Online research in philosophy

Quite unexpectedly, cognitive psychologists find their field intimately connected to a whole new intellectual landscape that had previously seemed remote, unfamiliar, and all but irrelevant. Yet the proliferating connections tying together the cognitive and evolutionary communities promise to transform both fields, with each supplying necessary principles, methods, and a species of rigor that the other lacks. (Cosmides and Tooby, 1994, p. 85).

There is an argument that has recently been deployed in favor of thinking that the mind is mostly (or even exclusively) composed of cognitive modules; an argument that draws from some ideas and concepts of evolutionary and of developmental biology. In a nutshell, the argument concludes that a mind that is massively composed of cognitive mechanisms that are cognitively modular (henceforth, c-modular) is more evolvable than a mind that is not c-modular (or that is scarcely c-modular), since a cognitive mechanism that is c-modular is likely to be biologically modular (henceforth, b-modular), and b-modular characters are more evolvable (e.g., Sperber 2002, Carruthers 2005). In evolutionary biology, the evolvability of a character in an organism is understood as the “organism’s capacity to facilitate the generation of non-lethal selectable phenotypic variation from random mutation” with respect to that character. Here I will argue that the notion of cognitive modularity needed to make this argument plausible will have to be understood in terms of the biological notion of variational independence; that is, it will have to be understood in such a way that a cognitive feature is c-modular only if few or no other morphological changes (cognitive and not) are significantly correlated with variations of that feature arising in members of the relevant population. I will also argue that all –except for (possibly) one—of the connotations contained in a cluster of notions of cognitive modularity widely accepted in some of the mainstream currents of thought in classical cognitive science, are simply irrelevant to the argument. In order to argue for this, I will have to examine the question as to whether there are any strong theoretical connections between (1) those connotations and (2) notions of modularity accepted in biology, specially in evolutionary and in developmental biology, that are thought to be most relevant to arguments to the effect that biological modularity enhances evolvability.

The standard view of classical cognitive science stated that cognition consists in the manipulation of language-like structures according to formal rules. Since cognition is ‘linguistic’ in itself, according to this view language is just a complex communication system and does not influence cognitive processes in any substantial way. This view has been criticized from several perspectives and a new framework (Embodied Cognition) has emerged that considers cognitive processes as non-symbolic and heavily dependent on the dynamical interactions between the cognitive system and its environment. But notwithstanding the successes of the embodied cognitive science in explaining low-level cognitive behaviors, it is still not clear whether and how it can scale up for explaining high-level cognition. In this paper we argue that this can be done by considering the role of language as a cognitive tool: i.e. how language transforms basic cognitive functions in the high-level functions that are characteristic of human cognition. In order to do that, we review some computational models that substantiate this view with respect to categorization and memory. Since these models are based on a very rudimentary form of non-syntactic ‘language’ we argue that the use of language as a cognitive tool might have been an early discovery in hominid evolution, and might have played a substantial role in the evolution of language itself.

Thirty years ago, grounded cognition had roots in philosophy, perception, cognitive linguistics, psycholinguistics, cognitive psychology, and cognitive neuropsychology. During the next 20 years, grounded cognition continued developing in these areas, and it also took new forms in robotics, cognitive ecology, cognitive neuroscience, and developmental psychology. In the past 10 years, research on grounded cognition has grown rapidly, especially in cognitive neuroscience, social neuroscience, cognitive psychology, social psychology, and developmental psychology. Currently, grounded cognition appears to be achieving increased acceptance throughout cognitive science, shifting from relatively minor status to increasing importance. Nevertheless, researchers wonder whether grounded mechanisms lie at the heart of the cognitive system or are peripheral to classic symbolic mechanisms. Although grounded cognition is currently dominated by demonstration experiments in the absence of well-developed theories, the area is likely to become increasingly theory driven over the next 30 years. Another likely development is the increased incorporation of grounding mechanisms into cognitive architectures and into accounts of classic cognitive phenomena. As this incorporation occurs, much functionality of these architectures and phenomena is likely to remain, along with many original mechanisms. Future theories of grounded cognition are likely to be heavily influenced by both cognitive neuroscience and social neuroscience, and also by developmental science and robotics. Aspects from the three major perspectives in cognitive science—classic symbolic architectures, statistical/dynamical systems, and grounded cognition—will probably be integrated increasingly in future theories, each capturing indispensable aspects of intelligence.

