Triviality arguments against the computational theory of mind claim that computational implementation is trivial and thus does not serve as an adequate metaphysical basis for mental states. It is common to take computational implementation to consist in a mapping from physical states to abstract computational states. In this paper, I propose a novel constraint on the kinds of physical states that can implement computational states, which helps to specify what it is for two physical states to non-trivially implement the same (...) computational state. (shrink)

This volume argues for a new image of science that understands both natural and social phenomena to be the product of mechanisms, casting the work of science as an effort to understand those mechanisms. Glennan offers an account of the nature of mechanisms and of the models used to represent them in physical, life, and social sciences.

Explanations in the life sciences frequently involve presenting a model of the mechanism taken to be responsible for a given phenomenon. Such explanations depart in numerous ways from nomological explanations commonly presented in philosophy of science. This paper focuses on three sorts of differences. First, scientists who develop mechanistic explanations are not limited to linguistic representations and logical inference; they frequently employ diagrams to characterize mechanisms and simulations to reason about them. Thus, the epistemic resources for presenting mechanistic explanations are (...) considerably richer than those suggested by a nomological framework. Second, the fact that mechanisms involve organized systems of component parts and operations provides direction to both the discovery and testing of mechanistic explanations. Finally, models of mechanisms are developed for specific exemplars and are not represented in terms of universally quantified statements. Generalization involves investigating both the similarity of new exemplars to those already studied and the variations between them. (shrink)

For the claim that the satisfaction of certain conditions is sufficient for the application of some concept to serve as part of the (‘reductive’) analysis of that concept, we require the conditions to be specified without employing that very concept. An account of the application conditions of a concept not meeting this requirement, we call analytically circular. For such a claim to be usable in determining the extension of the concept, however, such circularity may not matter, since if the concept (...) figures in a certain kind of intensional context in the specification of the conditions, the satisfaction of those conditions may not itself depend on the extension of the concept. We put this by saying that although analytically circular, the account may yet not be inferentially circular. (shrink)

Beginning with a historical overview of relativism, from Pythagoras in ancient Greece to Derrida and postmodernism, Maria Baghramian explores the resurgence of relativism throughout the history of philosophy. She then turns to the arguments for and against the many subdivisions of relativism, including Kuhn and Feyerabend's ideas of relativism in science, Rorty's relativism about truth, and the conceptual relativism of Quine and Putnam. Baghramian questions whether moral relativism leads to moral indifference or even nihilism, and whether feminist epistemology's concerns about (...) the very notion of objectivity can be considered a form of relativism. She concludes the relativism debate by assessing the recent criticisms such as Quine's argument from translation and Davidson's claim that even the motivations behind relativism are unintelligible. Finding these criticisms lacking, Baghramian proposes a moderate form of pluralism which addresses the legitimate worries that give rise to relativism without incurring charges of nihilism or anarchy. (shrink)

Physical Computation is the summation of Piccinini’s work on computation and mechanistic explanation over the past decade. It draws together material from papers published during that time, but also provides additional clarifications and restructuring that make this the definitive presentation of his mechanistic account of physical computation. This review will first give a brief summary of the account that Piccinini defends, followed by a chapter-by-chapter overview of the book, before finally discussing one aspect of the account in more critical detail.

The question ‘What is computation?’ might seem a trivial one to many, but this is far from being in consensus in philosophy of mind, cognitive science and even in physics. The lack of consensus leads to some interesting, yet contentious, claims, such as that cognition or even the universe is computational. Some have argued, though, that computation is a subjective phenomenon: whether or not a physical system is computational, and if so, which computation it performs, is entirely a matter of (...) an observer choosing to view it as such. According to one view, which we dub bold anti-realist pancomputationalism, every physical object (can be said to) computes every computer program. According to another, more modest view, some computational systems can be ascribed multiple computational descriptions. We argue that the first view is misguided, and that the second view need not entail observer-relativity of computation. At least to a large extent, computation is an objective phenomenon. Construed as a form of information processing, we argue that information-processing considerations determine what type of computation takes place in physical systems. (shrink)

'Modern History' views claim that in order for a trait X to have the proper function F, X must have been recently favored by natural selection for doing F (Griffiths 1992, 1993; Godfrey-Smith 1994). For many traits with prototypical proper functions, however, such recent selection may not have occurred, since traits may have been maintained owing to lack of variation or selection for other effects. I explore this flaw in Modern History accounts and offer an alternative etiological theory, which I (...) call the 'Continuing Usefulness' account. According to my view, a trait has the proper function F if and only if, first, the trait was favored by selection for doing F at some point (perhaps far in the past), and, secondly, the trait has recently contributed to survival and reproduction by doing F. This separates the requirement involving natural selection from the one involving the recent past, two issues that the Modern History account conflates. The clear separation allows a detailed analysis of the causal judgments and form of adaptationism that ground the etiological approach to function. (shrink)

