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Science & Education

, Volume 25, Issue 1–2, pp 95–114 | Cite as

On Mathematical Anti-Evolutionism

  • Jason RosenhouseEmail author
Article

Abstract

The teaching of evolution in American high schools has long been a source of controversy. The past decade has seen an important shift in the rhetoric of anti-evolutionists, toward arguments of a strongly mathematical character. These mathematical arguments, while different in their specifics, follow the same general program and rely on the same underlying model of evolution. We shall discuss the nature and history of this program and model and describe general reasons for skepticism with regard to any anti-evolutionary arguments based upon them. We shall then survey the major arguments used by anti-evolutionists, to show how our general considerations make it possible to quickly identify their weakest points.

Keywords

Malaria Cumulative Selection Probability Calculation Intelligent Design Darwinian Evolution 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Conflict of interest

The author declares that he has no conflict of interest.

References

  1. Adami, C., Ofria, C., & Collier, T. C. (2000). Evolution of biological complexity. Proceedings of the National Academy of Sciences, 97(9), 4463–4468.CrossRefGoogle Scholar
  2. Applebaum, D. (2008). Probability and information: An integrated approach. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
  3. Behe, M. (1996). Darwin’s black box: The biochemical challenge to evolution. New York: Free Press.Google Scholar
  4. Behe, M. (2007). The edge of evolution: The search for the limits of evolution. New York: Free Press.Google Scholar
  5. Behe, M., & Snoke, D. (2004). Simulating evolution by gene duplication of protein features that require multiple amino acid residues. Protein Science, 13(10), 2651–2664.CrossRefGoogle Scholar
  6. Carrier, R. C. (2004). The argument from biogenesis: Probabilities against a natural origin of life. Biology and Philosophy, 19(5), 739–764.CrossRefGoogle Scholar
  7. Carroll, S. (2007). God as genetic engineer. Science, 316(5830), 1427–1428.CrossRefGoogle Scholar
  8. Dembski, W. (1998a). The design inference: Eliminating chance through small probabilities. New York: Cambridge University Press.CrossRefGoogle Scholar
  9. Dembski, W. (1998b). Mere creation: Science, faith and intelligent design. Downer’s Grove: InterVarsity Press.Google Scholar
  10. Dembski, W. (1999). Intelligent design: The bridge between science and theology. Downer’s Grove: InterVarsity Press.Google Scholar
  11. Dembski, W. (2002). No free lunch: Why specified complexity cannot be purchased without intelligence. Lanham: Rowman and Littlefield.Google Scholar
  12. Dembski, W. (2004). The design revolution: Answering the toughest questions about intelligent design. Downer’s Growve: InterVarsity Press.Google Scholar
  13. Dembski, W. (2014). Being as communion: A metaphysics of information. Surrey: Ashgate.Google Scholar
  14. Dembski, W., & Marks, R, I. I. (2009). Conservation of information in search: Measuring the cost of success. IEEE Transactions on Systems, Man and Cybernetics A, Systems and Humans, 5(5), 1051–1061.CrossRefGoogle Scholar
  15. Dembski, W., & Marks II, R. (2009b). Bernoulli’s principle of insufficient reason and conservation of information in computer search. In Proceedings of the 2009 IEEE international conference on systems, man, and cybernetics. San Antonio, TX, USA (pp. 2647–2652).Google Scholar
  16. Dembski, W., & Marks, R, I. I. (2010). The search for a search: Measuring the information cost of higher level search. Journal of Advanced Computational Intelligence and Intelligent Informatics, 14(5), 475–486.Google Scholar
