Understanding the dynamics of information is crucial to many areas of research, both inside and outside of philosophy. Using computer simulations of three kinds of information, germs, genes, and memes, we show that the mechanism of information transfer often swamps network structure in terms of its effects on both the dynamics and the fitness of the information. This insight has both obvious and subtle implications for a number of questions in philosophy, including questions about the nature of information, whether there (...) is genetic information, and how to arrange scientific communities. (shrink)

Reuben Hersh confided to us that, about forty years ago, the late Paul Cohen predicted to him that at some unspecified point in the future, mathematicians would be replaced by computers. Rather than focus on computers replacing mathematicians, however, our aim is to consider the (im)possibility of human mathematicians being joined by “artificial mathematicians” in the proving practice—not just as a method of inquiry but as a fellow inquirer.

The recently celebrated division into ‘easy’ and ‘hard’ problems of consciousness is unfortunate and misleading. Built on functionalist grounds, it carves up the subject matter by declaring that the most elusive parts need a fundamentally and intrinsically different solution. What we have, rather, are ‘difficult’ problems of conscious experience, but problems that are not difficult per se. Their difficulty is relative, among other things, to the kind of solution one is looking for and the tools used to accomplish the task. (...) I argue that the study of conscious experience in our scientific and philosophical tradition is a very difficult problem because it has been addressed with inappropriate tools: with harmful long-lasting and inadequate dogmas that have dogged science for centuries. I describe five of these dogmas, which are: the existence of an objective reality independent of human understanding; the subordination of epistemology to ontology; the restricted view of the objectivist-subjectivist dichotomy; the exclusion of the body from the study of the mind; and the idea of explaining the mind in terms of the neurophysiological processes of individual brains. I claim that conscious experience is not a transcendental, paranatural, mystic or magic phenomenon. It is tractable and approachable with scientific methods. However, one must look not only for non-reductionist views to approach it, but also for views that avoid the dogmas here described. Conscious experience is a living phenomenon and it has to be understood as such. Accordingly, our understanding of it has to make sense at several levels, from evolution to morphophysiology, from neuroanatomy to language. I put forward an approach to conscious experience which is free of the dogmas that make the study of conscious experience so difficult. This view, called ecological naturalism, is a non-functionalist and non-reductive view that provides an naturalistic account of the mind. It also puts special emphasis on irreducible supra-individual biological processes that are essential in the realization of mental phenomena and therefore conscious experience. (shrink)

The present work is focussed on the completeness of physics, or what is here called the Completeness Thesis: the claim that the domain of the physical is causally closed. Two major questions are tackled: How best is the Completeness Thesis to be formulated? What can be said in defence of the Completeness Thesis? My principal conclusions are that the Completeness Thesis can be coherently formulated, and that the evidence in favour if it significantly outweighs that against it. In opposition to (...) those who argue that formulation is impossible because no account of what is to count as physical can be provided, I argue that as long as the purpose of the argument in which the account is to be used are borne in mind there are no significant difficulties. The account of the physical which I develop holds as physical whatever is needed to fix the likelihood of pre-theoretically given physical effects, and hypothesises in addition that no chemical, biological or psychological factors will be needed in this way. The thus formulated Completeness Thesis is coherent, and has significant empirical content. In opposition to those who defend the doctrine of emergentism by means of philosophical arguments I contend that those arguments are flawed, setting up misleading dichotomies between needlessly attenuated alternatives and assuming the truth of what is to be proved. Against those who defend emergentism by appeal to the evidence, I argue that the history of science since the nineteenth century shows clearly that the empirical credentials of the view that the world is causally closed at the level of a small number of purely physical forces and types of energy is stronger than ever, and the credentials of emergentism correspondingly weaker. In opposition to those who argue that difficulties with reductionism point to the implausibility of the Completeness Thesis I argue that completeness in no way entails the kinds of reductionism which give rise to the difficulties in question. I argue further that the truth of the Completeness Thesis is in fact compatible with a great deal of taxonomic disorder and the impossibility of any general reduction of non-fundamental descriptions to fundamental ones. In opposition to those who argue that the epistemological credentials of fundamental physical laws are poor, and that those laws should in fact be seen as false, I contend that truth preserving accounts of fundamental laws can be developed. Developing such an account, I test it by considering cases of the composition of forces and causes, where what takes place is different to what is predicted by reference to any single law, and argue that viewing laws as tendencies allows their truth to be preserved, and sense to be made of both the experimental discovery of laws, and the fact that composition enables accurate prediction in at least some cases. (shrink)

The topics of modeling and information come together in at least two ways. Computational modeling and simulation play an increasingly important role in science, across disciplines from mathematics through physics to economics and political science. The philosophical questions at issue are questions as to what modeling and simulation are adding, altering, or amplifying in terms of scientific information. What changes with regard to information acquisition, theoretical development, or empirical confirmation with contemporary tools of computational modeling? In this sense the title (...) of this article is read in the following way: What kind of information is modeling information? What kind of information does modeling give us? (shrink)