We begin by distinguishing computationalism from a number of other theses that are sometimes conflated with it. We also distinguish between several important kinds of computation: computation in a generic sense, digital computation, and analog computation. Then, we defend a weak version of computationalism—neural processes are computations in the generic sense. After that, we reject on empirical grounds the common assimilation of neural computation to either analog or digital computation, concluding that neural computation is sui generis. Analog computation requires continuous (...) signals; digital computation requires strings of digits. But current neuroscientific evidence indicates that typical neural signals, such as spike trains, are graded like continuous signals but are constituted by discrete functional elements (spikes); thus, typical neural signals are neither continuous signals nor strings of digits. It follows that neural computation is sui generis. Finally, we highlight three important consequences of a proper understanding of neural computation for the theory of cognition. First, understanding neural computation requires a specially designed mathematical theory (or theories) rather than the mathematical theories of analog or digital computation. Second, several popular views about neural computation turn out to be incorrect. Third, computational theories of cognition that rely on non-neural notions of computation ought to be replaced or reinterpreted in terms of neural computation. (shrink)

Carl F. Craver investigates what we are doing when we use neuroscience to explain what's going on in the brain. When does an explanation succeed and when does it fail? Craver offers explicit standards for successful explanation of the workings of the brain, on the basis of a systematic view about what neuroscientific explanations are.

We sketch a framework for building a unified science of cognition. This unification is achieved by showing how functional analyses of cognitive capacities can be integrated with the multilevel mechanistic explanations of neural systems. The core idea is that functional analyses are sketches of mechanisms , in which some structural aspects of a mechanistic explanation are omitted. Once the missing aspects are filled in, a functional analysis turns into a full-blown mechanistic explanation. By this process, functional analyses are seamlessly integrated (...) with multilevel mechanistic explanations. (shrink)

Every Thing Must Go aruges that the only kind of metaphysics that can contribute to objective knowledge is one based specifically on contemporary science as it ...

Many people assume that the claims of scientists are objective truths. But historians, sociologists, and philosophers of science have long argued that scientific claims reflect the particular historical, cultural, and social context in which those claims were made. The nature of scientific knowledge is not absolute because it is influenced by the practice and perspective of human agents. Scientific Perspectivism argues that the acts of observing and theorizing are both perspectival, and this nature makes scientific knowledge contingent, as Thomas Kuhn (...) theorized forty years ago. Using the example of color vision in humans to illustrate how his theory of “perspectivism” works, Ronald N. Giere argues that colors do not actually exist in objects; rather, color is the result of an interaction between aspects of the world and the human visual system. Giere extends this argument into a general interpretation of human perception and, more controversially, to scientific observation, conjecturing that the output of scientific instruments is perspectival. Furthermore, complex scientific principles—such as Maxwell’s equations describing the behavior of both the electric and magnetic fields—make no claims about the world, but models based on those principles can be used to make claims about specific aspects of the world. Offering a solution to the most contentious debate in the philosophy of science over the past thirty years, Scientific Perspectivism will be of interest to anyone involved in the study of science. (shrink)

Philosophers of science typically associate the causal-mechanical view of scientific explanation with the work of Railton and Salmon. In this paper I shall argue that the defects of this view arise from an inadequate analysis of the concept of mechanism. I contrast Salmon's account of mechanisms in terms of the causal nexus with my own account of mechanisms, in which mechanisms are viewed as complex systems. After describing these two concepts of mechanism, I show how the complex-systems approach avoids certain (...) objections to Salmon's account of causal-mechanical explanation. I conclude by discussing how mechanistic explanations can provide understanding by unification. (shrink)

In this paper I defend an etiological theory of biological functions (according to which the proper function of a trait is the effect for which it was selected by natural selection) against three objections which have been influential. I argue, contrary to Millikan, that it is wrong to base our defense of the theory on a rejection of conceptual analysis, for conceptual analysis does have an important role in philosophy of science. I also argue that biology requires a normative notion (...) of a "proper function", and that a normative notion is not ahistorical. (shrink)

The etiological approach to ‘proper functions’ in biology can be strengthened by relating it to Robert Cummins' general treatment of function ascription. The proper functions of a biological trait are the functions it is assigned in a Cummins-style functional explanation of the fitness of ancestors. These functions figure in selective explanations of the trait. It is also argued that some recent etiological theories include inaccurate accounts of selective explanation in biology. Finally, a generalization of the notion of selective explanation allows (...) an analysis of the proper functions of human artifacts. (shrink)

Biological functions are dispositions or effects a trait has which explain the recent maintenance of the trait under natural selection. This is the "modern history" approach to functions. The approach is historical because to ascribe a function is to make a claim about the past, but the relevant past is the recent past; modern history rather than ancient.

