This article argues for the explanatory autonomy of psychology drawing on cases from the multilevel modeling practice. This is done by considering a multilevel linear model in personality and social psychology, and discussing its philosophical implications for the reductionism debate in philosophy of psychology. I argue that this practice challenges the reductionist position in philosophy of psychology, and supports the explanatory autonomy of psychology.

Since the cognitive revolution, it has become commonplace that cognition involves both computation and information processing. Is this one claim or two? Is computation the same as information processing? The two terms are often used interchangeably, but this usage masks important differences. In this paper, we distinguish information processing from computation and examine some of their mutual relations, shedding light on the role each can play in a theory of cognition. We recommend that theorists of cognition be explicit and careful (...) in choosing notions of computation and information and connecting them together.Keywords: Computation; Information processing; Computationalism; Computational theory of mind; Cognitivism. (shrink)

This paper aims to address the relevance of the natural sciences for transcendental phenomenology, that is, the issue of naturalism. The first section distinguishes three varieties of naturalism and corresponding forms of naturalization: an ontological one, a methodological one, and an epistemological one. In light of these distinctions, in the second section, I examine the main projects aiming to “naturalize phenomenology”: neurophenomenology, front-loaded phenomenology, and formalized approaches to phenomenology. The third section then considers the commitments of Husserl’s transcendental phenomenology with (...) respect to the three varieties of naturalism previously discussed. I argue that Husserl rejected strong and weak forms of epistemological naturalism, strong methodological naturalism, and ontological naturalism. The fourth section presents the argument that Husserl endorsed a weak, conditional form of methodological naturalism. This point is illustrated with Husserl’s proposal of “somatology,” a natural science apt to study the corporeality of the lived body. The final section addresses the complementarity and respective limits of the transcendental phenomenological and the natural scientific frameworks. I argue that, on Husserl’s account, the function of transcendental phenomenology with respect to the natural sciences is to provide them with an epistemological foundation and an ontological clarification. I suggest that certain natural sciences can be understood, within the transcendental phenomenological framework, as “sciences of constitution,” that is, as sciences investigating the contribution of real structures acting as conditions of possibility for the occurrence of certain kinds of comprehensive unities in lived experience. (shrink)

An influential thesis in contemporary philosophy of mind is that subjectivity is best conceived as inner awareness of qualia. has argued that this unique subjective awareness generates a paradox which resists empirical explanation. On account of this “paradox of subjective duality,” Levine concludes that the hardest part of the hard problem of consciousness is to explain how anything like a subjective point of view could arise in the world. Against this, I argue that the nature of subjective thought is not (...) correctly characterized as inner awareness, that a non-paradoxical approach to the first-person perspective is available, and that the problem about subjectivity should be distinguished from the perennial problem of qualia or phenomenal properties. (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)

This paper presents the results of training an artificial neural network (ANN) to classify moral situations. The ANN produces a similarity space in the process of solving its classification problem. The state space is subjected to analysis that suggests that holistic approaches to interpreting its functioning are problematic. The idea of a contributory or pro tanto standard, as discussed in debates between moral particularists and generalists, is used to understand the structure of the similarity space generated by the ANN. A (...) spectrum of possibilities for reasons, from atomistic to holistic, is discussed. Reasons are understood as increasing in nonlocality as they move away from atomism. It is argued that contributory standards could be used to understand forms of nonlocality that need not go all the way to holism. It is also argued that contributory standards may help us to understand the kind of similarity at work in analogical reasoning and argument in ethics. Some objections to using state space approaches to similarity are dealt with, as are objections to using empirical and computational work in philosophy. (shrink)

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)

Contrary to common views that philosophy is extraneous to cognitive science, this paper argues that philosophy has a crucial role to play in cognitive science with respect to generality and normativity. General questions include the nature of theories and explanations, the role of computer simulation in cognitive theorizing, and the relations among the different fields of cognitive science. Normative questions include whether human thinking should be Bayesian, whether decision making should maximize expected utility, and how norms should be established. These (...) kinds of general and normative questions make philosophical reflection an important part of progress in cognitive science. Philosophy operates best, however, not with a priori reasoning or conceptual analysis, but rather with empirically informed reflection on a wide range of findings in cognitive science. (shrink)

