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William Dembski created quite a stir in the world of information theory with his book The Design Inference. For the first time, he outlined a rigorous method for identifying design, which he called the explanatory filter. Since then many critics have claimed that Dembski’s proposed filter is without merit due to the lack of application in the couple of decades since its invention. But, are the critics right, or are they wrong—wrong in the way that a fish doesn’t recognize water because water is the very atmosphere of the fish’s existence? Let us first remind ourselves of Dembski’s explanatory filter. His filter proceeds in three main steps. Eliminate events of large probability (necessity) Eliminate events of medium probability (chance) Specify Read More ›