Casey Luskin | 27 April 2021 | 12 min read
Intelligent design—often called “ID”—is a scientific theory which holds that some features of the universe and living things are best explained by an intelligent cause rather than an undirected process such as natural selection. ID theorists argue that intelligent design can be inferred by finding in nature the type of information and complexity which in our experience arises from an intelligent cause.
Proponents of neo-Darwinian evolution contend that the information in life arose via blind, mechanistic processes that show no scientific evidence of guidance by intelligent design. ID proponents contend that the information in life does not appear to have an unguided origin, but arose via purposeful, intelligently guided processes. Both claims are scientifically testable using the standard methods of science. But ID theorists say that when we use the scientific method to explore nature, the evidence points away from blind material causes, and reveals intelligent design.
Intelligent Design in Everyday Reasoning
Whether we realize it or not, we detect design constantly in our everyday lives. In fact, our lives often depend on inferring intelligent design. Imagine you are driving along a road and come to a place where the asphalt is covered by a random splatter of paint (see the top graphic). You would probably ignore the paint and keep driving onward—with potentially drastic consequences.
Figure 1. We intuitively make design inferences every day—often with great consequences! Credit: Image created by Valerie Gower. Copyright © Discovery Institute.
But what if the paint is arranged in the form of a warning (see the bottom image)? In this case, you would immediately recognize that someone is trying to convey a message, and would make a design inference that could save your life. You would recognize that an intelligent agent was trying to communicate an important message. You would intuitively appreciate that only an intelligent agent can use foresight to accomplish an end-goal—such as arranging paint in a particular pattern that matches English words to convey an important warning. Recognizing this unique ability of intelligent agents allows scientists in many fields to detect design.
Intelligent Design in Archaeology and Forensics
ID is in the business of trying to discriminate between naturally caused objects on the one hand, and intelligently caused objects on the other. A variety of scientific fields already use ID reasoning. For example, archaeologists find and artifact and they need to determine whether it arrived at its shape through natural processes, and it’s just another rock, or whether it was carved for a purpose by an intelligence. Likewise forensic scientists distinguish between naturally caused deaths, and intelligently caused deaths, such as murder. These are important questions that our legal system must answer. The Search for Extra-Terrestrial Intelligence uses similar ID reasoning to discriminate between radiosignals coming from natural objects (like stars) and those which might have been sent by an intelligent alien civilization. Following such logic, design theorists ask a simple question: If we can use science to detect design in other fields, why should it be controversial when we detect it in biology or cosmology?
So how does ID work? Scientists investigating ID start by observing how intelligent agents act when they design things. Human intelligent agents provide a large dataset for studying the products of the action of intelligent agents. We find that when intelligent agents act, they generate large amounts of information. In the example above, we detected design in a message in paint because it contained information. ID theorist Stephen Meyer says: “Our experience-based knowledge of information-flow confirms that systems with large amounts of specified complexity (especially codes and languages) invariably originate from an intelligent source—from a mind or personal agent.”
Thus, ID seeks to find in nature the types of information which are known to be produced by intelligent agents, and reliably indicate the prior action of intelligence. But what is the kind of information that is known to be produced by intelligence? The type of information which indicates design is generally called “specified complexity” or “complex and specified information” or “CSI” for short. Let’s briefly investigate what that term means.
Something is complex if it is unlikely. But complexity or unlikelihood alone are not enough to infer design. To see why, imagine that you are dealt a hand of poker. Whatever hand you get is going to be a very unlikely set of cards. Even if you get a good hand, like a straight or a royal flush, you’re not necessarily going to suddenly say “Aha, the deck was stacked.” Why? Because unlikely things happen all the time. We don’t infer design simply because of finding unlikelihood. We need something else to detect design: specification. Something is specified if it matches an independent pattern.