According to Marr, a computational-level theory consists of two elements, the what and the why . This article highlights the distinct role of the Why element in the computational analysis of vision. Three theses are advanced: ( a ) that the Why element plays an explanatory role in computational-level theories, ( b ) that its goal is to explain why the computed function (specified by the What element) is appropriate for a given visual task, and ( c ) that the (...) explanation consists in showing that the functional relations between the representing cells are similar to the “external” mathematical relations between the entities that these cells represent. *Received September 2009; revised January 2010. †To contact the author, please write to: Departments of Philosophy and Cognitive Science, The Hebrew University, Jerusalem 91905, Israel; e-mail: [email protected]. (shrink)

It appears that consciousness science is progressing soundly, in particular in its search for the neural correlates of consciousness. There are two main approaches to this search, one is content-based (focusing on the contrast between conscious perception of, e.g., faces vs. houses), the other is state-based (focusing on overall conscious states, e.g., the contrast between dreamless sleep vs. the awake state). Methodological and conceptual considerations of a number of concrete studies show that both approaches are problematic: the content-based approach seems (...) to set aside crucial aspects of consciousness; and the state-based approach seems over-inclusive in a way that is hard to rectify without losing sight of the crucial conscious-unconscious contrast. Consequently, the search for the neural correlates of consciousness is in need of new experimental paradigms. (shrink)

Computationalism has been the mainstream view of cognition for decades. There are periodic reports of its demise, but they are greatly exaggerated. This essay surveys some recent literature on computationalism. It concludes that computationalism is a family of theories about the mechanisms of cognition. The main relevant evidence for testing it comes from neuroscience, though psychology and AI are relevant too. Computationalism comes in many versions, which continue to guide competing research programs in philosophy of mind as well as psychology (...) and neuroscience. Although our understanding of computationalism has deepened in recent years, much work in this area remains to be done. (shrink)

Cognitive science is the interdisciplinary investigation of mind and intelligence, embracing psychology, neuroscience, anthropology, artificial intelligence, and philosophy. There are many important philosophical questions related to this investigation, but this short chapter will focus on the following three. What is the nature of the explanations and theories developed in cognitive science? What are the relations among the five disciplines that comprise cognitive science? What are the implications of cognitive science research for general issues in the philosophy of science? I will (...) argue that cognitive theories and explanations depend on representations of mechanisms and that the relations among the five disciplines, especially psychology and neuroscience, depend on relations between kinds of mechanisms. These conclusions have implications for central problems in general philosophy of science such as the nature of theories, explanations, and reduction between theories at different levels. (shrink)

Over the past thirty years, it is been common to hear the mind likened to a digital computer. This essay is concerned with a particular philosophical view that holds that the mind literally is a digital computer (in a specific sense of “computer” to be developed), and that thought literally is a kind of computation. This view—which will be called the “Computational Theory of Mind” (CTM)—is thus to be distinguished from other and broader attempts to connect the mind with computation, (...) including (a) various enterprises at modeling features of the mind using computational modeling techniques, and (b) employing some feature or features of production-model computers (such as the stored program concept, or the distinction between hardware and software) merely as a guiding metaphor for understanding some feature of the mind. This entry is therefore concerned solely with the Computational Theory of Mind (CTM) proposed by Hilary Putnam [1961] and developed most notably for philosophers by Jerry Fodor [1975, 1980, 1987, 1993]. The senses of ‘computer’ and ‘computation’ employed here are technical; the main tasks of this entry will therefore be to elucidate: (a) the technical sense of ‘computation’ that is at issue, (b) the ways in which it is claimed to be applicable to the mind, (c) the philosophical problems this understanding of the mind is claimed to solve, and (d) the major criticisms that have accrued to this view. (shrink)

This short note takes two quotations from Snooks’ recent editorial on neuroeducation and teases out some further details on the philosophy of neuroscience and neurophilosophy along with consideration of the implications of both for philosophy of education.

