I challenge the dominant understanding of what it means to say two thoughts are associated. The two views that dominate the current literature treat association as a kind of mechanism that drives sequences of thought. The first, which I call reductive associationism, treats association as a kind of neural mechanism. The second treats association as a feature of the kind of psychological mechanism associative processing. Both of these views are inadequate. I argue that association should instead be seen as a (...) highly abstract filler term, standing in for causal relations between representational states in a system. Associations, so viewed, could be implemented by many different mechanisms. I outline the role that this view gives associative models as part of a top-down characterization of psychological processes of any kind and of any complexity. (shrink)

There are two roles that association played in 18th–19th century associationism. The first dominates modern understanding of the history of the concept: association is a causal link posited to explain why ideas come in the sequence they do. The second has been ignored: association is merely regularity in the trains of thought, and the target of explanation. The view of association as regularity arose in several forms throughout the tradition, but Thomas Brown (1778–1820) makes the distinction explicit. He argues that (...) there is no associative link, and association is mere sequence. I trace this view of association through the tradition, and consider its implications: Brown's views, in particular, motivate a rethinking of the associationist tradition in psychology. Associationism was a project united by a shared explanandum phenomenon, rather than a theory united by a shared theoretical posit. (shrink)

In Rules and Representations, first published in 1980, Noam Chomsky lays out many of the concepts that have made his approach to linguistics and human cognition so instrumental to our understanding of language.Chomsky arrives at his well-known position that there is a universal grammar, structured in the human mind and common to all human languages. Based on Chomsky's 1978 Woodbridge Lectures, this edition contains revised versions of the lectures and two new essays.

The book from which these sections are excerpted is concerned with the prospects for assimilating the study of human intelligence and its products to the natural sciences through the investigation of cognitive structures, understood as systems of rules and representations that can be regarded as “mental organs.” These mental structui′es serve as the vehicles for the exercise of various capacities. They develop in the mind on the basis of an innate endowment that permits the growth of rich and highly articulated (...) structures along an intrinsically determined course under the triggering and partially shaping effect of experience, which fixes parameters in an intricate system of predetermined form. It is argued that the mind is modular in character, with a diversity of cognitive structures, each with its specific properties arid principles. Knowledge of language, of the behavior of objects, and much else crucially involves these mental structures, and is thus not characterizable in terms of capacities, dispositions, or practical abilities, nor is it necessarily grounded in experience in the standard sense of this term.Various types of knowledge and modes of knowledge acquisition are discussed in these terms. Some of the properties of the language faculty are investigated. The basic cognitive relation is “knowing a grammar”; knowledge of language is derivative and, correspondingly, raises further problems. Language as commonly understood is not a unitary phenomenon but involves a number of interacting systems: the “computational” system of grammar, which provides the representations of sound and meaning that permit a rich range of expressive potential, is distinct from a conceptual system with its own properties; knowledge of language must be distinguished from knowledge of how to use a language; and the various systems that enter into the knowledge and use of language must be further analyzed into their specific subcomponents. (shrink)

Our prominent definitions of cognition are too vague and lack empirical grounding. They have not kept up with recent developments, and cannot bear the weight placed on them across many different debates. I here articulate and defend a more adequate theory. On this theory, behaviors under the control of cognition tend to display a cluster of characteristic properties, a cluster which tends to be absent from behaviors produced by non-cognitive processes. This cluster is reverse-engineered from the empirical tests that comparative (...) psychologists use to determine whether a behavior was generated by a cognitive or a non-cognitive process. Cognition should be understood as the natural kind of psychological process that non-accidentally exhibits the properties assessed by these tests (as well as others we have not yet discovered). Finally, I review two plausible neural accounts of cognition's underlying mechanisms?one based in localization of function to particular brain regions and another based in the more recent distributed networks approach to neuroscience?which would explain why these properties non-accidentally cluster. While this notion of cognition may be useful for a number of debates, I here focus on its application to a recent crisis over the distinction between cognition and association in comparative psychology. (shrink)

Our prominent definitions of cognition are too vague and lack empirical grounding. They have not kept up with recent developments, and cannot bear the weight placed on them across many different debates. I here articulate and defend a more adequate theory. On this theory, behaviors under the control of cognition tend to display a cluster of characteristic properties, a cluster which tends to be absent from behaviors produced by non-cognitive processes. This cluster is reverse-engineered from the empirical tests that comparative (...) psychologists use to determine whether a behavior was generated by a cognitive or a non-cognitive process. Cognition should be understood as the natural kind of psychological process that non-accidentally exhibits the properties assessed by these tests (as well as others we have not yet discovered). Finally, I review two plausible neural accounts of cognition's underlying mechanisms—one based in localization of function to particular brain regions and another based in the more recent distributed networks approach to neuroscience—which would explain why these properties non-accidentally cluster. While this notion of cognition may be useful for a number of debates, I here focus on its application to a recent crisis over the distinction between cognition and association in comparative psychology. (shrink)