A Tale of Two Mountains
To appreciate CSI and how it helps us to detect design, imagine you are a tourist visiting mountains of North America. You first come across Mount Rainier, a huge volcano near Seattle (Figure 2, left). There are features of this mountain that differentiate it from any other mountain on Earth. In fact, if all possible combinations of rocks, peaks, ridges, gullies, cracks, and crags are considered, Mount Rainier’s exact shape is extremely unlikely and complex. But you’re not going to infer design simply because Mount Rainier has a complex shape. Why? Because you can easily explain its shape through the natural processes of erosion, uplift, heating, cooling, freezing, thawing, weathering, etc. Complexity (unlikelihood) alone is not enough to infer design, and there’s no special, independent pattern to the shape of Mount Rainier.
Figure 2. Which of these two mountains has a shape that allows us to detect design? Mount Rainier (left) has an unlikely (complex) shape, but it’s not specified, so we do not detect design. In contrast, Mount Rushmore (right) has a shape that is both complex and specified, so we detect design. Credits: Mount Rainier: Casey Luskin. Mount Rushmore: Dean Franklin, CC BY 2.0 (https://creativecommons.org/licenses/by/2.0), via Wikimedia Commons.
Now let’s say you go to a different mountain—Mount Rushmore in South Dakota. This mountain also has a very unlikely shape, you observe, but its shape is special. Its shape matches a pattern—the faces of four famous presidents. With Mount Rushmore, you don’t just observe complexity, you also find specification. It’s this specification—finding an independent pattern—plus complexity that allows you to infer that its shape was designed.
Detecting Design in Biology
Design theorists ask, “If we can detect design in other fields, is it possible to apply this kind of reasoning to biology?” They believe the answer is “Yes”! One of the greatest scientific discoveries of recent decades is that life is fundamentally built upon information. It’s all around us. As you read a book, your brain processes information stored in the shapes of ink on the page. When you talk to a friend, you communicate information using sound-based language, transmitted through vibrations in air molecules. Computers work because they can receive information, process it, and then give useful output.
Everyday life would be difficult without information. But could there even be life without it? Carl Sagan observed that the “information content of a simple cell” is “around 1012 bits, comparable to about a hundred million pages of the Encyclopedia Britannica.” Information forms the chemical blueprint for all living organisms, governing the assembly, structure, and function at essentially all levels of cells. But where does this information come from?
As noted previously, ID begins with the observation that intelligent agents generate large quantities of CSI. Studies of the cell reveal vast quantities of information in our DNA stored biochemically through the sequence of nucleotide bases. No physical or chemical law dictates the order of the nucleotide bases in our DNA, and the sequences are highly improbable and complex. Yet the unlikely information sequence of the coding regions of DNA match precise patterns necessary to produce functional proteins. Experiments done by pro-ID scientists have found that the sequence of nucleotide bases in our DNA must be extremely precise in order to generate a functional protein. One study found that the likelihood of a random sequence of 150 amino acids generating a functional, stable enzyme is less than one in 10 to the 70th power. In other words, our DNA contains high CSI.
Thus, molecular biologists now widely recognize that the coding regions of DNA possess a high “information content”—where “information content” in a biological context means complexity and specificity to perform biological functions. Even the staunch Darwinian biologist Richard Dawkins concedes that “[b]iology is the study of complicated things that give the appearance of having been designed for a purpose.” Dawkins believes that blind mechanistic processes did all the “designing” but intelligent design theorist Stephen C. Meyer notes, “in all cases where we know the causal origin of ‘high information content,’ experience has shown that intelligent design played a causal role.”
A DVD in Search of a DVD Player
By itself, a DNA molecule is useless. You need some kind of machinery to read the information in the DNA and produce some useful output. A lone DNA molecule is like having a DVD but no DVD player to read and process its information. A DVD might carry information, but without a machine to read that information, it’s useless. To read the information in a DVD, we need a DVD player. In the same way, our cells have a large amount of molecular machinery to help process the information in our DNA.
That machinery reads the commands and codes in our DNA much like a computer processes commands in computer code. Many authorities have recognized the computer-like information processing of the cell and the computer-like information-rich properties of DNA’s language-based code. Bill Gates observes, “Human DNA is like a computer program but far, far more advanced than any software we’ve ever created.” Craig Venter says that “life is a DNA software system,” containing “digital information” or “digital code,” and the cell is a “biological machine” full of “protein robots.” Richard Dawkins has written that “[t]he machine code of the genes is uncannily computer-like.” Francis Collins notes, “DNA is something like the hard drive on your computer,” containing “programming.”
