Richard Dawkins has popularized an argument which, according to him, proves that there is almost certainly no God. It rests on the assumption that complex and statistically improbable things are more difficult to explain than those that are not, and that any explanatory mechanism that is called on to do the explaining must show how this complexity can be built up from simpler means as it would be useless otherwise. In this paper, I first question what justifies the consideration of (...) the designer’s own complexity. I suggest a different understanding of both order and simplicity inevitable when one considers the psychological counterpart of information. I then assess what seems to be the inference engine of the proposal, the metaphor of biological organisms as either self-programmed machines or algorithms. I show how self-generated organized complexity would not sit well with our knowledge of both abduction and the theorems of information theory applied to genetics. I then turn to the positive side of Dawkins’ challenge, and I review some philosophers and their proposals for how the complexity of the world could be controlled from outside if one wanted to uphold a traditional understanding of God’s simplicity. (shrink)

Most cognitive scientists nowadays tend to think that at least some of the mind’s capacities are the product of biological evolution, yet important conceptual problems remain for all of them in order to be able to speak coherently of mental or cognitive systems as having evolved naturally. Two of these important problems concern the articulation of adequate, interesting and empirically useful concepts of homology and variation as applied to cognitive systems. However, systems in cognitive science are usually understood as functional (...) systems of some sort. Thus, talking about functional systems’ being homologous requires one’s having a solid, adequate and empirically articulated concept of functional homology—and the same is true of functional variation. Here I construct an original concept of functional homology that, in my view, adequately systematizes a number of the actual uses of the word ‘functional homology’ in a variety of biological disciplines and in ethology. I also propose a number of criteria for the empirical application of the concept that are analogous to the criteria that are actually used in comparative biology, ethology, and (possibly) molecular developmental genetics. Then I construct a concept of functional variation on the basis of this concept of homology. (shrink)

Ever since Darwin people have worried about the sceptical implications of evolution. If our minds are products of evolution like those of other animals, why suppose that the beliefs they produce are true, rather than merely useful? In this chapter we apply this argument to beliefs in three different domains: morality, religion, and science. We identify replies to evolutionary scepticism that work in some domains but not in others. The simplest reply to evolutionary scepticism is that the truth of beliefs (...) in a certain domain is, in fact, connected to evolutionary success, so that evolution can be expected to design systems that produce true beliefs in that domain. We call a connection between truth and evolutionary success a ‘Milvian bridge’, after the tradition which ascribes the triumph of Christianity at the battle of the Milvian bridge to the truth of Christianity. We argue that a Milvian bridge can be constructed for commonsense beliefs, and extended to scientific beliefs, but not to moral and religious beliefs. An alternative reply to evolutionary scepticism, which has been used defend moral beliefs, is to argue that their truth does not depend on their tracking some external state of affairs. We ask if this reply could be used to defend religious beliefs. (shrink)

Evolutionary psychologists, among others, have used a method called “reverse engineering” to uncover ( a ) whether a trait was selected for, and ( b ) if so, why that trait was selected for. In this paper I argue that reverse engineering cannot deliver on either ( a ) or ( b ), and tends to pervert, rather than enhance, our knowledge of natural history. In particular, I expose as false a fundamental assumption of reverse engineering—namely, that all traits selected (...) for a particular function will share some nontrivial properties. *Received March 2006; revised June 2008. †To contact the author, please write to: Department of Philosophy, 229 Major Williams Hall (0126), Virginia Tech, Blacksburg, VA 24061; e‐mail: haufe@vt.edu. (shrink)

Making Sense of Evolution explores contemporary evolutionary biology, focusing on the elements of theories—selection, adaptation, and species—that are complex and open to multiple possible interpretations, many of which are incompatible with one another and with other accepted practices in the discipline. Particular experimental methods, for example, may demand one understanding of “selection,” while the application of the same concept to another area of evolutionary biology could necessitate a very different definition.