The success of a piece of behaviour is often explained by its being caused by a true representation (similarly, failure falsity). In some simple organisms, success is just survival and reproduction. Scientists explain why a piece of behaviour helped the organism to survive and reproduce by adverting to the behaviour’s having been caused by a true representation. That usage should, if possible, be vindicated by an adequate naturalistic theory of content. Teleosemantics cannot do so, when it is applied to simple (...) representing systems (Godfrey-Smith 1996). Here it is argued that the teleosemantic approach to content should therefore be modified, not abandoned, at least for simple representing systems. The new ‘infotel-semantics’ adds an input condition to the output condition offered by teleosemantics, recognising that it is constitutive of content in a simple representing system that the tokening of a representation should correlate probabilistically with the obtaining of its specific evolutionary success condition. (shrink)

How the various things that are said to have meaning—purpose, natural signs, linguistic signs, perceptions, and thoughts—are related to one another.

This book presents an attempt to develop a theory of knowledge and a philosophy of mind using ideas derived from the mathematical theory of communication developed by Claude Shannon. Information is seen as an objective commodity defined by the dependency relations between distinct events. Knowledge is then analyzed as information caused belief. Perception is the delivery of information in analog form for conceptual utilization by cognitive mechanisms. The final chapters attempt to develop a theory of meaning by viewing meaning as (...) a certain kind of information-carrying role. (shrink)

A theory of information is developed in which the informational content of a signal (structure, event) can be specified. This content is expressed by a sentence describing the condition at a source on which the properties of a signal depend in some lawful way. Information, as so defined, though perfectly objective, has the kind of semantic property (intentionality) that seems to be needed for an analysis of cognition. Perceptual knowledge is an information-dependent internal state with a content corresponding to the (...) information producing it. This picture of knowledge captures most of what makes knowledge an important cpistcmological notion. It also avoids many of the problems infecting traditional justificational accounts of knowledge (knowledge as [justified, true belief those (unlike knowledge) having a content that can be either true or false (e.g., belief) – are described in terms of the way internal (presumably neural) structures acquire during learning a certain information-carrying role. The content of these structures (whether true or false) is identified with the kind of information they were developed to carry. (shrink)

There is no consensus yet on the definition of semantic information. This paper contributes to the current debate by criticising and revising the Standard Definition of semantic Information (SDI) as meaningful data, in favour of the Dretske‐Grice approach: meaningful and well‐formed data constitute semantic information only if they also qualify as contingently truthful. After a brief introduction, SDI is criticised for providing necessary but insufficient conditions for the definition of semantic information. SDI is incorrect because truth‐values do not supervene on (...) semantic information, and misinformation (that is, false semantic information) is not a type of semantic information, but pseudo‐information, that is not semantic information at all. This is shown by arguing that none of the reasons for interpreting misinformation as a type of semantic information is convincing, whilst there are compelling reasons to treat it as pseudo‐information. As a consequence, SDI is revised to include a necessary truth‐condition. The last section summarises the main results of the paper and indicates some interesting areas of application of the revised definition. (shrink)

In his essay "Consumers Need Information: Supplementing Teleosemantics with an Input Condition" (this issue) Nicholas Shea argues, with support from the work of Peter Godfrey-Smith (1996), that teleosemantics, as David Papinau and I have articulated it, cannot explain why "content attribution can be used to explain successful behavior." This failure is said to result from defining the intentional contents of representations by reference merely to historically normal conditions for success of their "outputs," that is, of their uses by interpreting or (...) consuming mechanisms, bypassing the more traditional focus, of those who would naturalize intentional content, on causal or informational inputs. Shea proposes to "add an input condition to teleosemantics," requiring that simple representations must carry "correlational information." I am grateful to Shea for his paper, as it presents me with an opportunity to clarify two fairly central features of my position on intentional content, one of which seems to have been overlooked in the literature (Millikan 1993a), the other of which I have stated previously only in a confusing way (Millikan 2004, Chapters 3-4). The first clarification concerns the general form that I take explanation by reference to intentional states to have. The second concerns my description of "locally recurrent natural information," why this kind of information is needed in place of Shea's "correlational information" to explain what feeds simple representational systems, and why no reference to natural information is needed to account for the success of behaviors by reference to the truth of representations that motivate them. (shrink)

This paper examines the relationship between a family of concepts involving reliable correlation, and a family of concepts involving adaptation and biological function, as these concepts are used in the naturalistic semantic theory of Dretske's "Explaining Behavior." I argue that Dretske's attempt to marry correlation and function to produce representation fails, though aspects of his failure point the way forward to a better theory.

We offer a novel theory of information that differs from traditional accounts in two respects: (i) it explains information in terms of counterfactuals rather than conditional probabilities, and (ii) it does not make essential reference to doxastic states of subjects, and consequently allows for the sort of objective, reductive explanations of various notions in epistemology and philosophy of mind that many have wanted from an account of information.