Information theory, evolutionary computation, and Dembski’s “complex specified information”
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Intelligent design advocate William Dembski has introduced a measure of information called “complex specified information”, or CSI. He claims that CSI is a reliable marker of design by intelligent agents. He puts forth a “Law of Conservation of Information” which states that chance and natural laws are incapable of generating CSI. In particular, CSI cannot be generated by evolutionary computation. Dembski asserts that CSI is present in intelligent causes and in the flagellum of Escherichia coli, and concludes that neither have natural explanations. In this paper, we examine Dembski’s claims, point out significant errors in his reasoning, and conclude that there is no reason to accept his assertions.
KeywordsInformation theory Evolutionary computation Artificial life Pseudomathematics Complex specified information
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- Apostolico, A., & Lonardi, S. (2000). Compression of biological sequences by greedy off-line textual substitution. In Proceedings of the IEEE data compression conference (DCC), pp. 143–152.Google Scholar
- Berlekamp E.R., Conway J.H., Guy R.K. (1982) Winning ways, for your mathematical plays. Academic Press, LondonGoogle Scholar
- Boyer P. (2001) Religion explained. Basic Books, New YorkGoogle Scholar
- Chaitin G. (1974) Information-theoretic limitations of formal systems. Journal of the Association for Computing Machinery 21: 403–424Google Scholar
- Channon, A. (2001). Passing the ALife test: Activity statistics classify evolution in Geb as unbounded. In J. Kelemen & P. Sosík (Eds.), Proceedings of the 6th European conference on advances in artificial life (ECAL 2001), Vol. 2159 of Lecture notes in artificial intelligence (pp. 417–426). Berlin: Springer.Google Scholar
- Chen, X., Kwong, S., & Li, M. (1999). A compression algorithm for DNA sequences and its applications in genome comparison. In Proceedings of the 10th workshop on genome informatics, pp. 52–61.Google Scholar
- Dembski W.A. (1999) Intelligent design: The bridge between science & theology. InterVarsity Press, IllinoisGoogle Scholar
- Dembski W.A. (2002) No free lunch: Why specified complexity cannot be purchased without intelligence. Rowman & Littlefield, Ianham, MDGoogle Scholar
- Dembski W.A. (2004) The design revolution: Answering the toughest questions about intelligent design. InterVarsity Press, IllinoisGoogle Scholar
- Edis T. (2001) Darwin in mind: ‘Intelligent design’ meets artificial intelligence. Skeptical Inquirer 25(2): 35–39Google Scholar
- Elsberry W., Shallit J. (2003) Eight challenges for intelligent design advocates. Reports of the NCSE 23(5–6): 23–25Google Scholar
- Elsberry W., Shallit J. (2004) Playing games with probability: Dembski’s complex specified information. In: Young M., Edis T. (eds) Why intelligent design fails. Rutgers University Press, Piscataway, NJ, pp 121–138Google Scholar
- Göbel, F. (1979). On the number of Hamiltonian cycles in product graphs. Technical report # 289. Technische Hogeschool Twente, Netherlands.Google Scholar
- Godfrey-Smith P. (2001) Information and the argument from design. In: Pennock R.T. (eds) Intelligent design creationism and its critics. The MIT Press, Cambridge, MA, pp 577–596Google Scholar
- Goles E., Schulz O., Markus M. (2001) Prime number selection of cycles in a predator-prey model. Complexity 6(4): 33–38. http://www3.interscience.wiley.com/cgi-bin/fulltext?ID=84502365&PLACEBO=IE.pdf.CrossRefGoogle Scholar
- Heeren F. (2000) The deed is done. American Spectator 33(10): 28–29Google Scholar