  17. Dembski, W., & Marks, R, I. I. (2011). Life’s conservation law: Why Darwinian evolution cannot create biological information. In B. Gordon & W. Dembski (Eds.), The nature of nature: Examining the role of naturalism in science (pp. 360–399). Wilmington: ISI Books.Google Scholar
  18. Denton, M. (1985). Evolution: A theory in crisis. London: Adler and Adler.Google Scholar
  19. Devine, S. (2014). An algorithmic information theory challenge to intelligent design. Zygon, 49(1), 42–65.CrossRefGoogle Scholar
  20. Durrett, R., & Schmidt, D. (2008). Waiting for two mutations: With applications to regulatory sequence evolution and the limits of Darwinian evolution. Genetics, 180(3), 1501–1509.CrossRefGoogle Scholar
  21. Eden, M. (1967). Inadequacies of neo-Darwinian evolution as a scientific theory. In P. Moorhead & M. Kaplan (Eds.), Mathematical challenges to the neo-Darwinian theory of evolution. Philadelphia: Wistar Institute Press.Google Scholar
  22. Elsberry, W., & Shallit, J. (2011). Information theory, evolutionary computation, and Dembski’s complex specified information. Synthese, 178(2), 237–270.CrossRefGoogle Scholar
  23. Farmer, M., & Habura, A. (2010). Using protistan examples to dispel the myths of intelligent design. Journal of Eukaryotic Microbiology, 57(1), 3–10.CrossRefGoogle Scholar
  24. Fitelson, B., Stephens, C., & Sober, E. (1999). How not to detect design—Critical notice: William A. Dembski, the design inference. Philosophy of Science, 66(3), 472–488.CrossRefGoogle Scholar
  25. Forrest, B., & Gross, P. (2004). Creationism’s Trojan horse: The wedge of intelligent design. New York: Oxford University Press.CrossRefGoogle Scholar
  26. Foster, D. (1999) Proving god exists. In The saturday evening post, November–December, 59–61, 78, 80–81, 84.Google Scholar
  27. Gishlick, A. (2004). Evolutionary paths to irreducible systems: The avian flight apparatus. In M. Young & T. Edis (Eds.), Why intelligent design fails: A scientific critique of the new creationism (pp. 58–71). Piscataway: Rutgers University Press.Google Scholar
  28. Godfrey-Smith, P. (2001). Information and the argument from design. In R. Pennock (Ed.), Intelligent design creationism and its critics: Philosophical, theological, and scientific perspectives (pp. 575–596). Cambridge: MIT Press.Google Scholar
  29. Gordon, B., & Dembski, W. (2011). The nature of nature: Examining the role of naturalism in science. Wilmington: ISI Books.Google Scholar
  30. Gould, S. J. (1993). An earful of jaw. In S. J. Gould (Ed.), Eight little piggies: Reflections in natural history (pp. 95–108). New York: Norton.Google Scholar
  31. Häggström, O. (2007). Intelligent design and the NFL theorems. Biology and Philosophy, 22(2), 217–230.CrossRefGoogle Scholar
  32. Johnson, P. (1991). Darwin on trial. Downer’s Grove: InterVarsity Press.Google Scholar
  33. Johnson, P. (1995). Reason in the balance: The case against natuarlism in science, law and education. Downer’s Grove: InterVarsity Press.Google Scholar
  34. Kimura, M. (1961). Natural selection as the process of accumulating genetic information in adaptive evolution. Genetic Research, 2(1), 127–140.CrossRefGoogle Scholar
  35. Kitcher, P. (2007). Living with Darwin: Evolution, design, and the future of faith. New York: Oxford University Press.Google Scholar
  36. Lloyd, B. (2012). Is there any conflict between evolution and the second law of thermodynamics? The Mathematical Intelligencer, 34(1), 29–33.CrossRefGoogle Scholar
  37. Loikkanen, J. (2015). William A. Dembski’s argument for detecting design through specified complexity. Philosophy and Theology, 27(2), 289–306.CrossRefGoogle Scholar