Cells are thus constantly performing computer-like information processing. But what is the result of this process? Producing molecular machinery! The more we discover about the cell, the more we are learning that it functions like a miniature factory, replete with motors, powerhouses, garbage disposals, guarded gates, transportation corridors, and CPUs. As Bruce Alberts, former president of the U.S. National Academy of Sciences, stated:
“[T]he entire cell can be viewed as a factory that contains an elaborate network of interlocking assembly lines, each of which is composed of a set of large protein machines. … Why do we call the large protein assemblies that underlie cell function protein machines? Precisely because, like machines invented by humans to deal efficiently with the macroscopic world, these protein assemblies contain highly coordinated moving parts.”
There are hundreds, if not thousands, of molecular machines in living cells. But perhaps the most famous example of a molecular machine is the bacterial flagellum. The flagellum is a micro-molecular propeller assembly driven by a rotary engine that propels bacteria toward food or a hospitable living environment. There are various types of flagella, but all function like a rotary engine made by humans, as found in some car and boat motors. Flagella also contain many parts that are familiar to human engineers, including a rotor, a stator, a drive shaft, a u-joint, and a propeller. As one molecular biologist wrote, “[m]ore so than other motors the flagellum resembles a machine designed by a human.” But there’s something else that’s special about the flagellum.
Irreducible Complexity: A Challenge to Darwinian Explanations
In biology, ID theorists often discuss “irreducible complexity,” a concept developed and popularized by Lehigh University biochemistry professor Michael Behe. Irreducible complexity is a form of specified complexity, which exists in systems composed of “several interacting parts that contribute to the basic function, and where the removal of any one of the parts causes the system to effectively cease functioning.” Natural selection only preserves structures that confer a functional advantage to an organism, and such systems would be unlikely to evolve through a Darwinian process because there is no evolutionary pathway wherein they could remain functional during each small evolutionary step.
According to ID theorists, irreducible complexity is an informational pattern which reliably indicates design. As University of Idaho microbiologist Scott Minnich co-writes, “In all irreducibly complex systems in which the cause of the system is known by experience or observation, intelligent design or engineering played a role [in] the origin of the system.” Genetic knockout experimentsby Minnich show that the flagellum fails to assemble or function properly if any one of its approximately 35 protein-parts is removed. By definition, it is irreducibly complex. In this all-or-nothing game, mutations cannot produce the complexity needed to evolve a functional flagellum one step at a time, and the odds are too daunting for it to evolve in one great mutational leap.
The past 50 years of biological research have found that life is fundamentally based upon:
- A vast amount of complex and specified information encoded in a biochemical language.
- A computer-like system of commands and codes that processes the information.
- Irreducibly complex molecular machines and multi-machine systems.
Where, in our experience, do language, complex and specified information, programming code, and machines come from? They have only one known source: intelligence.
Intelligent Design and the Limits of Natural Selection
It’s important to appreciate that intelligent design does not reject all aspects of “evolution.” Evolution can mean something as benign as (1) “life has changed over time,” or it can entail more controversial ideas, like (2) “all living things share common ancestry,” or (3) “natural selection acting upon random mutations produced life’s diversity.”
ID does not conflict with the observation that natural selection causes small-scale changes over time (meaning 1), or the view that all organisms are related by common ancestry (meaning 2). However, the dominant evolutionary viewpoint today is neo-Darwinism (meaning 3), which contends that life’s entire history was driven by the blind mechanism of natural selection acting on random mutations (as well as other forces like genetic drift)—a purposeless process with no directions or goals. It is this specific neo-Darwinian claim that ID directly challenges.
Neo-Darwinian evolution can work fine when one small step (e.g., a single mutation in DNA) along an evolutionary pathway gives an advantage that helps an organism survive and reproduce. The theory of ID has no problem with this, and acknowledges that there are many small-scale changes that Darwinian mechanisms can produce.
