The concept of information tempts us as a theoretical primitive, partly because of the respectability lent to it by highly successful applications of Shannon’s information theory, partly because of its broad range of applicability in various domains, partly because of its neutrality with respect to what basic sorts of things there are. This versatility, however, is the very reason why information cannot be the theoretical primitive we might like it to be. “Information,” as it is variously used, is systematically ambiguous (...) between whether it involves continuous or discrete quantities, causal or noncausal relationships, and intrinsic or relational properties. Many uses can be firmly grounded in existing theory, however. Continuous quantities of information involving probabilities can be related to information theory proper. Information defined relative to systems of rules or conventions can be understood relative to the theory of meaning . A number of causal notions may possibly be located relative to standard notions in physics. Precise specification of these distinct properties involved in the common notion of information can allow us to map the relationships between them. Consequently, while information is not in itself the kind of single thing that can play a significant unifying role, analyzing its ambiguities may facilitate headway toward that goal. (shrink)

Mechanistic accounts of explanation have recently found popularity within philosophy of science. Presently, we introduce the idea of an extended mechanistic explanation, which makes explicit room for the role of environment in explanation. After delineating Craver and Bechtel’s account, we argue this suggestion is not sufficiently robust when we take seriously the mechanistic environment and modeling practices involved in studying contemporary complex biological systems. Our goal is to extend the already profitable mechanistic picture by pointing out the importance of the (...) mechanistic environment. It is our belief that extended mechanistic explanations, or mechanisms that take into consideration the temporal sequencing of the interplay between the mechanism and the environment, allow for mechanistic explanations regarding a broader group of scientific phenomena. (shrink)

Information theory offers a measure of "mutual information" which provides an appropriate measure of tracking efficiency for the naturalistic epistemologist. The statistical entropy on which it is based is arguably the best way of characterizing the uncertainty associated with the behavior of a system, and it is ontologically neutral. Though not appropriate for the naturalization of meaning, mutual information can serve as a measure of epistemic success independent of semantic maps and payoff structures. While not containing payoffs as terms, mutual (...) information places both upper and lower bounds on payoffs. This constitutes a non-trivial relationship to utility. (shrink)

Conventional wisdom has it that evolution makes a sham of morality, even if morality is an adaptation. I disagree. I argue that our best current adaptationist theory of meaning offers objective truth conditionsfor signaling systems of all sorts. The objectivity is, however, relative to species – specifically to the adaptive history of the signaling system in question. While evolution may not provide the kind of species independent objective standards that (e.g.) Kantians desire, this should be enough for the practical work (...) of justifying our confidence in the objectivity of moral standards. If you believe morality is an adaptation, you should be a moral realist. (shrink)