Peter Godfrey-Smith

The first part of this chapter revisits central themes in Armstrong’s defence and development of materialism about the mind. It argues that Armstrong’s focus on ‘peripheral’ mental states involving perception and intention leads to a mishandling of ‘core’ states, especially belief and desire. Frank Ramsey’s belief-desire model, developed decades earlier, enables a better handling of core mental states. The second part of the chapter looks at the present status of materialism—what the position amounts to, and why we might believe it. Parsimony arguments for materialism (used by Armstrong and Smart) are rejected. More compelling arguments make use of continuities between human and non-human mental capacities, and an evolutionary perspective. A form of ‘neutral monism’ is introduced as a better rival to materialism than other nonmaterialist views, but is also rejected.

Familiar summaries of evolution by natural selection hold that one requirement for change of this kind is heredity. Parents must resemble their offspring; like must beget like. However, many life cycles feature long and complex chains in which like begets unlike, before they return to their starting point. Such life cycles are common, being seen in various plants, animals, fungi, and protists. In response to these cases, the chapter offers a framework in which the familiar notion of reproduction is treated as a special case of a broader category.

Dennett argues that Darwinism provides a universal theory of adaptation and improvement in design. In his “Tower of Generate and Test,” Dennett distinguishes four kinds of creatures that realize a Darwinian pattern on different scales and with different degrees of sophistication: Darwinian, Skinnerian, Popperian, and Gregorian creatures. I examine Dennett’s tower in the light of recent work on learning, and in the context of the phylogenetic tree. A class of associative learners—Humean organisms—probably lies between Dennett’s Darwinian and Skinnerian creatures. Various cognitive capacities are also more demanding than instrumental conditioning, but insufficient for Popperian cognition in Dennett’s sense. Creatures corresponding to these intermediate stages are named—Carnapian, Pearlian, Tolmanian. These stages are not arranged in a tower.

This chapter discusses recent debates about scientific models and fictional or imaginary systems. Model-based science often apparently deals in non-actual or fictional systems, and does so by design. This practice raises questions about the relationships that can exist between such models and their real-world targets, especially about the evident empirical utility of some highly idealized scientific models. The chapter considers a range of recent treatments of models and offers an account that gives a central role to counterfactual conditionals. This chapter takes these conditionals to be the typical output of scientific modeling. These conditionals raise many problems of their own, but understanding models in these terms does enable some progress.

This chapter examines the idea that innateness can be understood in terms of genetic coding or genetic programming. A distinction is made between characteristics that are coded for or programmed for by the genes, and characteristics that are not. It is argued that the defensible versions of this distinction line up badly with the idea of innateness. The defensible versions of the idea of genetic coding treat only protein molecules as coded for. The defensible versions of the idea that developmental processes involve something like computation apply only to low-level processes, so the ‘programmed for’ traits are again too low-level to be of interest to nativists. Other versions of the idea that innate traits are ‘programmed to appear’ are in effect a handing-off of the problem to the concept of adaptation or evolutionary design.

Our understanding of communication and its evolution has advanced significantly through the study of simple models involving interacting senders and receivers of signals. Many theorists have thought that the resources of mathematical information theory are all that are needed to capture the meaning or content that is being communicated in these systems. However, the way theorists routinely talk about the models implicitly draws on a conception of content that is richer than bare informational content, especially in contexts where false content is important. This article shows that this concept can be made precise by defining a notion of functional content that captures the degree to which different states of the world are involved in stabilizing senders’ and receivers’ use of a signal at equilibrium. A series of case studies is used to contrast functional content with informational content, and to illustrate the explanatory role and limitations of this definition of functional content. _1_ Introduction _2_ Modelling Framework _3_ Two Kinds of Content _3.1_ Informational content _3.2_ Functional content _4_ Cases _4.1_ Case 1: Simplest case _4.2_ Case 2: Partial pooling _4.3_ Case 3: Bottleneck _4.4_ Case 4: Partial common interest _4.5_ Case 5: Deception _4.6_ Case 6: A further problem arising from divergent interests _5_ Discussion Appendix

How does science work? Does it tell us what the world is "really" like? What makes it different from other ways of understanding the universe? In Theory and Reality, Peter Godfrey-Smith addresses these questions by taking the reader on a grand tour of more than a hundred years of debate about science. The result is a completely accessible introduction to the main themes of the philosophy of science. Examples and asides engage the beginning student; a glossary of terms explains key concepts; and suggestions for further reading are included at the end of each chapter. Like no other text in this field, Theory and Reality combines a survey of recent history of the philosophy of science with current key debates that any beginning scholar or critical reader can follow. The second edition is thoroughly updated and expanded by the author with a new chapter on truth, simplicity, and models in science.

I will sketch, but not argue for here, a hypothesis about its origins and structure. What philosophers think of as folk psychology has dual origins. One is a genuine "intuitive psychology." This is an evolved predictive tool seen also in some nonhuman animals and very young children. It is "peripheral" in what it recognizes and describes. Primarily, it recognizes seeing and acting (including trying) as activities of others. This is common element in how human and non-human animals deal with each other. The full folk psychology that we are familiar with in philosophical discussion also includes a model of psychological interactions within the periphery. This model is based perhaps on discourse, the exchange of sentences in public – roughly as Wilfrid Sellars suggested many years ago. This part of folk psychology, unlike the first, might be expected to show some cultural variation. The resulting framework might be fine for describing certain kinds of human thought, but it is problematic when applied more generally.

Two of the most potent challenges faced by scientific realism are the underdetermination of theories by data, and the pessimistic induction based on theories previously held to be true, but subsequently acknowledged as false. Recently, Stanford (2006, Exceeding our grasp: Science, history, and the problem of unconceived alternatives. Oxford: Oxford University Press) has formulated what he calls the problem of unconceived alternatives: a version of the underdetermination thesis combined with a historical argument of the same form as the pessimistic induction. In this paper, I contend that while Stanford does present a novel antirealist argument, a successful response to the pessimistic induction would likewise defuse the problem of unconceived alternatives, and that a more selective and sophisticated realism than that which he allows is arguably immune to both concerns.

It is well known that informational theories of representation have trouble accounting for error. Informational semantics is a family of theories attempting a naturalistic, unashamedly reductive explanation of the semantic and intentional properties of thought and language. Most simply, the informational approach explains truth-conditional content in terms of causal, nomic, or simply regular correlation between a representation and a state of affairs. The central work is Dretske, and the theory was largely developed at the University of Wisconsin by Fred Dretske, Dennis Stampe, and Berent Enc. Recently, informational semantics has roamed far beyond its Wisconsin home, and built a sizeable collection of followers. Converts include Jerry Fodor, Robert Stalnaker and, less faithfully, Paul and Patricia Churchland and Hartry Field. But for some years informational semantics has been hounded by a problem with error – the classic presentation is Fodor – and no other problem has hounded the theory so persistently.