This paper presents a counterfactual account of what a mechanism is. Mechanisms consist of parts, the behavior of which conforms to generalizations that are invariant under interventions, and which are modular in the sense that it is possible in principle to change the behavior of one part independently of the others. Each of these features can be captured by the truth of certain counterfactuals.

Woodward's long awaited book is an attempt to construct a comprehensive account of causation explanation that applies to a wide variety of causal and explanatory claims in different areas of science and everyday life. The book engages some of the relevant literature from other disciplines, as Woodward weaves together examples, counterexamples, criticisms, defenses, objections, and replies into a convincing defense of the core of his theory, which is that we can analyze causation by appeal to the notion of manipulation.

The genetic code has been regarded as arbitrary in the sense that the codon-amino acid assignments could be different than they actually are. This general idea has been spelled out differently by previous, often rather implicit accounts of arbitrariness. They have drawn on the frozen accident theory, on evolutionary contingency, on alternative causal pathways, and on the absence of direct stereochemical interactions between codons and amino acids. It has also been suggested that the arbitrariness of the genetic code justifies attributing (...) semantic information to macromolecules, notably to DNA. I argue that these accounts of arbitrariness are unsatisfactory. I propose that the code is arbitrary in the sense of Jacques Monod's concept of chemical arbitrariness: the genetic code is arbitrary in that any codon requires certain chemical and structural properties to specify a particular amino acid, but these properties are not required in virtue of a principle of chemistry. This notion of arbitrariness is compatible with several recent hypotheses about code evolution. I maintain that the code's chemical arbitrariness is neither sufficient nor necessary for attributing semantic information to nucleic acids. (shrink)

The use of informational terms is widespread in molecular and developmental biology. The usage dates back to Weismann. In both protein synthesis and in later development, genes are symbols, in that there is no necessary connection between their form (sequence) and their effects. The sequence of a gene has been determined, by past natural selection, because of the effects it produces. In biology, the use of informational terms implies intentionality, in that both the form of the signal, and the response (...) to it, have evolved by selection. Where an engineer sees design, a biologist sees natural selection. (shrink)

Inevitably, much of this reply will concern points on which I disagree with one or other of the commentators. I should start, therefore, by saying that I am delighted to find that their thinking is in many ways similar to my own, and that a serious attempt is under way to clarify the concept of information in biology.

Maynard Smith notes that he provides a natural history and not a philosophical analysis of the use of concepts of information in contemporary biology. Just a natural history, however rich, would do little to resolve the ongoing controversy about the role of these concepts in biology. None of the disputants deny that the biological use of these concepts is pervasive. The dispute is about whether these concepts—and the framework in which they are embedded—continue to be of explanatory value in contemporary (...) biology. Fortunately, Maynard Smith does much more than provide a natural history: his contribution is also a sustained attempt to justify many of the uses of information in biology. (shrink)

The concept of mechanism is analyzed in terms of entities and activities, organized such that they are productive of regular changes. Examples show how mechanisms work in neurobiology and molecular biology. Thinking in terms of mechanisms provides a new framework for addressing many traditional philosophical issues: causality, laws, explanation, reduction, and scientific change.

Maynard Smith is right that one of the most striking features of contemporary biology is the ever-increasing prominence of the concept of information, along with related concepts like representation, programming, and coding. Maynard Smith is also right that this is surely a phenomenon which philosophers of science should examine closely. We should try to understand exactly what sorts of theoretical commitment are made when biological systems are described in these terms, and what connection there is between semantic descriptions in biology (...) and in other domains. (shrink)

In this lucid portrayal of human behavior, Fred Dretske provides an original account of the way reasons function in the causal explanation of behavior.

Many areas of science develop by discovering mechanisms and role functions. Cummins' (1975) analysis of role functions-according to which an item's role function is a capacity of that item that appears in an analytic explanation of the capacity of some containing system-captures one important sense of "function" in the biological sciences and elsewhere. Here I synthesize Cummins' account with recent work on mechanisms and causal/mechanical explanation. The synthesis produces an analysis of specifically mechanistic role functions, one that uses the characteristic (...) active, spatial, temporal, and hierarchical organization of mechanisms to add precision and content to Cummins' original suggestion. This synthesis also shows why the discovery of role functions is a scientific achievement. Discovering a role function (i) contributes to the interlevel integration of multilevel mechanisms, and (ii) provides a unique, contextual variety of causal/mechanical explanation. (shrink)