But what about cases where many steps, or multiple mutations, are necessary to gain some advantage? Here, neo-Darwinian evolution faces limits on what it can accomplish. Evolutionary biologist Jerry Coyne affirms this when he states: “natural selection cannot build any feature in which intermediate steps do not confer a net benefit on the organism.” This follows from Darwin, who wrote in Origin of Species:
“If it could be demonstrated that any complex organ existed, which could not possibly have been formed by numerous, successive, slight modifications, my theory would absolutely break down.”
As Darwin’s quote suggests, natural selection gets stuck when a feature cannot be built through “numerous, successive, slight modifications”—that is, when a structure requires multiple mutations to be present before providing any advantage for natural selection to select. Because of such problems, over 1100 PhD scientists have signed a statement that they “are skeptical of claims for the ability of random mutation and natural selection to account for the complexity of life.” Proponents of intelligent design have done research showing that many such biological structures exist which challenge standard evolutionary explanations.
In 2004, biochemist Michael Behe co-published a study in Protein Science with physicist David Snoke looking at the “waiting time” to evolve features that require multiple mutations in order to provide an advantage to an organism. They found that if multiple mutations were required to produce a functional bond between two proteins, then “the mechanism of gene duplication and point mutation alone would be ineffective because few multicellular species reach the required population sizes.” Writing in the journal Genetics, Behe’s critics tried to refute him, but ended up confirming his basic arguments. The critics found that, in a human population, to obtain a feature via Darwinian evolution that required only two mutations before providing an advantage “would take > 100 million years,” which they admitted was “very unlikely to occur on a reasonable timescale.” Such “multi-mutation features” are thus unlikely to evolve in humans, which have small population sizes and long generation times, reducing the efficiency of the Darwinian mechanism.
But can Darwinian processes produce complex multimutation features in bacteria which have larger population sizes and reproduce rapidly? Even here, Darwinian evolution faces limits.
In a 2010 peer-reviewed study, molecular biologist Douglas Axe calculated that when a “multi-mutation feature” requires more than six mutations before giving any benefit, it is unlikely to arise even in the whole history of the Earth—even in the case of bacteria. He provided empirical backing for this conclusion from experimental research he published in the Journal of Molecular Biology. There, he found there that only one in 1074 amino-acid sequences yields a functional protein fold in the beta-lactamase enzyme. That indicates that protein folds in general are multimutation features, requiring many amino acids to be present before there is any functional advantage.
Another study by Axe and biologist Ann Gauger found that converting one enzyme to perform the function of a closely related enzyme—the kind of conversion that evolutionists claim should be able to evolve easily—would require a minimum of seven mutations. This exceeds the limits of what Darwinian evolution can produce over the Earth’s entire history, as calculated by Axe’s 2010 paper. A later study published in 2014 by Gauger, Axe and biologist Mariclair Reeves bolstered this finding. They examined additional proteins to determine whether they could be converted to via mutation perform the function of a closely related protein. After inducing all possible single mutations in the enzymes, and many other combinations of mutations, they found that evolving a protein, via Darwinian evolution, to perform the function of a closely related protein would take over 1015 years—over 100,000 times longer than the age of the earth!
ID research is making inroads into mainstream scientific research. A 2020 paper in Journal of Theoretical Biology citing ID research described “molecular fine-tuning” and explained “how it can be used in biology, and how it challenges conventional Darwinian thinking.” The paper cited “irreducible complexity” and “specified complexity” and concluded these findings show “fine-tuning is a useful and consistent approach to model some of the categories of design.” Over 100 peer-reviewed scientific papers supporting intelligent design have been published in the peer-reviewed scientific literature.
Collectively, results from the ID research program indicate that biochemical features would often require many mutations before providing any advantage to an organism, and would thus be beyond the limit of what Darwinian evolution can produce. If blind evolutionary mechanisms cannot build these CSI-rich features, what can? Some non-random process is necessary that can “look ahead” with forethought and a goal to find the complex combinations of mutations to generate these high-CSI features. That process is intelligent design.
Intelligent Design Extends Beyond Biology
But there’s much more to ID. Contrary to what many people suppose, ID is much broader than the debate over Darwinian evolution. That’s because much of the scientific evidence for intelligent design comes from areas that Darwin’s theory doesn’t even address. In fact, much evidence for intelligent design comes from physics and cosmology.
