforces an ID expectation that the more detail revealed, the more the design evidence becomes apparent. Evolution may look plausible from afar, but the angel is in the details. 

How Reinforcements Are Called

After the bacterium is immobilized, the GBP1 straitjacket becomes a scaffold for snipers to dismantle the intruder’s armor. The GBP family of proteins serve not only as the sticky ropes coating the intruder and disrupting its armor; they are also equipped with radios to call in the snipers and bomb squad. These proteins install the kill switches.

Thus, insertion of human GBP1 seems to disrupt lateral LPS-LPS interactions to compromise OM integrity. This not only activates the caspase-4 inflammasome pathway but allows the passage of small antimicrobial proteins such as APOL3 to directly kill pathogenic bacteria.

Human GBP1 was found to be “obligate for initiating the entire signaling cascade,” the scientists found via knockout experiments. It’s the captain in command.

Irreducible Complexity in Peace and War

ID advocates enjoy the examples of irreducible complexity (IC) in peacetime: the ATP synthase motor, kinesin, and the DNA translation mechanism. But when intruders threaten the life of a cell or its host organism, IC can fight with lethal intensity in an “all hands on deck!” war campaign. Its armed forces are always at the ready.

An emerging paradigm for innate immune signaling cascades is the higher-order assembly of repetitive protein units that generate large polymers capable of amplifying signal transduction. Our results identify human GBP1 as the principal repetitive unit, numbering thousands of proteins per bacillus, that undergoes dramatic conformational opening to establish a host defense platform directly on the surface of gram-negative bacteria. This platform enabled the recruitment of other immune partners, including GBP family members and components of the inflammasome pathway, that initiate protective responses downstream of activating cytokines such as interferon-γ. Elucidating this giant molecular structure not only expands our understanding of how human cells recognize and combat infection but may also have implication for antibacterial approaches within the human population.

Isn’t it nice to know that “eukaryotes have evolved compartment-specific immune surveillance mechanisms that alert the host to infection and recruit antimicrobial proteins that help bring microbial replication under control”? Actually, Charles Darwin never proved that his proposed mechanism of natural selection was capable of creating anything beyond simple variation within a species. His use of rhetoric and the analogy of domestic breeding was recognized even by his contemporaries as a mere suggestive hypothesis lacking scientific demonstration. 

Robert Shedinger shows this in Darwin’s own words in the new book Darwin’s Bluff. Aware that the Origin of Species was a “mere abstract” falling short scientific standards, Darwin promised a “big book” with the evidence. But he never published one. Why? Shedinger suggests he knew the evidence was lacking, and he was afraid of criticism. Instead, he relied on friends to promote his views. Darwin’s friends ran with “natural selection” as an all-purpose can opener to explain nature without an intelligent designer, using imagination and storytelling instead of hard evidence. In my experience reading the best of neo-Darwinian explanations, that’s still all they have to offer. Demonstration of selection’s alleged creative power is lacking, especially for irreducibly complex “massive molecular machines” like this one.

The discovery of a multi-component system able to mount a coordinated response to a threat speaks instead of Foresight: preparedness for a future eventuality. Darwin’s mechanism has no foresight or goal. At best, it can only preserve what it already has. Our uniform experience with foresight is that it is a capability of designing intelligence. That is Undeniable.

The language of engineering proves superior to Darwinese in describing molecular biology.

 Is It Becoming Acceptable to Speak of Biological Systems and Processes in Terms of Design?

David Coppedge

To the question posed in the headline, the answer is: It seems that way sometimes. And can speaking about design in such a context be done without getting hammered by the press, censored, or ridiculed? Perhaps. We’ll see. In the following example, think of the Darwinese as packing peanuts that can be removed to get to the important items inside.

A remarkable paper was published in BioEssays in January, with three authors from the University of Washington, Steven S. Andrews, H. Steven Wiley, and Herbert M. Sauro. None has any known sympathies for intelligent design. And yet much of their paper, “Design patterns of biological cells,” could have been written by any one of the PhDs presenting ideas at the Conference on Engineering in Living Systems (CELS).

Design patterns are generalized solutions to frequently recurring problems. They were initially developed by architects and computer scientists to create a higher level of abstraction for their designs. Here, we extend these concepts to cell biology to lend a new perspective on the evolved designs of cells’ underlying reaction networks. We present a catalog of 21 design patterns divided into three categories: creational patterns describe processes that build the cell, structural patterns describe the layouts of reaction networks, and behavioral patterns describe reaction network function. Applying this pattern language to the E. coli central metabolic reaction network, the yeast pheromone response signaling network, and other examples lends new insights into these systems.

Taken for Granted

The authors do not question Darwinian evolution, taking it for granted some 14 times in the paper. They speak of “the evolution of complex life” and convergent evolution, even speculating on whether life on other planets would evolve the same way as it has on Earth. Such talk is common in biomimetics literature as well: e.g., one writer spoke of an ingenious solution that was “refined over more than 420 million years of evolution,” as if natural selection gave an organism a head start. We can safely dismiss such statements as either poetic license or a misunderstanding of evolution in its usual unguided sense.

The important items are these: a catalog of 21 design patterns presented as solutions to engineering problems that cells have solved. Here’s one example:

Pores and pumps

Problem

Cellular components, from ions to proteins, typically need to be localized to the correct sides of membranes, including the plasma membrane, nuclear membrane, and other organelle membranes.

Solution.