Much research in the last two decades has demonstrated that human responses deviate from the performance deemed normative according to various models of decision making and rational judgment (e.g., the basic axioms of utility theory). This gap between the normative and the descriptive can be interpreted as indicating systematic irrationalities in human cognition. However, four alternative interpretations preserve the assumption that human behavior and cognition is largely rational. These posit that the gap is due to (1) performance errors, (2) computational (...) limitations, (3) the wrong norm being applied by the experimenter, and (4) a different construal of the task by the subject. In the debates about the viability of these alternative explanations, attention has been focused too narrowly on the modal response. In a series of experiments involving most of the classic tasks in the heuristics and biases literature, we have examined the implications of individual differences in performance for each of the four explanations of the normative/descriptive gap. Performance errors are a minor factor in the gap; computational limitations underlie non-normative responding on several tasks, particularly those that involve some type of cognitive decontextualization. Unexpected patterns of covariance can suggest when the wrong norm is being applied to a task or when an alternative construal of the task should be considered appropriate. Key Words: biases; descriptive models; heuristics; individual differences; normative models; rationality; reasoning. (shrink)

Distinctions have been proposed between systems of reasoning for centuries. This article distills properties shared by many of these distinctions and characterizes the resulting systems in light of recent findings and theoretical developments. One system is associative because its computations reflect similarity structure and relations of temporal contiguity. The other is "rule based" because it operates on symbolic structures that have logical content and variables and because its computations have the properties that are normally assigned to rules. The systems serve (...) complementary functions and can simultaneously generate different solutions to a reasoning problem. The rule-based system can suppress the associative system but not completely inhibit it. The article reviews evidence in favor of the distinction and its characterization. (shrink)

‘Morgan's canon’ is a rule for making inferences from animal behaviour about animal minds, proposed in 1892 by the Bristol geologist and zoologist C. Lloyd Morgan, and celebrated for promoting scepticism about the reasoning powers of animals. Here I offer a new account of the origins and early career of the canon. Built into the canon, I argue, is the doctrine of the Oxford philologist F. Max Müller that animals, lacking language, necessarily lack reason. Restoring the Müllerian origins of the (...) canon in turn illuminates a number of changes in Morgan's position between 1892 and 1894. I explain these changes as responses to the work of the American naturalist R. L. Garner. Where Morgan had a rule for interpreting experiments with animals, Garner had an instrument for doing them: the Edison cylinder phonograph. Using the phonograph, Garner claimed to provide experimental proof that animals indeed spoke and reasoned. (shrink)

The past 50 years have seen an accumulation of evidence suggesting that associative learning depends on high-level cognitive processes that give rise to propositional knowledge. Yet, many learning theorists maintain a belief in a learning mechanism in which links between mental representations are formed automatically. We characterize and highlight the differences between the propositional and link approaches, and review the relevant empirical evidence. We conclude that learning is the consequence of propositional reasoning processes that cooperate with the unconscious processes involved (...) in memory retrieval and perception. We argue that this new conceptual framework allows many of the important recent advances in associative learning research to be retained, but recast in a model that provides a firmer foundation for both immediate application and future research. (shrink)

The overwhelming majority of those who theorize about implicit biases posit that these biases are caused by some sort of association. However, what exactly this claim amounts to is rarely specified. In this paper, I distinguish between different understandings of association, and I argue that the crucial senses of association for elucidating implicit bias are the cognitive structure and mental process senses. A hypothesis is subsequently derived: if associations really underpin implicit biases, then implicit biases should be modulated by counterconditioning (...) or extinction but should not be modulated by rational argumentation or logical interventions. This hypothesis is false; implicit biases are not predicated on any associative structures or associative processes but instead arise because of unconscious propositionally structured beliefs. I conclude by discussing how the case study of implicit bias illuminates problems with popular dual-process models of cognitive architecture. (shrink)

Working memory limits are best defined in terms of the complexity of the relations that can be processed in parallel. Complexity is defined as the number of related dimensions or sources of variation. A unary relation has one argument and one source of variation; its argument can be instantiated in only one way at a time. A binary relation has two arguments, two sources of variation, and two instantiations, and so on. Dimensionality is related to the number of chunks, because (...) both attributes on dimensions and chunks are independent units of information of arbitrary size. Studies of working memory limits suggest that there is a soft limit corresponding to the parallel processing of one quaternary relation. More complex concepts are processed by or In segmentation, tasks are broken into components that do not exceed processing capacity and can be processed serially. In conceptual chunking, representations are to reduce their dimensionality and hence their processing load, but at the cost of making some relational information inaccessible. Neural net models of relational representations show that relations with more arguments have a higher computational cost that coincides with experimental findings on higher processing loads in humans. Relational complexity is related to processing load in reasoning and sentence comprehension and can distinguish between the capacities of higher species. The complexity of relations processed by children increases with age. Implications for neural net models and theories of cognition and cognitive development are discussed. (shrink)