The fine-tuning of the laws of physics and chemistry to allow for advanced life is a profound example of extremely high levels of CSI in nature. To give a few examples, the strength of gravity (gravitational constant) must be fine-tuned to within 1 part in 1035; the expansion rate of the universe be fine-tuned to within 1 part in 1055; and the cosmological constant must be fine-tuned to within 1 part in 10120 Cosmologists have calculated the initial entropy of the universe must have been fine-tuned to within 1 part in 1010^123. That’s ten raised to a power of 10 with 123 zeros after it—a number far too long to write out!
The laws and constants of the universe are complex because they take on extremely precise and unlikely values. The laws of the universe are specified in that they match the narrow band of parameters required for the existence of advanced life. This high CSI indicates design. The Nobel Prize-winning physicist Charles Townes observed:
“Intelligent design, as one sees it from a scientific point of view, seems to be quite real. This is a very special universe: it’s remarkable that it came out just this way. If the laws of physics weren’t just the way they are, we couldn’t be here at all.”
Even the atheist cosmologist Fred Hoyle observed, “[a] common sense interpretation of the facts suggests that a super intellect has monkeyed with physics, as well as with chemistry and biology.” From the tiniest atom, to living organisms, to the architecture of the entire cosmos, the fabric of nature shows strong evidence of intelligent design.
A Positive Argument
This introduction has shown that ID’s arguments are positive, based upon what we have learned from studies about the origin of certain types of information, such as CSI-rich structures. In our experience, high CSI or irreducible complexity derives from a mind. If we did not have these observations, we could not infer intelligent design. We can then go out into nature and empirically test for high CSI or irreducible complexity, and when we find these types of information, we can justifiably infer that an intelligent agent was at work. Thus, ID is not based upon what we don’t know—an argument from ignorance or gaps in our knowledge—but rather, is based upon what we do know about the origin of information-rich structures, as testified by the observed information-generative powers of intelligent agents.
The opinions and views expressed in this article are those of the author and do not necessarily reflect the views and opinions of the employees and members of Ratio Christi South Africa.
 S. C. Meyer, “The origin of biological information and the higher taxonomic categories,” Proceedings of the Biological Society of Washington, 117(2):213-239 (2004).
 C. Sagan, “Life,” in Encyclopedia Britannica: Macropaedia Vol. 10 (Encyclopedia Britannica, Inc., 1984), 894.
 D. D. Axe, “Extreme Functional Sensitivity to Conservative Amino Acid Changes on Enzyme Exteriors,” Journal of Molecular Biology, 301:585-595 (2000); D. D. Axe, “Estimating the Prevalence of Protein Sequences Adopting Functional Enzyme Folds,” Journal of Molecular Biology, 1-21 (2004).
 Richard Dawkins, The Blind Watchmaker (New York: W. W. Norton, 1986), 1.
 S. C. Meyer et. al., “The Cambrian Explosion: Biology’s Big Bang,” in Darwinism, Design, and Public Education, J. A. Campbell and S. C. Meyer eds. (Michigan State University Press, 2003).
 B. Gates, N. Myhrvold, and P. Rinearson, The Road Ahead: Completely Revised and Up-To-Date (New York: Penguin Books, 1996), 228.
 J. Craig Venter, “The Big Idea: Craig Venter On the Future of Life,” The Daily Beast (October 25, 2013), accessed October 25, 2013, www.thedailybeast.com/articles/2013/10/25/the-big-idea-craig-venter-the-future-of-life.html.
 See C. Luskin, “Craig Venter in Seattle: ‘Life Is a DNA Software System’,” (October 24, 2013), www.evolutionnews.org/2013/10/craig_venter_in078301.html
 R. Dawkins, River Out of Eden: A Darwinian View of Life (New York: Basic Books, 1995), 17.
 F. Collins, The Language of God: A Scientist Presents Evidence for Belief (New York: Free Press, 2006), 91.
 B. Alberts, “The Cell as a Collection of Protein Machines: Preparing the Next Generation of Molecular Biologists,” Cell, 92: 291-294 (February 6, 1998).
 D. J. DeRosier, “The Turn of the Screw: The Bacterial Flagellar Motor,” Cell, 93: 17-20 (April 3, 1998). Note: DeRosier is not pro-ID.