Trans-membrane pores and pumps that use either active or passive transport. These pores and pumps are typically quite selective about what molecules they transmit and are often gated by external signals.

Cell membranes are quite permeable to oxygen, carbon dioxide, and other small nonpolar molecules but are effectively impermeable to larger and more charged species, a property that is essential to establishing and maintaining cell organization. Transport of these latter species occurs via transporters and channels, including ion channels, passive and active transporters for ions or other small molecules, proton pumps, ABC transporters, photosynthetic reaction centers for electron transport, and ATP synthase proteins for mitochondrial proton transport. The nuclear pore complex is a particularly large pore, which enables passive transport of small molecules and performs active transport on proteins that carry nuclear localization or nuclear export signals.

Readers can enjoy all 21 of these design patterns at their leisure in the open-access paper. The key takeaway is that the authors are looking at cells not as poorly designed conglomerations of haphazard parts that some blind tinkerer cobbled together from whatever pieces of stuff were available, but as collections of elegant solutions to real problems familiar to engineers. It represents a noteworthy step toward design thinking in biology from an unexpected source.

Motivation for the Paper

In a video within the paper, Dr. Sauro from the Bioengineering Department explains what motivated the paper. He begins his answer by holding up a copy of Bruce Alberts’s textbook Molecular Biology of the Cell, a thick tome with 1,500 pages. 

We started thinking: Is there any way we could abstract this information at a higher level, to help us comprehend what’s going on in a cell? And we were struck by this other book, which is totally different, Design Patterns. It’s a famous book in computer science by a so-called Gang of Four. It’s an interesting book because it describes how to solve complex problems in a sort of simplified way. And we thought: Is there was any way to marry this book with the Alberts book? That’s basically what motivated us to write this paper.

Following the order of the Design Patterns book, the authors divided systems in molecular biology into the same three basic categories: creational (such as the synthesis of a protein), structural (such as a phosphorylation cascade with inputs and outputs), and behavioral (such as a relaxation oscillator). 

From this outline, the authors correlated the computer scientists’ design patterns with their actual implementations in cells. The implementations look like logic diagrams in circuit design. Mechanisms can be quite different, Sauro explains, and yet the underlying design pattern can be the same when examined at a higher level. 

Importance of the Paper

Dr. Sauro feels the paper is important for a number of reasons. It provides a new way of communicating ideas in molecular biology, so that computational theorists and experimentalists can understand each other. Another benefit of the approach is to motivate other biochemists to build on their scaffolding of design patterns. This assumes many more engineering solutions can be identified; indeed, Sauro hopes others will help construct a searchable database of design patterns. Machine learning, then, could recognize patterns in newly identified networks in living organisms, expanding our understanding cellular networks. This would be very helpful for complex signaling networks, for instance, when it is hard to determine what is going on. Machine learning could compare known design patterns with the input/output behavior of the components, leading to an “Aha!” moment that untangles the complexity into a recognizable logic diagram.

Sauro credits primary author Steven Andrews for the clear and readable form in which the paper was presented. He hopes many scientists will read it, because it covers a wide range of biology and should interest all biologists — and, we would add, engineers. It is a springboard for ideas that also might interest those preparing for the next CELS conference.

Design patterns are recurrent solutions to commonly encountered problems. All biological cells encounter the same problems of how to construct the biochemical components that they are built from, how to connect those components together into useful reaction networks, and how to use those reaction networks to animate life.

The authors are quick to acknowledge certain predecessors in biological design thinking. 

The idea of understanding cellular systems in terms of functional parts is of course not new. For example, Hartwell et al. argued for a modular view of cell biology, Del Vecchio et al. emphasized the central roles of control mechanisms, and Khammash’s group has focused on mechanisms that provide integral feedback control. In contrast to these and other works, our focus is larger, covering a wider swath of cell biology mechanisms. Also, our perspective is subtly different. Rather than focusing on a particular biological topic, our emphasis is on the development of a catalog of the solutions that cells have evolved to solve specific problems. This design pattern concept is useful for abstracting a broad range of cell functions into a manageable set of distinct patterns, enabling one to better see parallels and

Future of the Design Pattern Approach

Clearly, design thinking is a fruitful heuristic for discovery. But what about the “interlinked and hierarchical design patterns” mentioned next? Could those evolve? In the Illustra film Darwin’s Dilemma, such hierarchical patterns (exemplified in the body plans of the Cambrian fauna), are shown to resist Darwinian approaches because they require top-down design, as with a blueprint or logic diagram before assembly begins. Is this not the case with all “design patterns”?

The authors grant too much creativity to the neo-Darwinian mechanism. They assume that problems motivate their own solutions in biology:

Going even farther afield, one can speculate about life on other planets, where again the same problems would likely arise, and again would necessarily be addressed with many of the same solutions. This suggests that the design patterns listed here, along with others not addressed, could be reasonably considered universal principles of life.

Most likely this kind of speculation will wither on its own as the successors of Bruce Alberts add more pages to molecular biology textbooks. If, as the authors conclude, those involved in simulating cells will refer to a database of design patterns in their multiscale modeling, it should become increasingly clear that cells resemble engineered masterpieces. Darwinese would then decline as superfluous words in future research projects focused on design patterns.

The tech of muscles vs. Darwin

 

OOL researchers may have tossed the answer in the trash?