In earlier works, I have argued that it is useful to think of much scientific activity, particularly in experimental sciences, as involving the operation of distributed cognitive systems, as these are understood in the contemporary cognitive sciences. Introducing a notion of distributed cognition, however, invites consideration of whether, or in what way, related cognitive activities, such as knowing, might also be distributed. In this paper I will argue that one can usefully introduce a notion of distributed cognition without attributing other cognitive attributes, such as knowing, let alone having a mind or being conscious, to distributed cognitive systems. I will first briefly introduce the cognitive science understanding of distributed cognition, partly so as to distinguish full-blown distributed cognition from mere collective cognition.1.

Traditional views separate cognitive processes from sensory–motor processes, seeing cognition as amodal, propositional, and compositional, and thus fundamentally different from the processes that underlie perceiving and acting. These were the ideas on which cognitive science was founded 30 years ago. However, advancing discoveries in neuroscience, cognitive neuroscience, and psychology suggests that cognition may be inseparable from processes of perceiving and acting. From this perspective, this study considers the future of cognitive science with respect to the study of cognitive development.

This article draws out an epistemological tension implicit in Cosmides and Tooby's conception of evolutionary psychology. Cosmides and Tooby think of the mind as a collection of functionally individuated, domain-specific modules. Although they do not explicitly deny the existence of domain-general processes, it will be shown that their methodology commits them to the assumption that only domain-specific cognitive processes are capable of producing useful outputs. The resultant view limits the scope of biologically possible cognitive accomplishments and these limitations, it will be argued, are such as to deny us epistemic capacities that evolutionary psychology presupposes in its pursuit of an objective, comprehensive account of human nature.

When Fodor titled his (1983) book the _Modularity of Mind_, he overstated his position. His actual view is that the mind divides into systems some of which are modular and others of which are not. The book would have been more aptly, if less provocatively, called _The Modularity of Low-Level Peripheral Systems_. High-level perception and cognitive systems are non-modular on Fodor’s theory. In recent years, modularity has found more zealous defenders, who claim that the entire mind divides into highly specialized modules. This view has been especially popular among Evolutionary Psychologists. They claim that the mind is massively modular (Cosmides and Tooby, 1994; Sperber, 1994; Pinker, 1997; see also Samuels, 1998). Like a Swiss Army Knife, the mind is an assembly of specialized tools, each of which has been designed for some particular purpose. My goal here is to raise doubts about both peripheral modularity and massive modularity. To do that, I will rely on the criteria for modularity laid out by Fodor (1983). I will argue that neither input systems, nor central systems are modular on any of these criteria.

Prominent evolutionary psychologists have argued that our innate psychological endowment consists of numerous domainspecific cognitive resources, rather than a few domaingeneral ones. In the light of some conceptual clarification, we examine the central inprinciple arguments that evolutionary psychologists mount against domaingeneral cognition. We conclude (a) that the fundamental logic of Darwinism, as advanced within evolutionary psychology, does not entail that the innate mind consists exclusively, or even massively, of domainspecific features, and (b) that a mixed innate cognitive economy of domainspecific and domaingeneral resources remains a genuine conceptual possibility. However, an examination of evolutionary psychology's 'grain problem' reveals that there is no way of establishing a principled and robust distinction between domainspecific and domaingeneral features. Nevertheless, we show that evolutionary psychologists can and do live with this grain problem without their whole enterprise being undermined.

Introduction: toward an understanding of embodied cognition -- Standard cognitive science -- Challenging standard cognitive science -- Conceptions of embodiment -- Embodied cognition: the conceptualization hypothesis -- Embodied cognition: the replacement hypothesis -- Embodied cognition: the constitution hypothesis -- Concluding thoughts.