The fundamental lesson here is that the Dembski-Marks approach to evaluating model assumptions is both arbitrary and a poor reflection of scientific reasoning. Model assumptions are not accepted or rejected based on a numerical measure of how many logical possibilities that are ruled out or how far probability distributions deviate from uniform measures. Rather, model assumptions are accepted or rejected based on predictive and descriptive accuracy, domain of applicability, ability to unify existing models and empirical knowledge, and so on. Merely talking about target sets requires assumptions that impose structure on the search space and processes related to it. Dembski and Marks (2009a) mention “a simple self-replicating molecule, an autocatalytic set, or a lipid membrane” as examples of biological targets. However, these chemical concepts presuppose model assumptions from physics, chemistry and biochemistry and they could hardly be independent of the chemical processes by which they are thought to arise.As others have stated, Dembski and Marks do not understand how biological systems operate and how selection operates. This hampers their ability to correctly model a biosphere.
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