 Aliens in the Garbage

Daniel Witt

Garry Nolan is the Rachford and Carlota A. Harris Professor of Pathology at Stanford University. He is a productive and respected immunologist who has published more than 330 research articles, and is a pioneering inventor of laboratory tools for his field.  

He also believes in extraterrestrials — that is, intelligent non-human visitors to Earth. Though Nolan admits that the publicly available evidence has not yet reached the standard of scientific proof, he says that he has been personally convinced by the evidence he has examined. More importantly, he is adamant that whether extraterrestrial visits have actually happened or not, scientists should be exploring the possibility rather than ignoring it.

Not Everyone Agrees

Some people — whether they would put it in so many words or not — believe that certain types of answers are simply off-limits in a scientific inquiry. Nolan has no patience for this notion. He says: 

That’s not how a scientist operates. If you take a potential solution off the table and you throw it in the garbage, you could spend the rest of eternity searching around on the table for the answer, and you threw it in the garbage. 

That’s very well-put. There’s no harm in keeping a potential answer on the table, and there could be harm in tossing it in the trash. Without saying anything about the evidence itself, the philosophical principle underlying Nolan’s investigation is sound. And it’s a principle with much wider applications. 

By investigating the possibility of intelligent, non-human causes for certain phenomena, Nolan is, in fact, working as an intelligent design researcher — whether he would embrace that label or not (and I see no reason to think he would). The underlying logic of an argument for alien design in mysterious artifacts or conditions is the same logic underlying the arguments for design in the origin of life or the laws of the universe. 

Nolan seems to be aware of this. Asked in a recent interview what he considered the most fascinating aspect of biology at the cellular level, he had this to say:  

The micromachines and the nanomachines that proteins make and become. That to me is the most interesting: the fact that you have this, basically, dynamic computer within every cell that’s constantly processing its environment, and at the heart of it is DNA, which is a dynamic machine, a dynamic computation process. People think of the DNA as a linear code. It’s codes within codes within codes, and it is the, actually, the epigenetic state that’s doing this amazing processing. I mean, if you ever wanted to believe in God, just look inside the cell.

He goes on to say that the appearance of design goes all the way down to the laws of physics and the fabric of the universe itself. 

Yet as far as “wanting to believe in God” goes, Nolan isn’t sure that he does. He prefers to posit alien intelligences and remain agnostic, for the time being, about their natures. Within the bounds of pure science (not getting into philosophy), that’s a perfectly valid stance to take, since examining an artifact can’t tell you everything about its designer. Whether you personally think that God or a non-God extraterrestrial is the more credible explanation, the design inference is the same. 

Since he is making that inference in his research, it is not surprising that Nolan is running up against the same objection that other ID researchers do: the objection that certain types of explanation should be rejected a priori because they are (by definition) unscientific.

This Is All Well and Fine 

That is, as long as scientists happen to be investigating something with a true explanation that belongs to the set of approved options. But suppose it doesn’t? Suppose the real explanation lies in the “off the table” category of answers? (If you don’t think that’s possible, suppose.) Should any scientist spend his or her whole life looking for a type of answer that doesn’t exist? At what point do we start considering the off-limit options? That’s Nolan’s point about throwing a potential solution in the garbage — once you do that, you could be doomed to an eternity of futile searching.  

The pressure to dig around in the garbage for discarded explanations is growing in many scientific disciplines. It is probably strongest, at the moment, in the field of origin of life (OOL) research. The difficulty (read: impossibility) of crafting a coherent explanation for how self-replicating structures could arise through deterministic processes has led some scientists, such as Richard Dawkins and Francis Crick, to admit that alien intelligence is a possible cause. (So Dawkins and Crick join the ranks of intelligent design theorists, albeit unwillingly.) 

Honest OOL researchers admit that they reject ID arguments not because those arguments lack all merit, but simply because they are off the table, out-of-bounds. For example, take some interview comments by OOL researcher Joana Xavier (also discussed by David Klinghoffer in a recent post). She said:  

I read Signature in the Cell by Stephen Meyer… and I must tell you, I found it one of the best books I’ve read in terms of really pointing, putting the finger on the questions. What I didn’t like was the final answer, of course. But I actually tell everyone I can, “Listen, read that book. Let’s not put Intelligent Design in a spike and burn it. Let’s understand what they’re saying and engage.” And it’s a really good book that really exposes a lot of the questions that people try to sweep under the carpet. It’s just … I think we must have a more naturalistic answer to these processes. There must be! Otherwise I’ll be out of a job. [laughs]… I like to see myself as a very open-minded person in terms of metaphysics, but that’s not to say that the molecular study of the cell should just end. I don’t even think that the ID people want it to end — it’s just the pressure to accept that there’s no answer through naturalistic means that I’m a bit against.  

To her credit, Xavier is upfront about her reasoning. Not everyone is; some scientists would prefer to pretend that the case for ID is pure rubbish, rather than admit that they are simply working in a framework that cannot accept a conclusion of intelligent design. 

Xavier, by contrast, makes it quite clear that she does not believe in accepting a non-naturalistic answer to a scientific question. (I’m not sure whether she would apply this to the idea that a “natural” intelligent being, such as an extraterrestrial, created the first life.) It’s great she acknowledges that her community’s philosophical commitments don’t justify sweeping the arguments of ID proponents under the rug. But is it really practical to engage with an argument while giving yourself the rule that you cannot accept it? 

“This Appears Designed”

Xavier’s fear is that to say, “This appears designed,” would be to give up on the quest to find a natural cause: there might be one, but scientists would never find it because they ended their quest by shrugging their shoulders and saying, “I guess God did it.” 

