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AN ALGORITHMIC INFORMATION THEORY CHALLENGE TO INTELLIGENT DESIGN
Author(s) -
Devine Sean
Publication year - 2014
Publication title -
zygon®
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.222
H-Index - 23
eISSN - 1467-9744
pISSN - 0591-2385
DOI - 10.1111/zygo.12059
Subject(s) - randomness , intelligent design , natural (archaeology) , process (computing) , computer science , second law of thermodynamics , management science , test (biology) , epistemology , mathematical economics , mathematics , economics , philosophy , statistics , physics , archaeology , quantum mechanics , history , operating system , paleontology , biology
William Dembski claims to have established a decision process to determine when highly unlikely events observed in the natural world are due to Intelligent Design. This article argues that, as no implementable randomness test is superior to a universal Martin‐Löf test, this test should be used to replace Dembski's decision process. Furthermore, Dembski's decision process is flawed, as natural explanations are eliminated before chance. Dembski also introduces a fourth law of thermodynamics, his “law of conservation of information,” to argue that information cannot increase by natural processes. However, this article, using algorithmic information theory, shows that this law is no more than the second law of thermodynamics. The article concludes that any discussions on the possibilities of design interventions in nature should be articulated in terms of the algorithmic information theory approach to randomness and its robust decision process.