Eric Margolis

The human mind is capable of entertaining an astounding range of thoughts. These thoughts are composed of concepts or ideas, which are the building blocks of thoughts. This book is about where all of these concepts come from and the psychological structures that ultimately account for their acquisition. We argue that the debate over the origins of concepts, known as the rationalism-empiricism debate, has been widely misunderstood—not just by its critics but also by researchers who have been active participants in the debate. Part I fundamentally rethinks the foundations of the debate. Part II defends a rationalist view of the origins of concepts according to which many concepts across many conceptual domains are either innate or acquired via rationalist learning mechanisms. Our case is built around seven distinct arguments, which together form a large-scale inference to the best explanation argument for our account. Part III then defends this account against the most important empiricist objections and alternatives. Finally, Part IV argues against an extreme but highly influential rationalist view—Jerry Fodor’s infamous view that it is impossible to learn new concepts and his related radical concept nativism, which holds that essentially all lexical concepts are innate. Throughout the book, our discussion blends philosophical and theoretical reflection with consideration of a broad range of empirical work drawn from many different disciplines studying the mind, providing a thorough update to the rationalism-empiricism debate in philosophy and cognitive science and a major new rationalist account of the origins of concepts. [An open access title available under the terms of a CC BY-NC-ND 4.0 licence]

The notion of domain specificity plays a central role in some of the most important debates in cognitive science. Yet, despite the widespread reliance on domain specificity in recent theorizing in cognitive science, this notion remains elusive. Critics have claimed that the notion of domain specificity can't bear the theoretical weight that has been put on it and that it should be abandoned. Even its most steadfast proponents have highlighted puzzles and tensions that arise once one tries to go beyond an initial intuitive sketch of what domain specificity involves. In this paper, we address these concerns head on by developing an account of what it means for a cognitive mechanism to be domain specific that overcomes the obstacles that have made domain specificity seem so problematic. We then apply this understanding of domain specificity to one of the key debates that it has figured prominently in—the rationalism-empiricism debate concerning the origins of cognitive traits—and introduce several related theoretical notions that work alongside domain specificity in helping to clarify what makes a view more (or less) rationalist. This example illustrates how the notion of domain specificity can, and should, continue to play a central role in ongoing debates in cognitive science.

Fiona Cowie's book What's Within: Nativism Reconsidered offers an important critical assessment of nativist views of the mind. She provides an account of what nativism consists in, and discusses prominent nativist views of concept acquisition and language acquisition. In the latter case, she also offers an empiricist alternative to Chomskyan nativist accounts, and claims that the main arguments for an innate language faculty—one that embodies Universal Grammar—don't work. We provide an overview of her position, focusing mostly on her views about natural language, and argue that she has underestimated the power the poverty of the stimulus argument and consequently has underestimated the advantages of nativist models of language acquisition.

I argue that the human mind includes an innate domain-specific system for representing precise small numerical quantities. This theory contrasts with object-tracking theories and with domain-general theories that only make use of mental models. I argue that there is a good amount of evidence for innate representations of small numerical quantities and that such a domain-specific system has explanatory advantages when infants’ poor working memory is taken into account. I also show that the mental models approach requires previously unnoticed domain-specific structure and consequently that there is no domain-general alternative to an innate domain-specific small number system.

How do people decide what category an artifact belongs to? Previous studies have suggested that adults and, to some degree, children, categorize artifacts in accordance with the design stance, a categorization system which privileges the designer’s original intent in making categorization judgments. However, these studies have all been conducted in Western, technologically advanced societies, where artifacts are mass produced. In this study, we examined intuitions about artifact categorization among the Shuar, a hunter-horticulturalist society in the Amazon region of Ecuador. We used a forced-choice method similar to previous studies, but unlike these studies, our scenarios involved artifacts that would be familiar to the Shuar. We also incorporated a community condition to examine the possible effect of community consensus on how artifacts are categorized. The same scenarios were presented to university student participants in the UK. Across populations and conditions, participants tended to categorize artifacts in terms of a creator’s intent as opposed to a differing current use. This lends support to the view that the design stance may be a universal feature of human cognition. However, we conclude with some thoughts on the limitations of the present method for studying artifact concepts.

Where do human numerical abilities come from? This article is a commentary on Leibovich et al.’s “From 'sense of number' to 'sense of magnitude' —The role of continuous magnitudes in numerical cognition”. Leibovich et al. argue against nativist views of numerical development by noting limitations in newborns’ vision and limitations regarding newborns’ ability to individuate objects. I argue that these considerations do not undermine competing nativist views and that Leibovich et al.'s model itself presupposes that infant learners have numerical representations.

