Helping Students Answer a Professor’s Challenge to “Find a Fact” That Supports Intelligent Design (Part 2)
As I mentioned in Part 1 of this series, some students from a university biology class have e-mailed us trying to answer a challenge from their professor to “Find a fact (observation, data) that supports” intelligent design or evolution. These students wanted to find facts supporting intelligent design, and as I mentioned in my previous post, I told them that ID meets their professor’s definition of a theory: something that is “supported by a large amount of data (observations in the physical world)” and has a “broad application to explain a wide range of phenomena” and “a framework that allows the development of novel hypotheses (questions about nature).” In this second installment I’ll provide the rest of my response to these students, discussing in more detail exactly how intelligent design meets their professor’s definition of a scientific theory:
So let’s now return to how intelligent design is a “theory” (under your professor’s definition). There are innumerable data and observations of the physical world that support intelligent design from a wide variety of fields. For me, the most compelling fact (in biology) is the presence of highly complex and specified information in the genome (see Axe, 2000 and Axe, 2004), and specified and complex information is a reliable indicator of design (Dembski, 1998). In fact, I think that another student from your class emailed me asking the same question, and here’s the answer I gave (expanded here).
If you’d like a more comprehensive discussion of this evidence and how ID provides a framework for developing novel hypotheses, you might enjoy my article, “The Positive Case for Design.” To summarize that paper, ID theorists start by observing how intelligent agents act when they design things. Some of their observations show that:
- (1) Intelligent agents think with an “end goal” in mind, allowing them to solve complex problems by taking many parts and arranging them in intricate patterns that perform a specific function (e.g. complex and specified information).
- (2) Intelligent agents can rapidly infuse large amounts of information into systems.
- (3) Intelligent agents ‘re-use’ functional components that work over and over in different systems (e.g., wheels for cars and airplanes).
- (4) Intelligent agents typically create functional things.
Keeping our numbering straight, we can use those observations to generate hypotheses based upon testable predictions in a variety of different fields:
- (1) Natural structures will be found that contain many parts arranged in intricate patterns that perform a specific function (e.g. complex and specified information).
- (2) Forms containing large amounts of novel information will appear in the fossil record suddenly and without similar precursors.
- (3) Convergence will occur routinely. That is, genes and other functional parts will be re-used in different and unrelated organisms.
- (4) Much so-called “junk DNA” will turn out to perform valuable functions.
Thus, intelligent design can predict and explain a broad range of observations in many scientific fields. Below is a discussion of some of the fields where ID provides a framework for predicting, understanding, and explaining data from a wide variety of scientific fields:
- Biochemistry, where ID explains and predicts the presence of high levels of complex and specified information in proteins and DNA (Axe, 2000; Axe, 2004; Behe & Snoke, 2004);
- Genetics, where ID predicts and explains function for so-called “junk” DNA while neo-Darwinism stifles such research (Sternberg, 2002; Wells, 2004; Makalowski, 2003; Gibbs, 2003);
- Systematics, where ID explains why there are similarities between living species, including examples of extreme genetic “convergence” that severely conflict with conventional evolutionary phylogenies (Lönnig, 2004; Nelson & Wells, 2003; Lawton, 2009);
- Cell biology, where ID explains why the cell resembles “designed structures rather than accidental by-products of neo-Darwinian evolution,” allowing scientists to better understand the workings of molecular machines (Wells, 2005; Minnich & Meyer, 2004; Behe, 1996; Lönnig, 2004);
- Systems biology, where ID encourages biologists to look at various biological systems as integrated components of larger systems that are designed to work together in a top-down, coordinated fashion, which is what biologists are finding is the case (Lönnig, 2004; Bract 2002; Kitano, 2003);
- Animal biology, where ID predicts function for allegedly “vestigial” organs, structures, or systems whereas evolution has made many faulty predictions here (Wells, 2002; Dembski & Wells, 2008);
(Note: your professor says that the appendix “do[es] not seem to have any purpose” and is “useless,” but he’s mistaken. There is in fact extensive evidence of immuno-function for the appendix. See Martin, Loren G., “What is the function of the human appendix?” Scientific American (October 21, 1999), and Bollinger, R. Randal et al., “Biofilms in the Large Bowel Suggest an Apparent Function of the Human Vermiform Appendix,” 249 JOURNAL OF THEORETICAL BIOLOGY: 826-31 (2007); Duke University Medical Center, “Appendix Isn’t Useless At All: It’s A Safe House For Good Bacteria,” SCIENCEDAILY (October 8, 2007). Your professor says you “can’t use the appendix,” but you don’t want to use the appendix as evidence for evolution because it has been demonstrated to NOT be “useless” and your professor is uncritically promoting Darwinian urban legends, providing you with an object lesson for how Darwinian assumptions and predictions stifle scientific progress.)
- Bioinformatics, where ID explains the presence of new layers of information and functional language embedded in the genetic codes, as well as other codes within biology (Wells, 2004; Meyer, 2004b; Voie, 2006; Abel & Trevors, 2006);
- Information theory, where ID encourages scientists to understand where intelligent causes are superior to natural causes in producing certain types of information (Dembski, 1998; Dembski & Marks, 2009a; Dembski & Marks, 2009b; Voie, 2006; Trevors & Abel, 2004; Abel & Trevors, 2006);
- Paleontology, where ID’s prediction of irreducibly complexity in biological systems explains paleontological patterns such as the abrupt appearance of biological life forms, punctuated change, and stasis throughout the history of life (Meyer, Ross, Nelson & Chien, 2003; Meyer, 2004a; Meyer, 2004b; Luskin, 2005; Luskin, 2008);
- Physics and Cosmology, where ID encourages scientists to investigate and discover more instances of fine-tuning of the laws of physics and properties of our universe that uniquely allow for the existence of advanced forms of life (Gonzalez & Richards, 2004; Brumfiel, 2006).