- Heltzer R.A., Vyse S.A. (1994) Intermittent consequences and problem solving: The experimental control of “superstitious” beliefs. Psychological Record 44: 155–169Google Scholar
- Hirvensalo M. (2001) Quantum computing. Springer, BerlinGoogle Scholar
- Kahneman D., Slovic P., Tversky A. (1982) Judgment under uncertainty: Heuristics and biases. Cambridge University Press, CambridgeGoogle Scholar
- Keynes J.M. (1957) A treatise on probability. Macmillan, LondonGoogle Scholar
- Koons R.C. (2001) Remarks while introducing Dembski’s talk at the conference Design, self-organization and the integrity of creation. Calvin College, Grand Rapids, MichiganGoogle Scholar
- Koza J.R. (1994) Artificial life: Spontaneous emergence of self-replicating and evolutionary self-improving computer programs. In: Langton C.G. (eds) Artificial life III.. Addison-Wesley, Redwood City, CA, pp 225–262Google Scholar
- Lanctot, J. K., Li, M., & Yang, E. (2000). Estimating DNA sequence entropy. In Proceedings of the 11th ACM-SIAM symposium on discrete algorithms (SODA), pp. 409–418.Google Scholar
- Laplace P.S. (1952) A philosophical essay on probabilities. Dover, New YorkGoogle Scholar
- Li M. (2002) Compressing DNA sequences. In: Jiang T., Xu Y., Zhang M.Q. (eds) Current topics in computational molecular biology. The MIT Press, Cambridge, MA, pp 157–171Google Scholar
- Medawar P.B. (1984) The limits of science. Harper & Row, New YorkGoogle Scholar
- Meyer S.C. (2000) DNA and other designs. First Things 102: 30–38Google Scholar
- Perakh M. (2004) Unintelligent design. Prometheus, New YorkGoogle Scholar
- Pigliucci M. (2000) Chance, necessity, and the new holy war against science. A review of W. A. Dembski’s the design inference. BioScience 50: 79–81Google Scholar
- Pigliucci M. (2001) Design yes, intelligent no: A critique of intelligent design theory and neocreationism. Skeptical Inquirer 25(5): 34–39Google Scholar
- Ray, T. (2001). Evolution of complexity: Tissue differentiation in network Tierra. http://www.isd.atr.co.jp/ray/pubs/atrjournal/index.html.
- Rizzotti M. (2000) Early evolution: From the appearance of the first cell to the first modern organisms. Birkhäuser, BostonGoogle Scholar
- Roche D. (2001) A bit confused: Creationism and information theory. Skeptical Inquirer 25(2): 40–42Google Scholar
- Rothemund, P. W. K., & Winfree, E. (2000). The program-size complexity of self-assembled squares. In Proceedings of the thirty-second annual ACM symposium on theory of computing, pp. 459–468. ACM.Google Scholar
- Rudski J.M., Lischner M.I., Albert L.M. (1999) Superstitious rule generation is affected by probability and type of outcome. Psychological Record 49: 245–260Google Scholar
- Sainsbury R.M. (1995) Paradoxes (2nd ed). Cambridge University Press, CambridgeGoogle Scholar
- Schneider, T. D. (2001). Rebuttal to William A. Dembski’s posting. http://www.lecb.ncifcrf.gov/toms/paper/ev/dembski/rebuttal.html.
- Shallit, J. (2004). Dembski’s mathematical achievements. Retrieved May 12 2004, from http://www.pandasthumb.org/pt-archives/000207.html.
- Shannon C. (1950) Prediction and entropy of printed English. Bell System Technical Journal 3: 50–64Google Scholar
- Sims K. (1994) Evolving 3D morphology and behavior by competition. In: Brooks R.A., Maes P. (eds) Artificial life IV: Proceedings of the fourth international workshop on the synthesis and simulation of living systems. MIT Press, Cambridge, MA, pp 28–39Google Scholar
- Wein, R. (2000). What’s wrong with the design inference. http://www.metanexus.net/metanexus_online/show_article2.asp?id=2654.
- Yelen D.R. (1971) The acquisition and extinction of superstitious behavior. Journal of Experimental Research in Personality 5: 1–6Google Scholar
- Young M., Edis T. (eds) (2004) Why intelligent design fails. Rutgers University Press, Piscataway, NJGoogle Scholar