Eric Margolis

Would an innate Approximate Number System (ANS) vindicate number concept nativism? A natural and widely assumed way to approach this question is to suppose that the answer turns on whether the ANS’s representations are conceptual—if they are, this would support number concept nativism, but if they aren’t, then an innate ANS wouldn’t provide any support for number concept nativism. As tempting as this approach may be, this chapter argues that it is mistaken. Whether an innate ANS supports number concept nativism doesn’t turn on whether its representations are concepts—or on there being any innate number concepts at all.

This chapter examines the question of whether there is an essential connection between language and number, while looking more broadly at some of the potential innate precursors to the acquisition of the positive integers. It focuses on the theoretical question of how language may figure in an account of the ontogeny of the positive integers. Despite the trend in developmental psychology to suppose that it does, there are actually few detailed accounts on offer. Two exceptions are examined — two theories that give natural language a prominent role to play and that represent the state of the art in the study of mathematical cognition. The first is owing to C. R. Gallistel, Rochel Gelman, and their colleagues; the second to Elizabeth Spelke and her colleagues. Although both accounts are rich and innovative, they face a range of serious objections, in particular, their appeal to language isn't helpful.

This chapter examines Gordon's study and its implications for theories of numerical concepts. Gordon's data was collected among the Pirahã tribe of the Brazilian Amazon, who have no words for precise numerical quantities. The data appear to show that the Pirahã are also incapable of precise numerical thought, and this has been widely taken to undermine strong nativism and support the claim that exact numerical thought is dependent upon natural language. It is argued that there are many important flaws in Gordon's study which prevent us from drawing any inferences at all regarding the numerical abilities of the Pirahã or the dependence of thought on language. Hence, there is nothing in Gordon's study that could undermine strong nativism or support linguistic determinism.

Many psychologists think that concepts should be understood on analogy with the terms of scientific theories, yet the significance of this claim has always been obscure. In this paper, I clarify the psychological content of the theory analogy, focusing on influential pieces by Susan Carey. Once plainly put, the analogy amounts to the view that a mental representation has its semantical properties by virtue of its role in a restricted knowledge structure. One of the commendable things about Carey's work is that, unlike many other psychologists who appeal to the theory analogy, she takes seriously the need to specify how these structures are constrained. At the same time, the constraints she offers are insufficient. Her account also faces challenges from recent work in the semantics of natural kind terms.

Can an atomistic theory of concepts accommodate concept learning? The standard assumption is no: without internal structure, there are no semantic constituents for learning to assemble. This paper challenges that assumption. I develop an acquisition model for natural kind concepts within an atomistic, information-based semantic framework. The key is the notion of a sustaining mechanism—the inferential apparatus that links a concept to its worldly property. I argue that children's essentialist dispositions and perceptual heuristics for natural kinds provide the resources to construct such mechanisms through experience with exemplars, delivering a learning model rather than a mere triggering account.

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 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

A standard view within psychology is that there have been two important shifts in the study of concepts and that each has led to some improvements. The first shift was from the classical theory of concepts to probabilistic theories, including the prototype theory. The second shift was from probabilistic theories to theory-based theories. In this article, I critically evaluate the view that the first shift was a major advance and argue that the prototype theory suffers some of the same problems that have been thought to challenge the classical theory.

Strong nativist views about numerical concepts claim that human beings have at least some innate precise numerical representations. Weak nativist views claim only that humans, like other animals, possess an innate system for representing approximate numerical quantity. We present a new strong nativist model of the origins of numerical concepts and defend the strong nativist approach against recent cross-cultural studies that have been interpreted to show that precise numerical concepts are dependent on language and that they are restricted to speakers of languages with the right kind of structure.

In LOT 2: The Language of Thought Revisited, Jerry Fodor argues that concept learning of any kind—even for complex concepts—is simply impossible. In order to avoid the conclusion that all concepts, primitive and complex, are innate, he argues that concept acquisition depends on purely noncognitive biological processes. In this paper, we show (1) that Fodor fails to establish that concept learning is impossible, (2) that his own biological account of concept acquisition is unworkable, and (3) that there are in fact many promising general models for explaining how concepts are learned.

This chapter provides a critical overview of ten central arguments that philosophers have given in support of a distinction between the conceptual and the nonconceptual. We use these arguments to examine the question of whether (and in what sense) perceptual states might be deemed nonconceptual and also whether (and in what sense) animals and infants might be deemed to lack concepts. We argue that philosophers have implicitly relied on a wide variety of different ways to draw the conceptual/nonconceptual distinction and that all ten of the arguments we discuss face considerable difficulties.

In a survey of his views in the philosophy of mind, David Lewis criticizes much recent work in the field by attacking an imaginary opponent, Strawman. His case against Strawman focuses on four central theses which Lewis takes to be widely accepted among contemporary philosophers of mind. These theses concern (1) the language of thought hypothesis and its relation to folk psychology, (2) narrow content, (3) de se content, and (4) rationality. We respond to Lewis, arguing that he underestimates Strawman’s theoretical resources in a variety of important ways.

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..

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.