Her fear is justified. It’s a real danger. Sometimes, things that at first glance appear designed turn out to have purely natural causes. We shouldn’t close our minds to naturalistic explanations just because an intelligent designer could have done it. 

But OOL researchers such as Xavier should realize that the opposite danger also exists. If you begin by saying, “Unguided natural causes did it,” then if unguided natural causes didn’t do it, you will miss the true explanation. You might, as Dr. Nolan said, “spend the rest of eternity searching around on the table for the answer, and you threw it in the garbage.”

Intelligent design theory is not opposed to naturalistic explanations. It is merely open to non-naturalistic explanations. You don’t have to throw any explanation in the garbage: not natural processes, not intelligent mind, not God, not aliens. The deeper purpose of science is not to find a naturalistic explanation, but to find the true explanation. Every possibility must remain on the table in the search for truth. 

Out of a Job?

Will that lead to OOL researchers being put “out of a job,” as Xavier fears? Well, it’s certainly true that once you find a definite answer to a problem, you may have little work left to do on that problem. So maybe one day (probably pretty far off) origin-of-life researchers will settle the question once and for all, and have nothing left to do. 

But is that the worst thing that could happen? Scientists work themselves out of a job all the time. Normally, when they do, they just move on to another question. Isn’t that better than throwing the answer in the garbage, just to ensure you can keep searching for it forever? 

Time to end the quest for engineerless engineering?

Time to end the quedt Engineering Innovation from Cuttlefish 

Daniel Witt

Editor’s note: We are delighted to welcome Daniel Witt as a new contributor. In case you are curious about the background in his author photo, it was taken in a pyramid in Sudan, at Meroë.

Last month, Cambridge University’s science magazine, Bluesci, announced that researchers have developed a new camera based on cuttlefish eyes. Cuttlefish have unusual W-shaped pupils that allow them to see well in both dim and bright conditions as they navigate in deeper or shallower waters. The researchers successfully reverse-engineered the cuttlefish’s eye structure to create a camera that works better in conditions of highly variable luminosity.   

Cuttlefish are extraordinary creatures, and this is not the first time engineers have learned from them. In 2013, the Washington Post reported that the Office of Naval Research was funding a project to mimic the cuttlefish’s color-changing skin, with potential application in submarine camouflage technology. In 2009, NBC reported that MIT scientists had studied cuttlefish skin to design a TV screen that used less than 1 percent of the power that other screens at the time used. The reverse-engineering opportunities just keep coming. 

Usually, “reverse-engineering” implies that … well, engineering took place beforehand; design, in other words. And, as it happens, the news from Cambridge explicitly refers to cuttlefish eyes as “finely-designed.” 

It was probably a slip-up. No doubt the writer would defend this as a mere convention of speech — I doubt that he was trying to imply that actual design took place in the creation of cuttlefish eyes. But isn’t it interesting that it’s so difficult to talk about these things without invoking the language of design? 

Caught in the Weeds

Maybe it doesn’t seem so interesting. But that’s only because we’re so used to this reality. It can be easy to get caught in the weeds in the debate over whether Darwinian mechanisms are sufficient to explain life, and forget the reason the debate is going on in the first place. The debate only exists because these implausibly intricate engineering marvels exist. It did not have to be so. The universe could have been otherwise. It was never a given that when scientists looked deeper into life, they would find such exquisite designs; but they did.   

As we gain the ability to look deeper and deeper into the inner workings of life, we seem to be entering a new renaissance of collaboration between biologists and engineers. Physicist Brian Miller recently noted this trend in the developing field of systems biology:  

[W]hen you look at the design conversation, who controls it? It’s people who don’t have the expertise to really address it. They’re not engineers. They’ve been trained to see the world through this materialist grid, so they assume on faith that there’s no evidence of design, and then they find various reasons to justify that belief. In contrast, what you’re seeing in biology is really a revolution that’s at its early stages, because engineers are working more and more with biologists, and what you’re seeing is, when they do that they use design language, they use design assumptions.

An Engineering Marvel 

As we all know, the prevailing theory insists that this appearance of design is mere illusion. But when engineers team up with biologists to learn how to copy the mechanisms of life, they aren’t thinking about that. Whether a cuttlefish eye is designed, or merely in every way appears to be designed, is irrelevant. The point is that it is an engineering marvel, and engineers can learn from it. 

This fact is important, not because it is in-and-of-itself proof of design, but because it tells us something practical about the competing theories and their respective productivity. 

Proponents of the neo-Darwinian model are fond of asserting that the naysaying arguments of ID-supporters (regarding irreducible complexity, non-traversable fitness landscapes, the probabilistic inability of Darwinian mechanisms to make meaningful changes to life within the lifespan of earth, lack of any confirmed observation of constructive mutations, etc.) make little difference to the actual research underway in biology. That is to say: Life only makes sense “in the light of evolution,” and the critics of that framework are just flies buzzing in the background. 

A Verbal Gloss

The truth is something close to the opposite. Assumptions of macroevolution almost never have any practical bearing on research in biology. Darwinian evolution is invoked as a verbal gloss, not as a vital presupposition. Chemist and National Academy of Sciences member Philip S. Skell famously asked 70 distinguished researchers whether they would have done their work differently if they had believed Darwin’s theory was false. They all answered no.