Your professor stated that the “fact can be any observation in biology that is substantiated by publication in a scientific journal,” and in this regard I’ve listed many of the references cited for you below. In my opinion, ID explains quite a broad range of data and provides us with a powerful framework for predicting and understanding data from a variety of different fields. Thanks for your time and I hope this helps.
Douglas D. Axe, “Extreme Functional Sensitivity to Conservative Amino Acid Changes on Enzyme Exteriors,” Journal of Molecular Biology, Vol. 301:585-595 (2000)
Douglas D. Axe, “Estimating the Prevalence of Protein Sequences Adopting Functional Enzyme Folds,” Journal of Molecular Biology, 1-21 (2004)
Michael Behe, Darwin’s Black Box: The Biochemical Challenge to Evolution (Free Press, 1996)
Michael J. Behe & David W. Snoke, “Simulating Evolution by Gene Duplication of Protein Features That Require Multiple Amino Acid Residues,” Protein Science, Vol 13:2651-2664 (2004)
Geoff Brumfiel, “Outrageous Fortune,” Nature, Vol. 439: 10-12 (Jan. 5, 2006)
Bract, “Inventions, Algorithms, and Biological Design,” in Progress in Complexity, Information, and Design (Vol. 1.1, 2002)
William A. Dembski, The Design Inference: Eliminating Chance Through Small Probabilities (Cambridge University Press, 1998)
a. William A. Dembski and Robert J. Marks II, “Conservation of Information in Search: Measuring the Cost of Success” (In publication, 2009)
b. William A. Dembski and Robert J. Marks II, “The Search for a Search: Measuring the Information Cost of Higher Level Search” (In publication, 2009)
William Dembski and Jonathan Wells, The Design of Life: Discovering Signs of Intelligence in Living Systems, (FTE, 2008) (see www.thedesignoflife.net)
Wayt T. Gibbs, “The Unseen Genome: Gems among the Junk,” Scientific American (November, 2003)
Guillermo Gonzalez and Jay Wesley Richards, The Privileged Planet: How our Place in the Cosmos is Designed for Discovery, (Regnery, 2004)
Graham Lawton, “Why Darwin was wrong about the tree of life,” New Scientist (January 21, 2009)
Hiroaki Kitano, “Systems Biology: A Brief Overview,” Science, Vol. 295: 1662-1664 (March 1, 2002)
Wolf-Ekkehard Lönnig, “Dynamic genomes, morphological stasis, and the origin of irreducible complexity,” in Dynamical Genetics pp. 101-119 (Valerio Parisi, Valeria De Fonzo, and Filippo Aluffi-Pentini eds., 2004)
Casey Luskin, “Human Origins and Intelligent Design,” Progress in Complexity and Design, (Vol 4.1, November, 2005)
Casey Luskin, “Intelligent Design Has Scientific Merit in Paleontology,” part of the “Does Intelligent Design Have Merit?” debate at OpposingViews.com (September, 2008)
Wojciech Makalowski, “Not Junk After All,” Science, Vol. 300(5623):1246-1247 (May 23, 2003)
Stephen C. Meyer, Marcus Ross, Paul Nelson & Paul Chien, “The Cambrian Explosion: Biology’s Big Bang,” in Darwinism, Design, and Public Education (John A. Campbell and Stephen C. Meyer eds., Michigan State University Press, 2003)
a. Stephen C. Meyer, “The Cambrian Information Explosion,” in Debating Design (edited by Michael Ruse and William Dembski; Cambridge University Press 2004)
b. Stephen C. Meyer, “The origin of biological information and the higher taxonomic categories,” Proceedings of the Biological Society of Washington, Vol. 117(2):213-239 (2004)
Scott A. Minnich & Stephen 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)
Paul Nelson and Jonathan Wells, “Homology in Biology,” in Darwinism, Design, and Public Education, (Michigan State University Press, 2003)
Richard v. Sternberg, “On the Roles of Repetitive DNA Elements in the Context of a Unified Genomic– Epigenetic System,” Annals of the New York Academy of Sciences, Vol. 981: 154–188 (2002)
J.T. Trevors and D.L. Abel, “Chance and necessity do not explain the origin of life,” Cell Biology International, Vol. 28: 729-739 (2004)
D. L. Abel & J. T. Trevors, “Self-organization vs. self-ordering events in life-origin models,” Physics of Life Reviews, Vol. 3: 211–228 (2006)
Øyvind Albert Voie, “Biological function and the genetic code are interdependent,” Chaos, Solitons and Fractals, Vol. 28:1000–1004 (2006)
Jonathan Wells, “Using Intelligent Design Theory to Guide Scientific Research” Progress in Complexity, Information, and Design (Vol. 3.1.2, November 2004)
Jonathan Wells, “Do Centrioles Generate a Polar Ejection Force?,” Rivista di Biologia / Biology Forum, Vol. 98:71-96 (2005)