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)

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.

I defend the historical definition of "function" originally given in my Language, Thought and Other Biological Categories (1984a). The definition was not offered in the spirit of conceptual analysis but is more akin to a theoretical definition of "function". A major theme is that nonhistorical analyses of "function" fail to deal adequately with items that are not capable of performing their functions.

The paper presents an extended argument for the claim that mental content impacts the computational individuation of a cognitive system (section 2). The argument starts with the observation that a cognitive system may simultaneously implement a variety of different syntactic structures, but that the computational identity of a cognitive system is given by only one of these implemented syntactic structures. It is then asked what are the features that determine which of implemented syntactic structures is the computational structure of the (...) system, and it is contended that these features are certain aspects of mental content. The argument helps (section 3) to reassess the thesis known as computational externalism, namely, the thesis that computational theories of cognition make essential reference to features in the individual's environment. It is suggested that the familiar arguments for computational externalism?which rest on thought experiments and on exegesis of Marr's theories of vision?are unconvincing, but that they can be improved. A reconstruction of the visex/audex thought experiment is offered in section 3.1. An outline of a novel interpretation of Marr's theories of vision is presented in section 3.2. The corrected arguments support the claim that computational theories of cognition are intentional. Computational externalism is still pending, however, upon the thesis that psychological content is extrinsic. (shrink)

Through the use of such "folk" concepts as belief, desire, intention, and expectation, Daniel Dennett asserts in this first full scale presentation of...

Relativism, roughly put, is the view that truth and falsity, right and wrong, standards of reasoning, and procedures of justification are products of differing conventions and frameworks of assessment and that their authority is confined to the context giving rise to them. More precisely, ‘relativism’ covers views which maintain that—at a level of high abstraction—at least some class of things have properties they have not simpliciter, but only relative to a given framework of assessment, and correspondingly, that the truth of (...) claims attributing these properties holds only once the relevant framework of assessment is specified or supplied. Relativists characteristically insist, furthermore, that if something is only relatively so, then there can be no framework-independent vantage point from which the matter of whether the thing in question is so can be established. Relativism has been, in its various guises, both one of the most popular and most reviled philosophical doctrines of our time. Defenders see it as a harbinger of tolerance and the only ethical and epistemic stance worthy of the open-minded and tolerant. Detractors dismiss it for its alleged incoherence and uncritical intellectual permissiveness. Debates about relativism permeate the whole spectrum of philosophical sub-disciplines. From ethics to epistemology, science to religion, political theory to ontology, theories of meaning and even logic, philosophy has felt the need to respond to this heady and seemingly subversive idea. Discussions of relativism often also invoke considerations relevant to the very nature and methodology of philosophy and to the division between the so-called ‘analytic and continental’ camps in philosophy. And yet, despite a long history of debate going back to Plato and a still developing large body of writing, it is still difficult to come to an agreed definition of what, at its core, relativism is, and what philosophical import it has. This entry attempts to provide a broad account of the many ways in which ‘relativism’ has been defined, explained, defended and criticized. (shrink)

ABSTRACT Shagrir and Sprevak explore the apparent necessity of representation for the individuation of digits in computational systems.1 1 I will first offer a response to Sprevak’s argument that does not mention Shagrir’s original formulation, which was more complex. I then extend my initial response to cover Shagrir’s argument, thus demonstrating that it is possible to individuate digits in non-representational computing mechanisms. I also consider the implications that the non-representational individuation of digits would have for the broader theory of computing (...) mechanisms. 1 The Received View: No Computation without Representation 2 Computing Mechanisms and Functional Individuation 3 Against Computational Externalism 4 Implications for the Mechanistic Account. (shrink)

In this paper, I assess recent claims in philosophy of science about scientific perspectivism being compatible with realism. I clarify the rationale for scientific perspectivism and the problems and challenges that perspectivism faces in delivering a form of realism. In particular, I concentrate my attention on truth, and on ways in which truth can be understood in perspectival terms. I offer a cost-benefit analysis of each of them and defend a version that in my view is most promising in living (...) up to realist expectations. (shrink)

