This essay discusses Elliott Sober’s Evidence and Evolution: The Logic Behind the Science. Valuable to both philosophers and biologists, Sober analyzes the testing of different kinds of evolutionary hypotheses about natural selection or phylogenetic history, including a thorough critique of intelligent design. Not at least because of a discussion of different schools of hypothesis testing (Bayesianism, likelihoodism, and frequentism), with Sober favoring a pluralism where different inference methods are appropriate in different empirical contexts, the book has lessons for philosophy of (...) science beyond its evolutionary focus. I criticize Sober for not including epistemic values and social aspects of scientific practice in his epistemological framework. (shrink)

This chapter offers a critique of intelligent design arguments against evolution and a philosophical discussion of the nature of science, drawing several lessons for the teaching of evolution and for science education in general. I discuss why Behe’s irreducible complexity argument fails, and why his portrayal of organismal systems as machines is detrimental to biology education and any under-standing of how organismal evolution is possible. The idea that the evolution of complex organismal features is too unlikely to have occurred by (...) random mutation and selection (as recently promoted by Dembski) is very widespread, but it is easy to show students why such small probability arguments are fallacious. While intelligent design proponents have claimed that the exclusion of supernatural causes mandated by scientific methods is dogmatically presupposed by science, scientists have an empirical justification for using such methods. This justification is instructive for my discussion of how to demarcate science from pseudoscience. I argue that there is no universal account of the nature of science, but that the criteria used to judge an intellectual approach vary across historical periods and have to be specific to the scientific domain. Moreover, intellectual approaches have to be construed as practices based on institutional factors and values, and to be evaluated in terms of the activities of their practitioners. Science educators should not just teach scientific facts, but present science as a practice and make students reflect on the nature of science, as this gives them a better appreciation of the ways in which intelligent design falls short of actual science. (shrink)

The argument that the second law of thermodynamics contradicts the theory of evolution has recently been revived by anti-evolutionists. In its basic form, the argument asserts that whereas evolution implies that there has been an increase in biological complexity over time, the second law, a fundamental principle of physics, shows this to be impossible. Scientists have responded primarily by noting that the second law does not rule out increases in complexity in open systems, and since the Earth receives energy from (...) the Sun, it is an open system. This reply is correct as far as it goes, and it adequately rebuts the most crude versions of the second law argument. However, it is insufficient against more sophisticated versions, and it leaves many relevant aspects of thermodynamics unexplained. We shall consider the history of the argument, explain the nuances various anti-evolution writers have brought to it, and offer thorough explanations for why the argument is fallacious. We shall emphasize in particular that the second law is best viewed as a mathematical statement. Since anti-evolutionists never make use of the mathematical structure of thermodynamics, invocations of the second law never contribute anything substantive to their discourse. (shrink)

The teaching of evolution in American high schools has long been a source of controversy. The past decade has seen an important shift in the rhetoric of anti-evolutionists, toward arguments of a strongly mathematical character. These mathematical arguments, while different in their specifics, follow the same general program and rely on the same underlying model of evolution. We shall discuss the nature and history of this program and model and describe general reasons for skepticism with regard to any anti-evolutionary arguments (...) based upon them. We shall then survey the major arguments used by anti-evolutionists, to show how our general considerations make it possible to quickly identify their weakest points. (shrink)

The explanatory filter is a proposed method to detect design in nature with the aim of refuting Darwinian evolution. The explanatory filter borrows its logical structure from the theory of statistical hypothesis testing but we argue that, when viewed within this context, the filter runs into serious trouble in any interesting biological application. Although the explanatory filter has been extensively criticized from many angles, we present the first rigorous criticism based on the theory of mathematical statistics.

Due to the logical relations between theism and intelligent design (id), there are two challenges to theism that also apply to id. In the falsifiability challenge, it is charged that theism is compatible with every observation statement and thus asserts nothing. I argue that the contentious assumptions of this challenge can be avoided without loss of precision by charging theism (and thus id) directly with the lack of observational assertions. In the translatability challenge, it is charged that theism can be (...) translated into a (non-theistic) set of observation statements without loss of cognitive content. I argue that the contentious assumptions of this challenge are avoided by the related charge that the (non-theistic) evolutionary theory makes all the observational assertions of id, while the converse does not hold. Elliott Sober has argued that id meets the falsifiability challenge, but, since it makes almost no observational assertions, is not testable. I point out two problems with Sober’s argument and show that id is both deductively and probabilistically testable. Sober’s argument, I suggest, inconsistently combines the modified falsifiability challenge with the modified translatability challenge. If his claims about id’s observational assertions are true, however, id succumbs to the modified translatability challenge. (shrink)

If intelligent design (id) is to compete with evolutionary theory (et), it must meet the modified falsifiability challenge, that is, make some deductive or probabilistic observational assertions. It must also meet the modified translatability challenge, which it fails if et makes all the observational assertions of id, while id does not make all the observational assertions of et. I discuss four prominent but diverse formulations of id and show that each either fails one of the two challenges or is analytically (...) false. (shrink)

John organized a state lottery and his wife won the main prize. You may feel that the event of her winning wasn’t particularly random, but how would you argue that in a fair court of law? Traditional probability theory does not even have the notion of random events. Algorithmic information theory does, but it is not applicable to real-world scenarios like the lottery one. We attempt to rectify that.

Certain enterprises at the fringes of science, such as intelligent design creationism, claim to identify phenomena that go beyond not just our present physics but any possible physical explanation. Asking what it would take for such a claim to succeed, we introduce a version of physicalism that formulates the proposition that all available data sets are best explained by combinations of “chance and necessity”—algorithmic rules and randomness. Physicalism would then be violated by the existence of oracles that produce certain kinds (...) of noncomputable functions. Examining how a candidate for such an oracle would be evaluated leads to questions that do not admit an easy resolution. Since we lack any plausible candidate for any such oracle, however, chance-and-necessity physicalism appears very likely to be correct. (shrink)

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. (shrink)