Editor’s note: We are delighted to present a series by geologist Casey Luskin on “The Positive Case for Intelligent Design.” This is the third entry in the series, a modified excerpt from the new book The Comprehensive Guide to Science and Faith: Exploring the Ultimate Questions About Life and the Cosmos. Find the full series so far here.

We’ll now use the basic method [outlined here yesterday] to investigate the positive evidence for design in five fields: (1) biochemistry, (2) paleontology, (3) systematics (the relationships between organisms), (4) genetics, and (5) physics. Each example will begin with observations about how intelligent agents act based on previous studies by ID theorists. Then a testable hypothesis/prediction is made, followed by a discussion of what the data reveals (experiment), and finally, a conclusion.

The Positive Case for Design in Biochemistry

Observation (from previous studies): Intelligent agents think with an end goal in mind, allowing them to solve complex problems by taking many parts or symbols and arranging them in intricate patterns that perform a specific function — i.e., they generate high levels of complex and specified information:

• “Intelligence is a goal-directed process that is capable of thinking with will, forethought, and intentionality to achieve some end-goal.”¹
• “[W]e have repeated experience of rational and conscious agents — in particular ourselves — generating or causing increases in complex specified information, both in the form of sequence-specific lines of code and in the form of hierarchically arranged systems of parts…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.”²
• “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.”³

Hypothesis (prediction): Finely tuned high-CSI structures will be found in biology, including irreducibly complex systems that require multiple components to function. 

Experiment (data): Natural structures contain many parts arranged in intricate patterns that perform a specific function (e.g., they contain high CSI). These include language-based codes in our DNA, irreducibly complex molecular machines like the bacterial flagellum,⁴ and highly specified protein sequences. Mutational sensitivity tests have shown that the amino acid sequences of many functional proteins must be highly complex and specified in order to function.⁵

Conclusion: Irreducible complexity and high CSI systems are found, indicating these systems were designed.

Next, “The Positive Case for Design in Paleontology.”

Notes

1. Gary Kemper, Hallie Kemper, and Casey Luskin, Discovering Intelligent Design: A Journey into the Scientific Evidence (Seattle, WA: Discovery Institute Press, 2013).
2. Stephen C. Meyer, “The origin of biological information and the higher taxonomic categories,” Proceedings of the Biological Society of Washington 117 (2004), 213-239.
3. Scott A. Minnich and Stephen C. Meyer, “Genetic Analysis of Coordinate Flagellar and Type III Regulatory Circuits in Pathogenic Bacteria,” Proceedings of the Second International Conference on Design & Nature, Rhodes Greece, eds. M.W. Collins and C.A. Brebbia (Southampton, UK: WIT Press, 2004).
4. William A. Dembski, No Free Lunch: Why Specified Complexity Cannot Be Purchased Without Intelligence (Lanham, MD: Rowman & Littlefield, 2002), 239-310; Michael Behe, Darwin’s Black Box: The Biochemical Challenge to Evolution (New York: Free Press, 1996), 51-73; Minnich and Meyer, “Genetic analysis of coordinate flagellar and type III regulatory circuits in pathogenic bacteria”; A.C. McIntosh, “Information and Entropy—Top-Down or Bottom-Up Development in Living Systems?,” International Journal of Design & Nature and Ecodynamics 4 (2009), 351-385; A.C. McIntosh, “Evidence of Design in Bird Feathers and Avian Respiration,” International Journal of Design & Nature and Ecodynamics 4 (2009), 154-169.
5. Douglas D. Axe, “Extreme Functional Sensitivity to Conservative Amino Acid Changes on Enzyme Exteriors,” Journal of Molecular Biology 301 (2000), 585-595; Douglas D. Axe, “Estimating the Prevalence of Protein Sequences Adopting Functional Enzyme Folds,” Journal of Molecular Biology 341 (2004), 1295-1315; Ann K. Gauger et al., “Reductive Evolution Can Prevent Populations from Taking Simple Adaptive Paths to High Fitness,” BIO-Complexity 2010 (2); Kirk K. Durston et al., “Measuring the functional sequence complexity of proteins,” Theoretical Biology and Medical Modelling 4 (2007), 47; Ann K. Gauger and Douglas D. Axe, “The Evolutionary Accessibility of New Enzyme Functions: A Case Study from the Biotin Pathway,” BIO-Complexity 2011 (1); M.A. Reeves, A.K. Gauger, and D.D. Axe, “Enzyme Families-Shared Evolutionary History or Shared Design? A Study of the GABA-Aminotransferase Family,” BIO-Complexity 2014 (4).