Dr. Skell isn’t the only one to point this out; it’s the reality of the field. An assumption of design, by contrast, is quite often an essential foundation to successful research projects in biology — whether the design language is expurgated from the final presentation or not. 

Biologists will continue to debate whether this design is real or only apparent. But in the meanwhile, intelligent design-based research will keep moving forward, untroubled by those debates — as it always has. 

A match made in heaven?

 Can the Laws of Nature Design Life? Emily Reeves Considers the Compatibility of Evolution and ID

Andrew McDiarmid

Can intelligent design and evolution work together? It’s an intriguing idea that is welcomed by some, but does the scientific evidence support it? On a new episode of ID the Future, host Casey Luskin speaks with Dr. Emily Reeves to discuss her contribution to a recent paper critiquing theologian Rope Kojonen’s proposal that mainstream evolutionary biology and intelligent design have worked in harmony to produce the diversity of life we see on earth. 

Dr. Reeves starts by summarizing the Compatibility of Evolution and Design (CED) argument before also summarizing her team’s response to it. “CED is a great work of scholarship,” says Reeves, “but I think its relevance really hinges on whether empirical evidence supports Kojonen’s version of how the design is implemented within evolutionary theory, and then, of course, whether design arguments…are really compatible with evolutionary theory.” 

Reeves and Luskin go on to critique Dr. Kojonen’s conception of design. His model posits that the laws of nature have been front-loaded with design by an intelligent designer. But laws are not creative forces on their own – they only describe forces already in action. There’s no empirical evidence that the laws of nature could do the type of heavy lifting required to steer evolutionary processes toward success. As an example, Dr. Reeves describes how the law of gravity interacts with a growing plant. Gravity is used as a cue in the plant’s biology, but it doesn’t power the plant’s ability to grow. Download the podcast or listen to it here.

ID is superstition masquerading as science?

 Are Proponents of ID Religiously Motivated, and Does It Matter?

Jonathan McLatchie

Recently, someone asked me to comment on an article, published in 2017, by John Danaher, a lecturer in the Law School at the University of Galway, Ireland. He is widely published on legal and moral philosophy, as well as philosophy of religion. In his article, Danaher alleges that proponents of intelligent design (ID) are religiously motivated. He also asserts that the argument for ID from irreducible complexity has conceptual problems, and that systems that we deem to be irreducibly complex can be adequately explained by co-optation of components performing other roles in the cell. In two articles, I will address his concerns about our supposed religious motives, and then tackle his specific objections to irreducible complexity.

Do We Have Religious Motives?

Danaher opens his essay by reminiscing about his days as a student when he first encountered ID.

When I was a student, well over a decade ago now, intelligent design was all the rage. It was the latest religiously-inspired threat to Darwinism (though it tried to hide its religious origins). It argued that Darwinism could never account for certain forms of adaptation that we see in the natural world. 

What made intelligent design different from its forebears was its seeming scientific sophistication. Proponents of intelligent design were often well-qualified scientists and mathematicians, and they dressed up their arguments with the latest findings from microbiology and abstruse applications of probability theory. My sense is that the fad for intelligent design has faded in the intervening years, though I have no doubt that it still has its proponents.

These paragraphs betray the fact that the author is quite out of touch with the literature on ID. 

Stronger than Ever

First, ID has come a long way since the early 2000s. Far from having faded, it is now stronger than ever, having more academic proponents (and many more peer-reviewed publications) than at any time in its history. Its arguments are far more developed and sophisticated than in the early 2000s and this trend is likely to continue. 

Second, it is unclear in what sense Danaher refers to the “religious origins” of ID. It is certainly true that having a religious perspective, predisposing one towards theism, creates a plausibility structure that opens one’s mind to the possibility of there being measurable evidence of design in the universe, including in living organisms. Thus, being independently persuaded of the truth of a theistic religion (in my case, Christianity) is positively relevant to one’s assessment of the prior probability (or, intrinsic plausibility) of ID. However, even if one is not persuaded of theistic religion, the evidence of design in the natural world is, in my opinion, sufficient to overwhelm even a very low prior. Indeed, the cosmological evidence that our universe has a finite history; the fine-tuning of the laws and constants of our universe; the prior environmental fitness of nature for complex life; the optimization of the universe for scientific discovery and technology; and the biological evidence of design all point univocally and convergently in the direction of a cosmic creator. Thus, ID has attracted support from scholars who are not themselves adherents of any religion, including Michael Denton, David Berlinski, and Steve Fuller. Paleontologist and frequent Evolution News contributor Günter Bechly, though a Christian believer now, was not sympathetic to Christianity when he first came to be persuaded of ID.

Misguided on Many Levels

Later in the essay, Danaher further remarks

The claim is not that God must have created the bacterial flagellum but, rather, that an intelligent designer did. For tactical reasons, proponents of intelligent design liked to hide their religious motivations, trying to claim that their theory was scientific, not religious in nature. This was largely done in order to get around certain legal prohibitions on the teaching of religion under US constitutional law. I’m not too interested in that here though. I view the intelligent design movement as a religious one, and hence the arguments they proffer as on a par with pretty much all design arguments.

These comments are misguided on many levels.