Philosophers of science typically associate the causal‐mechanical view of scientific explanation with the work of Railton and Salmon. In this paper I shall argue that the defects of this view arise from an inadequate analysis of the concept of mechanism. I contrast Salmon’s account of mechanisms in terms of the causal nexus with my own account of mechanisms, in which mechanisms are viewed as complex systems. After describing these two concepts of mechanism, I show how the complex‐systems approach avoids certain (...) objections to Salmon’s account of causal‐mechanical explanation. I conclude by discussing how mechanistic explanations can provide understanding by unification. (shrink)

Philosophers of science typically associate the causal-mechanical view of scientific explanation with the work of Railton and Salmon. In this paper I shall argue that the defects of this view arise from an inadequate analysis of the concept of mechanism. I contrast Salmon's account of mechanisms in terms of the causal nexus with my own account of mechanisms, in which mechanisms are viewed as complex systems. After describing these two concepts of mechanism, I show how the complex-systems approach avoids certain (...) objections to Salmon's account of causal-mechanical explanation. I conclude by discussing how mechanistic explanations can provide understanding by unification. (shrink)

In the book, I argue that the mind can be explained computationally because it is itself computational—whether it engages in mental arithmetic, parses natural language, or processes the auditory signals that allow us to experience music. All these capacities arise from complex information-processing operations of the mind. By analyzing the state of the art in cognitive science, I develop an account of computational explanation used to explain the capacities in question.

The claim that similarity plays a role in representation has been philosophically discredited. Psychologists, however, routinely analyse the success of mental representations for guiding behaviour in terms of a similarity between representation and the world. I provide a foundation for this practice by developing a philosophically responsible account of the relationship between similarity and representation in natural systems. I analyse similarity in terms of the existence of a suitable homomorphism between two structures. The key insight is that by restricting attention (...) to only those homomorphisms induced by causal processes, we can solve two philosophical problems with a single assumption. First, causal structure provides an adequate source for the bias required to ensure the similarity relation is non-trivial; second, it provides an adequate source for the directionality required to move from similarity to representation. I defend this account against objections by Goodman and van Fraassen and demonstrate that it is indeed the account of similarity’s role in representation assumed by psychological practice. (shrink)

The title of The Rediscovery of the Mind suggests the question "When was the mind lost?" Since most people may not be aware that it ever was lost, we must also then ask "Who lost it?" It was lost, of course, only by philosophers, by certain philosophers. This passed unnoticed by society at large. The "rediscovery" is also likely to pass unnoticed. But has the mind been rediscovered by the same philosophers who "lost" it? Probably not. John Searle is an (...) analytic philosopher, with some of the same notions as the positivists and behaviorists who rejected consciousness and "lost" the mind in the first place, but he also does not sound like the kind of reductionist who would have joined that crowd. His views, indeed, are sensible enough, and some of his insights so important, that it is a shame to find his thought profoundly limited by some of the same mistakes and prejudices that ruined philosophy, and not just philosophy of mind, under the influence of those positivists and behaviorists. There is enough of genuine value in his treatment, that it can easily be taken up and, with relatively slight modification, added to what is of permanent value in the history of philosophy. (shrink)

Certain lines of reasoning common in evolutionary taxonomy have been termed viciously circular. They are quite obviously not logically circular. They do give the superficial appearance of epistemological circularity. This appearance arises from the method of successive approximation used by evolutionary taxonomists. It is argued that this method is not epistemologically circular, even when the only evidence that the taxonomist has to go on is the phenetic similarity of contemporary forms. The important criticism of evolutionary taxonomy is rather that in (...) the absence of fossil evidence phyletic reconstructions are not warranted. It is argued that this charge stems initially from a misunderstanding of the kind of certainty possible in empirical science. When this criticism is couched in appropriate terms, it may be seen to have some force. Many phyletic inferences are not as warranted as one might wish. However, there is a great deal of difference between arguing that a line of reasoning is unwarranted and arguing that it is viciously circular. (shrink)

Gualtiero Piccinini articulates and defends a mechanistic account of concrete, or physical, computation. A physical system is a computing system just in case it is a mechanism one of whose functions is to manipulate vehicles based solely on differences between different portions of the vehicles according to a rule defined over the vehicles. Physical Computation discusses previous accounts of computation and argues that the mechanistic account is better. Many kinds of computation are explicated, such as digital vs. analog, serial vs. (...) parallel, neural network computation, program-controlled computation, and more. Piccinini argues that computation does not entail representation or information processing although information processing entails computation. Pancomputationalism, according to which every physical system is computational, is rejected. A modest version of the physical Church-Turing thesis, according to which any function that is physically computable is computable by Turing machines, is defended. (shrink)

NOW IN PAPERBACK"€"Starting from a collection of simple computer experiments"€"illustrated in the book by striking computer graphics"€"Stephen Wolfram shows how their unexpected results force a whole new way of looking at the operation of our universe.