  38. Lynch, M. (2005). Simple evolutionary pathways to complex proteins. Protein Science, 14(9), 2217–2225.CrossRefGoogle Scholar
  39. Marks, R., Behe, M., Dembski, W., Gordon, B., & Sanford, J. (2013). Biological information: New perspectives. Toh Tuck Link: World Scientific.CrossRefGoogle Scholar
  40. Matzke, N. (2007). The edge of creationism. Trends in Ecology and Evolution, 23(11), 566–567.CrossRefGoogle Scholar
  41. McIntosh, A. (2009). Information and entropy—Top down or bottom-up development in living systems? Journal of Design and Nature and Ecodynamics, 4(4), 351–385.CrossRefGoogle Scholar
  42. McIntosh, A. (2013). Information and thermodynamics in living systems. In R. Marks, et al. (Eds.), Biological information: New perspectives. Toh Tuck Link: World Scientific.Google Scholar
  43. Meyer, S. (2013). Darwin’s doubt: The explosive origin of animal life and the case for intelligent design. New York: HarperOne.Google Scholar
  44. Miller, K. (1999). Finding Darwin’s god: A scientist’s search for common ground between god and evolution. New York: Harper Collins.Google Scholar
  45. Miller, K. (2007). Falling over the edge. Nature, 447(28 June), 1055–1056.CrossRefGoogle Scholar
  46. Morris, H., & Parker, G. (1987). What is creation science?. El Cajon: Master Books.Google Scholar
  47. Musgrave, I. (2004). Evolution of the bacterial flagellum. In M. Young & T. Edis (Eds.), Why intelligent design fails: A scientific critique of the new creationism (pp. 58–71). Piscataway: Rutgers University Press.Google Scholar
  48. Olofsson, P. (2008). Intelligent design and mathematical statistics. Biology and Philosophy, 23(4), 545–553.CrossRefGoogle Scholar
  49. Orr, H. A. (1996/1997). Darwin v. intelligent design (again). In Boston review of books, December/January, 28–31.Google Scholar
  50. Pennock, R. (1999). Tower of babel: The evidence against the new creationism. Cambridge: MIT Press.Google Scholar
  51. Pennock, R. (2001a). The wizards of ID: Reply to Dembski. In R. Pennock (Ed.), Intelligent design creationism and its critics: Philosophical, theological, and scientific perspectives (pp. 645–668). Cambridge: MIT Press.Google Scholar
  52. Pennock, R. (2001b). Intelligent design creationism and its critics: Philosophical, theological, and scientific perspectives. Cambridge: MIT Press.Google Scholar
  53. Pennock, R. (2002). Should creationism be taught in the public schools? Science and Education, 11(2), 111–133.CrossRefGoogle Scholar
  54. Pennock, R. (2007). Models, simulations, instantiations and evidence: The case of digital evolution. Journal of Experimental and Theoretical Artificial Intelligence, 19(1), 29–42.CrossRefGoogle Scholar
  55. Pennock, R. (2010). The postmodern sin of intelligent design creationism. Science and Education, 19(6–8), 757–778.CrossRefGoogle Scholar
  56. Perakh, M. (2004). There is a free lunch after all: William Dembski’s wrong answers to irrelevant questions. In M. Young & T. Edis (Eds.), Why intelligent design fails: A scientific critique of the new creationism. Piscataway: Rutgers University Press.Google Scholar
  57. Plutynski, A. (2010). Should intelligent design be taught in Public school science classrooms? Science and Education, 19(6–8), 779–795.CrossRefGoogle Scholar
  58. Rosenhouse, J. (2001). How anti-evolutionists abuse mathematics. The Mathematical Intelligencer, 23(4), 3–8.CrossRefGoogle Scholar
  59. Rosenhouse, J. (2002a). Probability, optimization theory, and evolution. Evolution, 56(8), 1721–1722.Google Scholar
  60. Rosenhouse, J. (2002b). Rhetorical legerdemain in intelligent design literature. In A. Chesworth (Ed.), Darwin day collection one. Albuquerque: Tangled Bank Press.Google Scholar