It is not rare in philosophy and psychology to see theorists fall into dichotomous thinking about mental phenomena. On one side of the dichotomy there are processes that I will label “unintelligent.” These processes are thought to be unconscious, implicit, automatic, unintentional, involuntary, procedural, and non-cognitive. On the other side, there are “intelligent” processes that are conscious, explicit, controlled, intentional, voluntary, declarative, and cognitive. Often, if a process or behavior is characterized by one of the features from either of the (...) above lists, the process or behavior is classified as falling under the category to which the feature belongs. For example, if a process is implicit this is usually considered sufficient for classifying it as “unintelligent” and for assuming that the remaining features that fall under the “unintelligent” grouping will apply to it as well. Accordingly, if a process or behavior is automatic, philosophers often consider it to be unintelligent. It is my goal in this paper to challenge the conceptual slip from “automatic” to “unintelligent”. I will argue that there are a whole range of properties highlighted by the existing psychological literature that make automaticity a much more complex phenomenon than is usually appreciated. I will then go on to discuss two further important relationships between automatic processes and controlled processes that arise when we think about automatic processes in the context of skilled behavior. These interactions should add to our resistance to classifying automaticity as unintelligent or mindless. In Sect. 1, I present a few representative cases of philosophers classifying automatic processes and behaviors as mindless or unintelligent. In Sect. 2, I review trends in the psychology of automaticity in order highlight a complex set of features that are characteristic, though not definitive, of automatic processes and behaviors. In Sect. 3, I argue that at least some automatic processes are likely cognitively penetrable. In Sect. 4, I argue that the structure of skilled automatic processes is shaped diachronically by practice, training and learning. Taken together, these considerations should dislodge the temptation to equate “automatic” with “unintelligent”. (shrink)

This paper explores the difference between Connectionist proposals for cognitive a r c h i t e c t u r e a n d t h e s o r t s o f m o d e l s t hat have traditionally been assum e d i n c o g n i t i v e s c i e n c e . W e c l a i m t h a t t h (...) e m a j o r d i s t i n c t i o n i s t h a t , w h i l e b o t h Connectionist and Classical architectures postulate representational mental states, the latter but not the former are committed to a symbol-level of representation, or to a ‘language of thought’: i.e., to representational states that have combinatorial syntactic and semantic structure. Several arguments for combinatorial structure in mental representations are then reviewed. These include arguments based on the ‘systematicity’ of mental representation: i.e., on the fact that cognitive capacities always exhibit certain symmetries, so that the ability to entertain a given thought implies the ability to entertain thoughts with semantically related contents. We claim that such arguments make a powerful case that mind/brain architecture is not Connectionist at the cognitive level. We then consider the possibility that Connectionism may provide an account of the neural (or ‘abstract neurological’) structures in which Classical cognitive architecture is implemented. We survey a n u m b e r o f t h e s t a n d a r d a r g u m e n t s t h a t h a v e b e e n o f f e r e d i n f a v o r o f Connectionism, and conclude that they are coherent only on this interpretation. (shrink)

I had intended this review not specifically as a criticism of Skinner's speculations regarding language, but rather as a more general critique of behaviorist (I would now prefer to say "empiricist") speculation as to the nature of higher mental processes. My reason for discussing Skinner's book in such detail was that it was the most careful and thoroughgoing presentation of such speculations, an evaluation that I feel is still accurate. Therefore, if the conclusions I attempted to substantiate in the review (...) are correct, as I believe they are, then Skinner's work can be regarded as, in effect, a reductio ad absurdum of behaviorist assumptions. My personal view is that it is a definite merit, not a defect, of Skinner's work that it can be used for this purpose, and it was for this reason that I tried to deal with it fairly exhaustively. I do not see how his proposals can be improved upon, aside from occasional details and oversights, within the framework of the general assumptions that he accepts. I do not, in other words, see any way in which his proposals can be substantially improved within the general framework of behaviorist or neobehaviorist, or, more generally, empiricist ideas that has dominated much of modern linguistics, psychology, and philosophy. The conclusion that I hoped to establish in the review, by discussing these speculations in their most explicit and detailed form, was that the general point of view was largely mythology, and that its widespread acceptance is not the result of empirical support, persuasive reasoning, or the absence of a plausible alternative. (shrink)