| dc.description.abstract | This dissertation critiques and rejects Elliott Sober's dismissal of intelligent design as a scientific hypothesis. Sober builds the case for this dismissal in chapter 2 of his 2008 book Evidence and Evolution. Sober's case against intelligent design as science is a philosophical one, emerging from a Bayesian likelihood approach. Sober claims that unlike neo-Darwinian processes, intelligent design cannot supply independent evidence to support the claim that it is a measurably likely cause responsible for the emergence of biological organisms and the structures or processes of which they are composed. Without an assessable likelihood, Sober asserts that intelligent design (again, unlike neo-Darwinian mechanisms) is not testable, and since it is not testable, it does not qualify as a scientific hypothesis.
This dissertation argues however, that according to Sober's own standards in Evidence, because intelligent design and the neo-Darwinian hypothesis both address unrepeated, major biological changes in the unobservable past, and because they both depend upon crucial analogies in order to support either inductive arguments or likelihood assessments, the two hypotheses stand on equivalent evidential and logical
grounds. Either Sober must reject both neo-Darwinism and intelligent design, or he must allow them both as equivalent, rival hypotheses based upon a fair application of his argumentation requirements. In addition, after explaining important basics of analogy theory, and its crucial, even unavoidable role in the historical (or "origins") sciences, the dissertation goes on to show how intelligent design's empirical support, based upon analogy with humanly designed artifacts, machines and increasingly cell-like creations in the laboratory, is continuing to grow stronger by the year in both likelihood and in explanatory power. The dissertation thus concludes that intelligent design should be treated as a viable scientific explanation for the dramatic examples of specified complexity being discovered in biology, and indeed should be regarded as an increasingly vigorous rival to the neo-Darwinian explanation of such complexity. | en_US |