The topic of this thesis is the nature of human concepts understood as mental symbols or representations. ;Many discussions in this area presuppose an inferential model of concepts taken together with what I call the standard model of concept learning. An inferential model of concepts says that a concept's identity depends upon its participating in inferential dispositions linking it to certain other concepts. For example, one might think that part of what makes a mental symbol the concept BIRD is that it participates in an inferential disposition linking it to the concept ANIMAL. The standard model of concept learning says that learning a concept involves assembling it from previously available concepts. For example, one might think that the concept BIRD is learned by putting together the concept ANIMAL with concepts like WING, FLIES, and so on, yielding a more complex structure. The standard model of concept learning presupposes a form of the inferential model of concepts. Thus one of the reasons many people endorse the inferential model is that they are committed to a broadly empiricist picture of the mind; they assume that most concepts are learned, so they must also assume that most concepts have the sort of structure that the model presupposes. ;My thesis challenges both of these points with respect to a class of concept that has been of central interest in philosophy and cognitive science, namely, the lexical concepts . I argue that the independent evidence for the inferential model in this case is no good and consequently that the standard model of concept learning doesn't work. Still, it remains plausible that many lexical concepts are learned. What we need are new learning models, ones that depart in significant ways from the standard model. I end the thesis by outlining a proposal that may work for the natural kind concepts

Radical concept nativism is the thesis that virtually all lexical concepts are innate. Notoriously endorsed by Jerry Fodor (1975, 1981), radical concept nativism has had few supporters. However, it has proven difficult to say exactly what’s wrong with Fodor’s argument. We show that previous responses are inadequate on a number of grounds. Chief among these is that they typically do not achieve sufficient distance from Fodor’s dialectic, and, as a result, they do not illuminate the central question of how new primitive concepts are acquired. To achieve a fully satisfactory response to Fodor’s argument, one has to juxtapose questions about conceptual content with questions about cognitive development. To this end, we formulate a general schema for thinking about how concepts are acquired and then present a detailed illustration.

Conceptual analysis is undergoing a revival in philosophy, and much of the credit goes to Frank Jackson. Jackson argues that conceptual analysis is needed as an integral component of so-called serious metaphysics and that it also does explanatory work in accounting for such phenomena as categorization, meaning change, communication, and linguistic understanding. He even goes so far as to argue that opponents of conceptual analysis are implicitly committed to it in practice. We show that he is wrong on all of these points and that his case for conceptual analysis doesn't succeed. At the same time, we argue that the sorts of intuitions that figure in conceptual analysis may still have a significant role to play in philosophy. So naturalists needn't disregard intuitions altogether.

The philosophy of cognitive science is concerned with fundamental philosophical and theoretical questions connected to the sciences of the mind. How does the brain give rise to conscious experience? Does speaking a language change how we think? Is a genuinely intelligent computer possible? What features of the mind are innate? Advances in cognitive science have given philosophers important tools for addressing these sorts of questions; and cognitive scientists have, in turn, found themselves drawing upon insights from philosophy--insights that have often taken their research in novel directions. The Oxford Handbook of Philosophy of Cognitive Science brings together twenty-one newly commissioned chapters by leading researchers in this rich and fast-growing area of philosophy. It is an indispensible resource for anyone who seeks to understand the implications of cognitive science for philosophy, and the role of philosophy within cognitive science.

Theories of number concepts often suppose that the natural numbers are acquired as children learn to count and as they draw an induction based on their interpretation of the first few count words. In a bold critique of this general approach, Rips, Asmuth, Bloomfield [Rips, L., Asmuth, J. & Bloomfield, A.. Giving the boot to the bootstrap: How not to learn the natural numbers. Cognition, 101, B51–B60.] argue that such an inductive inference is consistent with a representational system that clearly does not express the natural numbers and that possession of the natural numbers requires further principles that make the inductive inference superfluous. We argue that their critique is unsuccessful. Provided that children have access to a suitable initial system of representation, the sort of inductive inference that Rips et al. call into question can in fact facilitate the acquisition of larger integer concepts without the addition of any further principles.

Hilary Putnam's Twin Earth thought experiment has come to have an enormous impact on contemporary philosophical thought. But while most of the discussion has taken place within the context of the philosophy of mind and language, Terence Horgan and Mark Timmons (H8cT) have defended the intriguing suggestion that a variation on the original thought experiment has important consequences for ethics.' In a series of papers, they' ve developed the idea of a Moral Twin Earth and have argued that its significance is that it has the resources to undermine naturalistic versions of moral realism.' H8t T don't hold back in their assessment. "Moral Twin..