First, the claim that we ID proponents are not clear about our personal religious persuasions is patently false. Speaking for myself, I have been very clear that I am a Christian theist, though my grounds for being persuaded of that conclusion are wholly independent of the science of ID. And I am by no means unusual. Virtually every leading ID proponent — from Michael Behe to William Dembski to Stephen Meyer to Phillip Johnson to David Klinghoffer to Casey Luskin to Brian Miller to Ann Gauger and many others — has been totally open about his or her personal religious beliefs. In the world of intelligent design, no one is hiding anything about religious beliefs, including those who lack religious beliefs.

Second, ID is a scientific argument, and when evaluating a scientific argument, the motives of its proponents are irrelevant. As Casey Luskin writes,

[I]n science, the motives or personal religious beliefs of scientists don’t matter; only the evidence matters. For example, the great scientists Johannes Kepler and Isaac Newton were inspired to their scientific work by their religious convictions that God would create an orderly, rational universe with comprehensible physical laws that governed the motion of the planets. They turned out to be right — not because of their religious beliefs — but because the scientific evidence validated their hypotheses. (At least, Newton was thought to be right until Einstein came along.) Their personal religious beliefs, motives, or affiliations did nothing to change the fact that their scientific theories had inestimable scientific merit that helped form the foundation for modern science.

To attack an idea because of the alleged religious motives of its proponents is to commit the genetic fallacy, and that is exactly what Danaher has done here.

Third, ID is not a religious argument. Though ID provides strong evidence for a broadly theistic perspective, the argument itself is grounded in the scientific method. ID does not aid in evaluating the merits of one particular religious tradition over another. ID does not even technically commit one to theism, though I would contend that God is the best candidate for the identity of the designer (as Stephen Meyer argues in his recent book, Return of the God Hypothesis). Thus, ID rightly attracts people of all religious persuasions and none (including Orthodox Jews, Muslims, and agnostics). This is important because it shows that ID is not about supporting one particular religion. We, therefore, strive to be honest about the limitations of ID while being careful not to overstate what the scientific evidence alone can tell us.

What About Evolution?

Finally, if Danaher wants to scrutinize the religious motives of ID proponents, we have to consider what such a line of attack would do to evolution. Casey Luskin has documented (see here or here) the extensive anti-religious beliefs, motives, and affiliations of many leading evolution-advocates. While I (and Luskin) would maintain that evolution is science, one must ask what would happen to evolution if the religious (or anti-religious) beliefs of its proponents suddenly became relevant to assessing its merits.

“Teach the Controversy”

Danaher’s statement that the claim that ID is scientific and not religious “was largely done in order to get around certain legal prohibitions on the teaching of religion under US constitutional law” is historically incorrect. Discovery Institute (the leading organization funding research into, and promoting the public understanding of, ID) does not support attempts to legally protect the teaching of ID in public schools. In fact, since Discovery Institute’s earliest involvement in major public education debates in the U.S. (in Ohio in 2002), it has not supported mandating the teaching of ID in public schools. This is not because we feel that ID is unconstitutional. ID, much like the Big Bang in cosmology, may be friendly to a broadly theistic perspective. However, this does not make the idea itself a religious one, just as the Big Bang theory is not a religious idea. Thus, there is nothing intrinsic to ID that would render it unconstitutional under the First Amendment. However, attempts to legislatively protect the teaching of ID tend to politicize the theory, and we believe that the merits of ID ought to be debated in the scientific journals, not in the courtroom. Rather, Discovery Institute advocates a “teach the controversy” model, where the strengths and weaknesses of scientific theories (including evolution) are presented and discussed. All of this is stated clearly and openly on our Science Education policy page:

As a matter of public policy, Discovery Institute opposes any effort to require the teaching of intelligent design by school districts or state boards of education. Attempts to require teaching about intelligent design only politicize the theory and will hinder fair and open discussion of the merits of the theory among scholars and within the scientific community. Furthermore, most teachers at the present time do not know enough about intelligent design to teach about it accurately and objectively. 

Instead of recommending teaching about intelligent design in public K-12 schools, Discovery Institute seeks to increase the coverage of evolution in curriculum. It believes that evolution should be fully and completely presented to students, and they should learn more about evolutionary theory, including its unresolved issues. In other words, evolution should be taught as a scientific theory that is open to critical scrutiny, not as a sacred dogma that can’t be questioned.

Thus, Danaher is ill-informed about Discovery Institute’s long-standing education policy. In a second article, I shall address his specific concerns regarding the argument from irreducible complexity.

A theory of everything re:design detection? V

 Orgelian Specified Complexity

William Dembski

As I noted at the start of this series on “specified complexity,” which I’m concluding today, Leslie Orgel introduced that term in his 1973 book The Origins of Life. Although specified complexity as developed by Winston Ewert, Robert Marks, and me attempts to get at the same informational reality that Orgel was trying to grasp, our formulations differ in important ways. 

For a fuller understanding of specified complexity, as an appendix to the series, it will therefore help to review what Orgel originally had in mind and to see where our formulation of the concept improves on his. Strictly speaking, this subject is mainly of historical interest. Because The Origins of Life is out of print and hard to get, I will quote from it extensively, offering exegetical commentary. I will focus on the three pages of his book where Orgel introduces and then discusses specified complexity (pages 189–191). 