I aim to show how and why some definitions can be benignly circular. According to Lloyd Humberstone, a definition that is analytically circular need not be inferentially circular and so might serve to illuminate the application-conditions for a concept. I begin by tidying up some problems with Humberstone's account. I then show that circular definitions of a kind commonly thought to be benign have inferentially circular truth-conditions and so are malign by Humberstone's test. But his test is too demanding. The (...) inferences we actually use to establish the applicability of, e.g., colour concepts are designed to establish warranted assertability and not truth. Understood thus, dispositional analyses are not inferentially circular. (shrink)

Computationalism about the brain is the view that the brain literally performs computations. For the view to be interesting, we need an account of computation. The most well-developed account of computation is Turing Machine computation, the account provided by theoretical computer science which provides the basis for contemporary digital computers. Some have thought that, given the seemingly-close analogy between the all-or-nothing nature of neural spikes in brains and the binary nature of digital logic, neural computation could be a species of (...) digital computation. A few recent authors have offered arguments against this idea; here, I review recent findings in neuroscience that further cement the implausibility of this view. However, I argue that we can retain the view that the brain is a computer if we expand what we mean by “computation” to include analog computation. I articulate an account of analog computation as the manipulation of analog representations based on previous work on the difference between analog and non-analog representations, extending a view originally articulated in Shagrir :271–279, 2010). Given that analog computation constitutes a significant chapter in the history of computation, this revision of computationalism to include analog computation is not an ad hoc addition. Brains may well be computers, but of the analog kind, rather than the digital kind. (shrink)

I examine a major objection to the mechanistic view of concrete computation, stemming from an apparent tension between the abstract nature of computational explanation and the tenets of the mechanistic framework: while computational explanation is medium-independent, the mechanistic framework insists on the importance of providing some degree of structural detail about the systems target of the explanation. I show that a common reply to the objection, i.e. that mechanistic explanation of computational systems involves only weak structural constraints, is not enough (...) to save the standard mechanistic view of computation—it trivialises the appeal to mechanism, and thus makes the account collapse into a purely functional view. I claim, however, that the objection can be put to rest once the account is appropriately amended: computational individuation is indeed functional, while mechanistic explanation plays a role in accounting for computational implementation. Since individuation and implementation are crucial elements in a satisfying account of computation in physical systems, mechanism keeps its central importance in the theory of concrete computation. Finally, I argue that my version of the mechanistic view helps to provide a convincing reply to a powerful objection against non-semantic theories of concrete computation: the argument from the multiplicity of computations. (shrink)

For the claim that the satisfaction of certain conditions is sufficient for the application of some concept to serve as part of the (`reductive') analysis of that concept, we require the conditions to be specified without employing that very concept. An account of the application conditions of a concept not meeting this requirement, we call analytically circular. For such a claim to be usable in determining the extension of the concept, however, such circularity may not matter, since if the concept (...) figures in a certain kind of intensional context in the specification of the conditions, the satisfaction of those conditions may not itself depend on the extension of the concept. We put this by saying that although analytically circular, the account may yet not be inferentially circular. (shrink)

The aim of this work is to apply information theoretic ideas to the notion of fundamentality. I will argue that if one adopts pancomputationalism as a metaphysics for the universe, then there are higher-level structures which are just as fundamental for computation as anything from microphysics.

A key component of scientific inquiry, especially inquiry devoted to developing mechanistic explanations, is delineating the phenomenon to be explained. The task of delineating phenomena, however, has not been sufficiently analyzed, even by the new mechanistic philosophers of science. We contend that Marr’s characterization of what he called the computational level provides a valuable resource for understanding what is involved in delineating phenomena. Unfortunately, the distinctive feature of Marr’s computational level, his dual emphasis on both what is computed and why (...) it is computed, has not been appreciated in philosophical discussions of Marr. Accordingly we offer a distinctive account of CL. This then allows us to develop two important points about delineating phenomena. First, the accounts of phenomena that figure in explanatory practice are typically not qualitative but precise, formal or mathematical, representations. Second, delineating phenomena requires consideration of the demands the environment places on the mechanism—identifying, as Marr put it, the basis of the computed function in the world. As valuable as Marr’s account of CL is in characterizing phenomena, we contend that ultimately he did not go far enough. Determining the relevant demands of the environment on the mechanism often requires detailed empirical investigation. Moreover, often phenomena are reconstituted in the course of inquiry on the mechanism itself. (shrink)