Scientific naturalism—the conception according to which the natural sciences, and possibly physics alone, set the limits of ontology and epistemology—is characterized by a strong monistic tendency. For this reason, all versions of scientific naturalism face the so-called “placement problem”, which concerns the features of the ordinary view of the world that, at least prima facie, do not fit into the scientific view of the world (think of consciousness, moral properties, free will, and intentionality). To address this problem, scientific naturalists use (...) three strategies: reductionism, eliminativism, and mysterianism—none of which, it is argued, produces satisfying results. Liberal naturalism opts instead for a pluralistic attitude in both ontology and epistemology but accepts a constraint according to which one should accept no entity or explanation that is incompatible with the scientific worldview. Liberal naturalism faces the “reconciliation problem”, which concerns the relationship between the scientific and the ordinary views of the world once one denies ontological and epistemological priority to either of them. Three strategies for addressing this problem are presented: according to the first, the ordinary worldview and the scientific world are categorically distinct; according to the second, the former emerges from the latter; according to the third, between them there is a relation of global supervenience. Other objections to liberal naturalism are finally presented and addressed. (shrink)

Embedded and embodied approaches to cognition urge that (1) complicated internal representations may be avoided by letting features of the environment drive behavior, and (2) environmental structures can play an enabling role in cognition, allowing prior cognitive processes to solve novel tasks. Such approaches are thus in a natural position to oppose the ‘thesis of linguistic structuring’: The claim that the ability to use language results in a wholesale recapitulation of linguistic structure in onboard mental representation. Prominent examples of researchers (...) adopting this critical stance include Andy Clark, Michael Wheeler, and Mark Rowlands. But is such opposition warranted? Since each of these authors advocate accounts of mental representation that are broadly connectionist, I survey research on formal language computation in artificial neural networks, and argue that results indicate a strong form of the linguistic structuring thesis is true: Internal representational systems recapitulate significant linguistic structure, even on a connectionist account of mental representation. I conclude by sketching how my conclusion can nonetheless be viewed as consistent with and complimentary to an embedded/embodied account of the role of linguistic structure in cognition. (shrink)

This paper proposes an account of the self as a multilevel system consisting of social, individual, neural, and molecular mechanisms. It argues that the functioning of the self depends on causal relations between mechanisms operating at different levels. In place of reductionist and holistic approaches to cognitive science, I advocate a method of multilevel interacting mechanisms. This method is illustrated by showing how self-concepts operate at several different levels.

Recent work in neurophilosophy has either made reference to the work of John Dewey or independently developed positions similar to it. I review these developments in order first to show that Dewey was indeed doing neurophilosophy well before the Churchlands and others, thereby preceding many other mid-twentieth century European philosophers’ views on cognition to whom many present day philosophers refer (e.g., Heidegger, Merleau-Ponty). I also show that Dewey’s work provides useful tools for evading or overcoming many issues in contemporary neurophilosophy (...) and philosophy of mind. In this introductory review, I distinguish between three waves among neurophilosophers that revolve around the import of evolution and the degree of brain-centrism. Throughout, I emphasize and elaborate upon Dewey’s dynamic view of mind and consciousness. I conclude by introducing the consciousness-as-cooking metaphor as an alternative to both the consciousness-as-digestion and consciousness-as-dancing metaphors. Neurophilosophical pragmatism—or neuropragmatism—recognizes the import of evolutionary and cognitive neurobiology for developing a science of mind and consciousness. However, as the cooking metaphor illustrates, a science of mind and consciousness cannot rely on the brain alone—just as explaining cooking entails more than understanding the gut—and therefore must establish continuity with cultural activities and their respective fields of inquiry. Neuropragmatism advances a new and promising perspective on how to reconcile the scientific and manifest images of humanity as well as how to reconstruct the relationship between science and the humanities. (shrink)

Current discussions on artificial intelligence, in both the theoretical and practical realms, contain a fundamental lack of clarity regarding the nature of artificial intelligence, perhaps due to the fact that the distinction between natural and artificial appears, at first sight, both intuitive and evident. Is AI something unnatural, non-human and therefore dangerous to humanity, or is it only a continuation of man’s natural tendency towards creativity? It is not surprising that from the philosophical point of view, this distinction is the (...) basic question that fundamentally affects all other considerations and conclusions pertaining to artificial intelligence. In this article, I would like to explain this difference and draw attention to some conclusions, which may result from a naturalistic perspective with regard to recent philosophical posthumanism. For this purpose, I present several examples of the natural–artificial distinction in the different fields of the philosophy of science and then discuss their implications for the problem of intelligence. Based on Dennett’s conception of intentionality and the naturalistic perspective, I demonstrate that besides the traditional conception, there is a non-anthropocentric evolutionary view in which the natural–artificial distinction disappears and it is possible to see a united process of intelligence creation. (shrink)