"Terrestrial Biology”

Orgel introduces the term “specified complexity” in a section titled “Terrestrial Biology.” Elsewhere in his book, Orgel also considers non-terrestrial biology, which is why the title of his book refers to the origins (plural) of life — radically different forms of life might arise in different parts of the universe. To set the stage for introducing specified complexity, Orgel discusses the various commonly cited defining features of life, such reproduction or metabolism. Thinking these don’t get at the essence of life, he introduces the term that is the focus of this series:

It is possible to make a more fundamental distinction between living and nonliving things by examining their molecular structure and molecular behavior. In brief, living organisms are distinguished by their specified complexity. Crystals are usually taken as the prototypes of simple, well-specified structures because they consist of a very large number of identical molecules packed together in a uniform way. Lumps of granite or random mixtures of polymers are examples of structures which are complex but not specified. The crystals fail to qualify as living because they lack complexity; the mixtures of polymers fail to qualify because they lack specificity. (p. 189)

So far, so good. Everything Orgel writes here makes good intuitive sense. It matches up with the three types of order discussed at the start of this series: repetitive order, random order, complex specified order. Wanting to put specified complexity on a firmer theoretical basis, Orgel next connects it to information theory:

These vague ideas can be made more precise by introducing the idea of information. Roughly speaking, the information content of a structure is the minimum number of instructions needed to specify the structure. One can see intuitively that many instructions are needed to specify a complex structure. On the other hand, a simple repeating structure can be specified in rather few instructions. Complex but random structures, by definition. need hardly be specified at all. (p. 190)

Orgel’s elaboration here of specified complexity calls for further clarification. His use of the term “information content” is ill-defined. He unpacks it in terms of “minimum number of instructions needed to specify a structure.” This suggests a Kolmogorov information measure. Yet complex specified structures, according to him, require lots of instructions, and so suggest high Kolmogorov information. By contrast, specified complexity as developed in this series requires low Kolmogorov information. 

At the same time, for Orgel to write that “complex but random structures … need hardly be specified at all” suggests low Kolmogorov complexity for random structures, which is exactly the opposite of how Kolmogorov information characterizes randomness. For Kolmogorov, the random structures are those that are incompressible, and thus, in Orgel’s usage, require many instructions to specify (not “need hardly be specified at all”). 

Perhaps Orgel had something else in mind — I am trying to read him charitably — but from the vantage of information theory, his options are limited. Shannon and Kolmogorov are, for Orgel, the only games in town. And yet, Shannon information, focused as it is on probability rather than instruction sets, doesn’t clarify Orgel’s last remarks. Fortunately, Orgel elaborates on them with three examples:

These differences are made clear by the following example. Suppose a chemist agreed to synthesize anything that could be described accurately to him. How many instructions would he need to make a crystal, a mixture of random DNA-like polymers or the DNA of the bacterium E. coli? (p. 190)

This passage seems promising for understanding what Orgel is getting at with specified complexity. Nonetheless, it also suggests that Orgel is understanding information entirely in terms of instruction sets for building chemical systems, which then weds him entirely to a Kolmogorov rather than Shannon view of information. In particular, nothing here suggests that he will bring both views of information together under a coherent umbrella. 

The Language of Short Descriptions

Here’s is how Orgel elaborates the first example, which is replete with the language of short descriptions (as in the account of specified complexity given in this series):

To describe the crystal we had in mind, we would need to specify which substance we wanted and the way in which the molecules were to be packed together in the crystal. The first requirement could be conveyed in a short sentence. The second would be almost as brief, because we could describe how we wanted the first few molecules packed together, and then say “and keep on doing the same.” Structural information has to be given only once because the crystal is regular. (p. 190)

This example has very much the feel of our earlier example in which Kolmogorov information was illustrated in a sequence of 100 identical coin tosses (0 for tails) described very simply by “repeat ‘0’ 100 times.” For specified complexity as developed in this series, an example like this one by Orgel yields a low degree of specified complexity. It combines both low Shannon information (the crystal forms reliably and repeatedly with high probability and thus low complexity) and low Kolmogorov information (the crystal requires a short description of instruction set). It exhibits specified non-complexity, or what could be called specified simplicity.

A Fatal Difficulty

Orgel’s next example, focused on randomness, is more revealing, and indicates a fatal difficulty with his approach to specified complexity:

It would be almost as easy to tell the chemist how to make a mixture of random DNA-like polymers. We would first specify the proportion of each of the four nucleotides in the mixture. Then, we would say, “Mix the nucleotides in the required proportions, choose nucleotide molecules at random from the mixture, and join them together in the order you find them.” In this way the chemist would be sure to make polymers with the specified composition, but the sequences would be random. (p. 190)

Orgel’s account of forming random polymers here betrays information-theoretic confusion. Previously, he was using the terms “specify” and “specified” in the sense of giving a full instruction set to bring about a given structure — in this case, a given nucleotide polymer. But that’s not what he is doing here. Instead, he is giving a recipe for forming random nucleotide polymers in general. Granted, the recipe is short (i.e., bring together the right separate ingredients and mix), suggesting a short description length since it would be “easy” to tell a chemist how to produce it. 

But the synthetic chemist here is producing not just one random polymer but a whole bunch of them. And even if the chemist produced a single such polymer, it would not be precisely identified. Rather, it would belong to a class of random polymers. To identify and actually build a given random polymer would require a large instructional set, and would thus indicate high, not low Kolmogorov information, contrary to what Orgel is saying here about random polymers.