  61. Rosenhouse, J. (2006). Does evolution have a thermodynamics problem? Center for inquiry. http://www.csicop.org/specialarticles/show/does\_evolution\_have\_a\_thermodynamics\_problem/. Accessed 23 December 2015.
  62. Rosenhouse, J. (2011). Among the creationists: Dispatches from the anti-evolutionist front line. New York: Oxford University Press.Google Scholar
  63. Roth, A. (1998). Origins: Linking science and scripture. Hagerstown: Review and Herald Publishing Association.Google Scholar
  64. Sarkar, S. (2007). Doubting Darwin: Creationist designs on evolution. Malden: Blackwell.Google Scholar
  65. Schützenberger, M. P. (1967). Algorithms and the neo-Darwinian theory of evolution. In P. Moorhead & M. Kaplan (Eds.), Mathematical challenges to the neo-Darwinian theory of evolution. Philadelphia: Wistar Institute Press.Google Scholar
  66. Sewell, G. (2013a). Entropy and evolution. BIO-Complexity, 2013(2), 1–5.CrossRefGoogle Scholar
  67. Sewell, G. (2013b). Entropy, evolution and open systems. In R. Marks, et al. (Eds.), Biological information: New perspectives. Toh Tuck Link: World Scientific.Google Scholar
  68. Shallit, J., & Elsberry, W. (2004). Playing games with probability: Dembski’s complex specified information. In M. Young & T. Edis (Eds.), Why intelligent design fails: A scientific critique of the new creationism (pp. 121–138). Piscataway: Rutgers University Press.Google Scholar
  69. Sober, E. (2002). Intelligent design and probability reasoning. International Journal for the Philosophy of Religion, 52(2), 65–80.CrossRefGoogle Scholar
  70. Sober, E. (2008). Evidence and evolution: The logic behind the science. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
  71. Sober, E. (2014). Evolutionary biology, causal completeness, and theism. In D. Walsh & P. Thompson (Eds.), Evolutionary biology—Conceptual, ethical, and religious issues (pp. 31–44). Cambridge: Cambridge University Press.CrossRefGoogle Scholar
  72. Thornhill, R., & Ussery, D. (2000). A classification of possible routes in Darwinian evolution. Journal of Theoretical Biology, 203(2), 111–116.CrossRefGoogle Scholar
  73. Ulam, S. (1967). How to formulate mathematically problems of rate of evolution. In P. Moorhead & M. Kaplan (Eds.), Mathematical challenges to the neo-Darwinian theory of evolution. Philadelphia: Wistar Institute Press.Google Scholar
  74. Wein, R. (2002). Not a free lunch but a box of chocolates: A critique of William Dembski’s book No free lunch. The TalkOrigins Archive. http://www.talkorigins.org/design/faqs/nfl/\#irred. Accessed 23 December 2015.
  75. Wells, J. (2002). Icons of evolution: Science or myth? Why much of what we teach about evolution is wrong. Washington, DC: Regnery Publishing Inc.Google Scholar
  76. Wilkins, J. (2012). Can God create through Darwinian accidents? Zygon, 47(1), 30–42.CrossRefGoogle Scholar
  77. Wilkins, J., & Elsberry, W. (2001). The advantage of theft over toil: The design inference and arguing from ignorance. Biology and Philosophy, 16(5), 67–82.CrossRefGoogle Scholar
  78. Williams, W. (1925). The evolution of man scientifically disproved, in fifty arguments, privately published. http://ldolphin.org/wmwilliams.html. Accessed 23 December 2015.
  79. Wolpert, D. H., & Macready, W. G. (1997). No free lunch theorems for optimization. IEEE Transactions on Evolutionary Computation, 1(1), 67–82.CrossRefGoogle Scholar
  80. Young, M., & Edis, T. (2004). Why intelligent design fails: A scientific critique of the new creationism. Piscataway: Rutgers University Press.Google Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2016

Authors and Affiliations

  1. 1.Department of Mathematics and StatisticsJames Madison UniversityHarrisonburgUSA

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