In recent years, several authors have debated about the justifiability of so-called scientific imperialism. To date, however, widespread disagreements remain regarding both the identification and the normative evaluation of scientific imperialism. In this paper, I aim to remedy this situation by making some conceptual distinctions concerning scientific imperialism and by providing a detailed assessment of the most prominent objections to it. I shall argue that these objections provide a valuable basis for opposing some instances of scientific imperialism, but do not (...) yield cogent reasons to think that scientific imperialism in general is objectionable or unjustified. I then highlight three wide-ranging implications of this result for the ongoing philosophical debate about the justifiability of scientific imperialism. (shrink)

An underlying assumption in computational approaches in cognitive and brain sciences is that the nervous system is an input–output model of the world: Its input–output functions mirror certain relations in the target domains. I argue that the input–output modelling assumption plays distinct methodological and explanatory roles. Methodologically, input–output modelling serves to discover the computed function from environmental cues. Explanatorily, input–output modelling serves to account for the appropriateness of the computed function to the explanandum information-processing task. I compare very briefly the (...) modelling explanation to mechanistic and optimality explanations, noting that in both cases the explanations can be seen as complementary rather than contrastive or competing. (shrink)

Our primary goal in this article is to discuss the cross-talk between biological and cultural factors that become manifested in the individual brain development, neural wiring, neurochemical homeostasis, and behavior. We will show that behavioral propensities are the product of both cultural and biological factors and an understanding of these interactive processes can provide deep insights into why people behave the way they do. This interdisciplinary perspective is offered in an effort to generate dialog and empirical work among scholars interested (...) in merging aspects of anthropology and neuroscience, and anticipates that biological and cultural anthropology converge. We discuss new theoretical developments, hypothesis-testing strategies, and cross-disciplinary methods of observation and data collection. We believe that the exigency of integrating anthropology and the neurosciences is indisputable and anthropology's role in an emerging interdisciplinary science of human behavior will be critical because its focus is, and has always been, on human biological and cultural systems. (shrink)

Philosophers have long been familiar with the contrast between predicates privado privado son las únicas características cualitativas realmente simples. Con base en que, después de todo, sus referentes externos admiten un análisis estructural, relacional, causal o funcional de algún tipo. En este artículo quiero adoptar un enfoque más general y más filosófico que los argumentos antireduccionistas evidenciando los problemas que generan con la filosofía de la ciencia; la neurociencia emergente y con la historia de la ciencia en general. Sus argumentos (...) carecen incluso de solidez con respecto a los estándares de la filosofía puramente analítica únicas características cualitativas realmente simples. Con base en que, después de todo, sus referentes externos admiten un análisis estructural, relacional, causal o funcional de algún tipo. En este artículo quiero adoptar un enfoque más general y más filosófico que los argumentos antireduccionistas evidenciando los problemas que generan con la filosofía de la ciencia; la neurociencia emergente y con la historia de la ciencia en general. Sus argumentos carecen incluso or concepts that denote “qualitative simples,” as opposed to predicates or concepts that denote or express “structural, relational, causal, or functional” features. The tendency has been to think of these two classes of properties as being ontologically quite different from each other. Some would insist that the features displayed in this private cognitive domain are the only genuinely simple qualitative features, on grounds that their external brethren all turn out to admit of a structural, relational, causal, or functional analysis of some kind after all. In this paper I wish to take a more general and more philosophical approach to the anti-reductionist arguments which run into trouble with the philosophy of science, with emerging neuroscience, and with the history of science generally. They lack integrity even by the standards of purely analytic philosophy. / Los filósofos conocen bien el contraste entre predicados o conceptos que denotan características “cualitativas simples”, a diferencia de predicados o conceptos que señalan características “estructurales, relacionales, causales o funcionales”. La tendencia ha sido pensar estas dos clases de propiedades como ontológicamente diferentes entre sí. Algunos insistirían en que las características que se muestran en este dominio cognitivo de solidez con respecto a los estándares de la filosofía puramente analítica. (shrink)