Biologists rely heavily on the language of information, coding, and transmission that is commonplace in the field of information theory developed by Claude Shannon, but there is open debate about whether such language is anything more than facile metaphor. Philosophers of biology have argued that when biologists talk about information in genes and in evolution, they are not talking about the sort of information that Shannon’s theory addresses. First, philosophers have suggested that Shannon’s theory is only useful for developing a (...) shallow notion of correlation, the so-called causal sense of information. Second, they typically argue that in genetics and evolutionary biology, information language is used in a semantic sense, whereas semantics are deliberately omitted from Shannon’s theory. Neither critique is well-founded. Here we propose an alternative to the causal and semantic senses of information: a transmission sense of information, in which an object X conveys information if the function of X is to reduce, by virtue of its sequence properties, uncertainty on the part of an agent who observes X. The transmission sense not only captures much of what biologists intend when they talk about information in genes, but also brings Shannon’s theory back to the fore. By taking the viewpoint of a communications engineer and focusing on the decision problem of how information is to be packaged for transport, this approach resolves several problems that have plagued the information concept in biology, and highlights a number of important features of the way that information is encoded, stored, and transmitted as genetic sequence. (shrink)

Response to commentaries on “The Transmission Sense of Information” Content Type Journal Article Pages 195-200 DOI 10.1007/s10539-011-9257-3 Authors Carl T. Bergstrom, Department of Biology, University of Washington, Seattle, WA 98195-1800, USA Martin Rosvall, Integrated Science Lab, Department of Physics, Umeå University, 901 87 Umeå, Sweden Journal Biology and Philosophy Online ISSN 1572-8404 Print ISSN 0169-3867 Journal Volume Volume 26 Journal Issue Volume 26, Number 2.

Philosophy of science is positioned to make distinctive contributions to cognitive science by providing perspective on its conceptual foundations and by advancing normative recommendations. The philosophy of science I embrace is naturalistic in that it is grounded in the study of actual science. Focusing on explanation, I describe the recent development of a mechanistic philosophy of science from which I draw three normative consequences for cognitive science. First, insofar as cognitive mechanisms are information-processing mechanisms, cognitive science needs an account of (...) how the representations invoked in cognitive mechanisms carry information about contents, and I suggest that control theory offers the needed perspective on the relation of representations to contents. Second, I argue that cognitive science requires, but is still in search of, a catalog of cognitive operations that researchers can draw upon in explaining cognitive mechanisms. Last, I provide a new perspective on the relation of cognitive science to brain sciences, one which embraces both reductive research on neural components that figure in cognitive mechanisms and a concern with recomposing higher-level mechanisms from their components and situating them in their environments. (shrink)

Philosophy of science is positioned to make distinctive contributions to cognitive science by providing perspective on its conceptual foundations and by advancing normative recommendations. The philosophy of science I embrace is naturalistic in that it is grounded in the study of actual science. Focusing on explanation, I describe the recent development of a mechanistic philosophy of science from which I draw three normative consequences for cognitive science. First, insofar as cognitive mechanisms are information‐processing mechanisms, cognitive science needs an account of (...) how the representations invoked in cognitive mechanisms carry information about contents, and I suggest that control theory offers the needed perspective on the relation of representations to contents. Second, I argue that cognitive science requires, but is still in search of, a catalog of cognitive operations that researchers can draw upon in explaining cognitive mechanisms. Last, I provide a new perspective on the relation of cognitive science to brain sciences, one which embraces both reductive research on neural components that figure in cognitive mechanisms and a concern with recomposing higher‐level mechanisms from their components and situating them in their environments. (shrink)

Change and necessity is a statement of Darwinian natural selection as a process driven by chance necessity, devoid of purpose or intent.

Causal selection has to do with the distinction we make between background conditions and “the” true cause or causes of some outcome of interest. A longstanding consensus in philosophy views causal selection as lacking any objective rationale and as guided, instead, by arbitrary, pragmatic, and non-scientific considerations. I argue against this position in the context of causal selection for disease traits. In this domain, causes are selected on the basis of the type of causal control they exhibit over a disease (...) of interest. My analysis clarifies the principled rationale that guides this selection and how it involves both pragmatic and objective considerations, which have been overlooked in the extant literature. (shrink)