Conceptual structures are commonly likened to scientific theories, yet the content and motivation of the theory analogy are rarely discussed. Gregory Murphy and Douglas Medin's The Role of Theories in Conceptual Coherence is a notable exception and has become an authoritative exposition of the utility of the theory analogy. For Murphy and Medin, the theory analogy solves what they call the problem of conceptual coherence or the problem of conceptual glue. I argue that they conflate a number of issues under these rubrics and that in each case either the problem to be solved isn't subject to a general solution or the theory analogy is of little use. The issues I consider are: (1) what makes a concept efficient, useful, and informative, (2) what makes a concept refer to what it does, (3) what makes a set of objects form a single category, and (4) what makes concepts combine in one way rather than another

This chapter offers a high-level overview of the philosophy of cognitive science and an introduction to the Oxford Handbook of Philosophy of Cognitive Science. The philosophy of cognitive science emerged out of a set of common and overlapping interests among philosophers and scientists who study the mind. We identify five categories of issues that illustrate the best work in this broad field: (1) traditional philosophical issues about the mind that have been invigorated by research in cognitive science, (2) issues regarding the practice of cognitive science and its foundational assumptions, (3) issues regarding the explication and clarification of core concepts in cognitive science, (4) first-order empirical issues where philosophers participate in the interdisciplinary investigation of particular psychological phenomena, (5) traditional philosophical issues that aren’t about the mind but that can be informed by a better understanding of how the mind works.

We examine a proposal for dealing with perhaps the chief difficulty facing holistic theories of meaning—meaning instability. The problem is that, given a robust holism, small changes in a representational system are likely to lead to meaning changes throughout the system. Consequently, different individuals are likely never to mean the same thing. Eric Lormand suggests that holists can avoid this problem—and even secure more stability than non-holists—by positing that symbols have multiple meanings. We argue that the proposal doesn't work, however, since multiple meanings are unstable for much the same reason that single meanings are.

Concepts: Core Readings traces the develoment of one of the most active areas of investigation in cognitive science. This comprehensive volume brings together the essential background readings on concepts from philosophy, psychology, and linguistics, while providing a broad sampling of contemporary research. The first part of the book centers around the fall of the Classical Theory of Concepts in the face of attacks by W.V.O. Quine, Ludwig Wittgenstein, Eleanor Rosch, and others, emphasizing the emergence and development of the Prototype Theory and the controversies it spurred. The second part surveys a broad range of contemporary theories—Neoclassical Theories, the Prototype Theory, the Theory-Theory, and Conceptual Atomism.

Noam Chomsky's Poverty of the Stimulus Argument is one of the most famous and controversial arguments in the study of language and the mind. Though widely endorsed by linguists, the argument has met with much resistance in philosophy. Unfortunately, philosophical critics have often failed to fully appreciate the power of the argument. In this paper, we provide a systematic presentation of the Poverty of the Stimulus Argument, clarifying its structure, content, and evidential base. We defend the argument against a variety of philosophical criticisms, new and old, and argue that the Poverty of the Stimulus Argument continues to deserve its guiding role in the study of language and the mind.

Given the fundamental role that concepts play in theories of cognition, philosophers and cognitive scientists have a common interest in concepts. Nonetheless, there is a great deal of controversy regarding what kinds of things concepts are, how they are structured, and how they are acquired. This chapter offers a detailed high-level overview and critical evaluation of the main theories of concepts and their motivations. Taking into account the various challenges that each theory faces, the chapter also presents a novel approach to concepts that is organized around two ideas. The first is a pluralistic view of differing types of conceptual structure. The second is a model that treats concepts as atomic representations that are linked to various types of conceptual structures.

What is a concept? Philosophers have given many different answers to this question, reflecting a wide variety of approaches to the study of mind and language. Nonetheless, at the most general level, there are two dominant frameworks in contemporary philosophy. One proposes that concepts are mental representations, while the other proposes that they are abstract objects. This paper looks at the differences between these two approaches, the prospects for combining them, and the issues that are involved in the dispute. We argue that powerful motivations have been offered in support of both frameworks. This suggests the possibility of combining the two. Unlike Frege, we hold that the resulting position is perfectly coherent and well worth considering. Nonetheless, we argue that it should be rejected along with the view that concepts are abstract objects.

One of the most important abilities we have as humans is the ability to think about number. In this chapter, we examine the question of whether there is an essential connection between language and number. We provide a careful examination of two prominent theories according to which concepts of the positive integers are dependent on language. The first of these claims that language creates the positive integers on the basis of an innate capacity to represent real numbers. The second claims that language’s function is to integrate contents from modules that humans share with other animals. We argue that neither model is successful.