The Design Inference: Eliminating Chance through Small Probabilities

Blurb

The Design Inference: Eliminating Chance through Small Probabilities is a book by American philosopher and mathematician William A. Dembski, a proponent of intelligent design, which sets out to establish approaches by which evidence of intelligent agency could be inferred in natural and social situations. In the book he distinguishes between 3 general modes of competing explanations in order of priority: regularity, chance, and design. The processes in which regularity, chance, and design are ruled out one by one until one remains as a reasonable and sufficient explanation for an event, are what he calls an "explanatory filter". It is a method that tries to eliminate competing explanations in a systematic fashion including when a highly improbable event conforms to a discernible pattern that is given independently of the event itself. This pattern is Dembski's concept of specified complexity. Throughout the book he uses diverse examples such as detectability of spontaneous generation and occurrence of natural phenomena and cases of deceit like ballot rigging, plagiarism, falsification of data, etc.