Finally, let’s turn to the example that for Orgel motivates his introduction of the term “specified complexity” in the first place:

It is quite impossible to produce a corresponding simple set of instructions that would enable the chemist to synthesize the DNA of E. coli. In this case, the sequence matters: only by specifying the sequence letter-by-letter (about 4,000,000 instructions) could we tell the chemist what we wanted him to make. The synthetic chemist would need a book of instructions rather than a few short sentences. (p. 190)

Orgel’s Takeaway

Given this last example, it becomes clear that for Orgel, specified complexity is all about requiring a long instructional set to generate a structure. Orgel’s takeaway, then, is this:

It is important to notice that each polymer molecule on a random mixture has a sequence just as definite as that of E. coli DNA. However, in a random mixture the sequences are not specified. Whereas in E. coli, the DNA sequence is crucial. Two random mixtures contain quite different polymer sequences, but the DNA sequences in two E. coli cells are identical because they are specified. The polymer sequences are complex but random: although E. coli DNA is also complex, it is specified In a unique way. (pp. 190–191)

This is confused. The reason it’s confused is that Orgel’s account of specified complexity commits a category mistake. He admits that a random sequence requires just as long an instruction set to generate as E. coli DNA because both are, as he puts it, “definite.” Yet with random sequences, he looks at an entire class or range of random sequences whereas with E. coli DNA, he is looking at one particular sequence. 

Orgel is correct, as far as he goes, that from an instruction set point of view, it’s easy to generate elements from such a class of random sequences. And yet, from an instruction set point of view, it is no easier to generate a particular random sequence than a particular non-random sequence, such as E. coli DNA. That’s the category mistake. Orgel is applying instruction sets in two very different ways, one to a class of sequences, the other to particular sequences. But he fails to note the difference. 

A Different Tack

The approach to specified complexity that Winston Ewert and I take, as characterized in this series, takes a different tack. Repetitive order yields high probability and specification, and therefore combines low Shannon and low Kolmogorov information, yielding, as we’ve seen, what can be called specified simplicity. This is consistent with Orgel. But note that our approach yields a specified complexity value (albeit a low one in this case). Specified complexity, as a difference between Shannon and Kolmogorov complexity, takes continuous values and thus comes in degrees. For repetitive order, specified complexity, as characterized in this series, will thus take on low values.

That said, Orgel’s application of specified complexity to distinguish a random nucleotide polymer from E. coli DNA diverges sharply from how specified complexity as outlined in this series applies to these same polymers. A random sequence, within the scheme outlined in the series, will have large Shannon information but also, because it has no short description, will have large Kolmogorov information, so the two will cancel each other, and the specified complexity of such a sequence will be low or indeterminate.

On the other hand, for E. coli DNA, within the scheme outlined in this series, there will be work to do in showing that it actually exhibits specified complexity. The problem is that the particular sequence in question will have low probability and thus high Shannon information. At the same time, that particular sequence will be unlikely to have a short exact description. Rather, what will be needed to characterize the E. coli DNA as exhibiting specified complexity within the scheme of this series is a short description to which the sequence answers but which also describes an event of small probability, thus combining high Shannon information with low Kolmogorov information. 

Specified complexity as characterized in this series and applied to this example will thus mean that the description will include not just the particular sequence in question but a range of sequences that answer to the description. Note that there is no category mistake here as there was with Orgel. The point of specified complexity as developed in this series is always with matching events and descriptions of those events, where any particular event is described provided it answers to the description. For instance, a die rolls exhibiting a 6 answers to the description “an even die roll.”

So, is there a simple description of the E. coli DNA that shows this sequence to exhibit specified complexity in the sense outlined in this series? That’s in fact not an easy question to answer. The truth of Darwinian evolution versus intelligent design hinges on the answer. Orgel realized this when he wrote the following immediately after introducing the concept of specified complexity, though his reference to miracles is a red herring (at issue is whether life is the result of intelligence, and there’s no reason to think that intelligence as operating in nature need act miraculously):

Since, as scientists, we must not postulate miracles we must suppose that the appearance of “life” is necessarily preceded by a period of evolution. At first, replicating structures are formed that have low but non-zero information content. Natural selection leads to the development of a series of structures of increasing complexity and information content, until one is formed which we are prepared to call “living.” (p. 192)

Orgel is here proposing the life evolves to increasing levels of complexity, where at each stage nothing radically improbable is happening. Natural selection is thus seen as a probability amplifier that renders probable what otherwise would be improbable. Is there a simple description to which the E. coli DNA answers and which is highly improbable, not just when the isolated nucleotides making up the E. coli DNA are viewed as a purely random mixture but rather by factoring in their evolvability via Darwinian evolution?

A Tough Question

That’s a tough question to answer precisely because evaluating the probability of forming E. coli DNA with or without natural selection is far from clear. Given Orgel’s account of specified complexity, he would have to say that the E. coli DNA exhibits specified complexity. But within the account of specified complexity given in this series, ascribing specified complexity always requires doing some work, finding a description to which an observed event answers, showing the description to be short, and showing the event precisely identified by the description has small probability, implying high Shannon information and low Kolmogorov information. 

For intelligent design in biology, the challenge in demonstrating specified complexity is always to find a biological system that can be briefly described (yielding low Kolmogorov complexity) and whose evolvability, even by Darwinian means, has small probability (yielding high Shannon information). Orgel’s understanding of specified complexity is quite different. In my view, it is not only conceptually incoherent but also stacks the deck unduly in favor of Darwinian evolution. 

To sum up, I have presented Orgel’s account of specified complexity at length so that readers can decide for themselves which account of specified complexity they prefer, Orgel’s or the one presented in this series.

Editor’s note: This article appeared originally at BillDembski.com