 M. J. Behe, Darwin’s Black Box: The Biochemical Challenge to Darwinism (Free Press 1996), 39.
 S. A. Minnich and S. C. Meyer, “Genetic Analysis of Coordinate Flagellar and Type III Regulatory Circuits in Pathogenic Bacteria,” in Proceedings of the Second International Conference on Design & Nature, Rhodes Greece (M.W. Collins & C.A. Brebbia eds., 2004), 8, www.discovery.org/f/389
 Transcript of testimony of Scott Minnich, Kitzmiller et al. v. Dover Area School Board (M.D. Pa., PM Testimony, November 3, 2005), 103-112. See also Table 1 in R. M. Macnab, “Flagella,” in Escherichia Coli and Salmonella Typhimurium: Cellular and Molecular Biology Vol. 1, eds. F. C. Neidhardt, J. L. Ingraham, K. B. Low, B. Magasanik, M. Schaechter, and H. E. Umbarger (Washington D.C.: American Society for Microbiology, 1987), 73-74.
 Jerry Coyne, “The Great Mutator,” The New Republic (June 14, 2007).
 Charles Darwin, Origin of Species, first British edition (1859), 189, http://darwin-online.org.uk/Variorum/1859/1859-189-dns.html
 For the most current public version of the list, See “A Scientific Dissent from Darwinism,” https://dissentfromdarwin.org/.
 Michael Behe and David Snoke, “Simulating Evolution by Gene Duplication of Protein Features That Require Multiple Amino Acid Residues,” Protein Science, 13: 2651-2664 (2004).
 Rick Durrett and Deena Schmidt, “Waiting for Two Mutations: With Applications to Regulatory Sequence Evolution and the Limits of Darwinian Evolution,” Genetics, 180:1501-1509 (2008).
 Douglas Axe, “The Limits of Complex Adaptation: An Analysis Based on a Simple Model of Structured Bacterial Populations,” BIO-Complexity, 2010 (4): 1-10.
 Axe, “Estimating the Prevalence of Protein Sequences Adopting Functional Enzyme Folds”; Axe, “Extreme Functional Sensitivity to Conservative Amino Acid Changes on Enzyme Exteriors.”
 Ann Gauger and Douglas Axe, “The Evolutionary Accessibility of New Enzyme Functions: A Case Study from the Biotin Pathway,” BIO-Complexity, 2011 (1): 1-17.
 Mariclair A. Reeves, Ann K. Gauger, Douglas D. Axe, “Enzyme Families—Shared Evolutionary History or Shared Design? A Study of the GABA-Aminotransferase Family,” BIO-Complexity, 2014 (4): 1-16.
 Steinar Thorvaldsen and Ola Hössjer, “Using statistical methods to model the fine-tuning of molecular machines and systems,” Journal of Theoretical Biology, 501: 110352 (September 21, 2020).
 See “Peer-Reviewed Articles Supporting Intelligent Design,” at www.discovery.org/id/peer-review/
 Geraint Lewis and Luke Barnes, A Fortunate Universe: Life in a Finely Tuned Cosmos (Cambridge, UK: Cambridge University Press, 2016), 109.
 Alan Guth, “Inflationary Universe: a possible solution to the horizon and flatness problems,” Physical Review D 23 (1981), 347-356; Leslie, Universes, 3, 29.
 John Leslie, Universes (London, UK: Routledge, 1989), 5, 31.
 Roger Penrose and Martin Gardner, The Emperor’s New Mind: Concerning Computers, Minds, and the Laws of Physics (Oxford, UK: Oxford University Press, 2002), 444-445; Leslie, Universes, 28.
 Charles Townes as quoted in Bonnie Azab Powell, “‘Explore as much as we can’: Nobel Prize winner Charles Townes on evolution, intelligent design, and the meaning of life,” UC Berkeley NewsCenter (June 17, 2005), https://www.berkeley.edu/news/media/releases/2005/06/17_townes.shtml.
 Fred Hoyle, “The Universe: Past and Present Reflections,” Engineering and Science, pp. 8-12 (November, 1981).