The development of computers as ‘mind tools’ has generated intriguing and provocative views about their potential human-like qualities. In this paper an attempt is made to explore the ‘real’ nature of computers by an examination of three widely different perspective, (1) the common-sense view of computers as tools; (2) the provocative view of computers as persons; and (3) the challenging view of computers as texts. In the course of the discussion an extended critique of the use of anthropomorphic terms in (...) relation to machines is conducted and the fundamental differences between human persons and machines is reasserted. (shrink)

The notion of a ‘symbol’ plays an important role in the disciplines of Philosophy, Psychology, Computer Science, and Cognitive Science. However, there is comparatively little agreement on how this notion is to be understood, either between disciplines, or even within particular disciplines. This paper does not attempt to defend some putatively ‘correct’ version of the concept of a ‘symbol.’ Rather, some terminological conventions are suggested, some constraints are proposed and a taxonomy of the kinds of issue that give rise to (...) disagreement is articulated. The goal here is to provide something like a ‘geography’ of the various notions of ‘symbol’ that have appeared in the various literatures, so as to highlight the key issues and to permit the focusing of attention upon the important dimensions. In particular, the relationship between ‘tokens’ and ‘symbols’ is addressed. The issue of designation is discussed in some detail. The distinction between simple and complex symbols is clarified and an apparently necessary condition for a system to be potentially symbol, or token bearing, is introduced. (shrink)

John Austin's masterpiece, How to Do Things with Words, was not just a contribution to philosophy; it has proven to be a major contribution to linguistics, one of the founding documents o pragmatics, the investigation of how we use words to accomplish various ends in the social world. Strangely, not much attention has been paid by philosophers — or by psychologists and linguists — to how we use words in private, you might say, to think. As Wittgenstein once noted, ‘It (...) is very noteworthy that what goes on in thinking practically never interests us.’. (shrink)

Genuine agents are able to engage in activity because they find it worth pursuing—because they care about it. In this respect, they differ from what might be called “mere intentional systems”: systems like chess-playing computers that exhibit merely goal-directed behavior mediated by instrumental rationality, without caring. A parallel distinction can be made in the domain of social activity: plural agents must be distinguished from plural intentional systems in that plural agents have cares and engage in activity because of those cares. (...) In this paper, I sketch an account of what it is for an individual to care about things in terms of her exhibiting a certain pattern of emotions. After extending this account to make sense of an individual's caring about other agents, I then show how a certain sort of emotional connectedness among a group of people can make intelligible the group's having cares and thereby constitute that group as a plural agent. Alternative accounts of social action, by ignoring the difference between mere intentional systems and genuine agents, and so by leaving out these emotional entanglements from their accounts of social action, thereby fail to capture a whole range of social phenomena involving plural agents. (shrink)

This paper problematizes the analogy that Hubert Dreyfus has presented between phenomenology and cognitive science. It argues that Dreyfus presents Merleau-Ponty''s modification of Husserl''s phenomenology in a misleading way. He ignores the idea of philosophy as a radical interrogation and self-responsibility that stems from Husserl''s work and recurs in Merleau-Ponty''s Phenomenology of Perception. The paper focuses on Merleau-Ponty''s understanding of the phenomenological reduction. It shows that his critical idea was not to restrict the scope of Husserl''s reductions but to study (...) the conditions of possibility for the thetic acts. Merleau-Ponty argued, following Husserl''s texts, that the thetic acts rest on the basis of primordial pre-thetic experience. This layer of experience cannot, by its nature, be explicated or clarified, but it can be questioned and unveiled. This is the recurrent task of phenomenological philosophy, as Merleau-Ponty understands it. (shrink)

It is argued, that theory sf signs, especially in the tradition of the great philosopher Charles Sanders Peirce (1839–1914) can inspire the study of central problems in the philosophy of biology. Three such problems are considered: (1) The nature of biology as a science, where a semiotically informed pluralistic approach to the theory of science is introduced. (2) The peculiarity of the general object of biology, where a realistic interpretation of sign- and information-concepts is required to see sign-processes as immanent (...) in nature. (3) The possibility of an artificial construction of life, hereby discussed as a conceptual problem in the present form of the artificial life project and its implied definition of life. (shrink)

What is required for one thing to be a reason for another? Must the reason, more precisely, be or involve a principle? In this essay I target the idea that justification via reasons of one's beliefs (e.g., epistemic or moral) requires that the 'justifying reasons' be or involve (substantive and significant) principles. I identify and explore some potential sources of a principles requirement, and conclude that none of them (i.e., the normative function of reasons, the abstract structure of reasons, the (...) universalizability constraint on [moral] reasons, and even the pragmatic considerations that attenuate 'real-world' reason-giving) mandate that reasons be principles. I then explore implications of this conclusion, and note especially the resultant and paradoxical permissibility of justifying reasons that manage to be lawlike (a sine qua non for justifying reasons) even while consisting of highly-detailed and situation-specific proposition sets, e.g., novel-length narratives. (shrink)

As we rapidly approach the 50th year of the much‐celebrated ‘cognitive revolution’, it is worth reflecting on its widespread impact on individual disciplines and areas of multidisciplinary endeavour. Of specific concern in this paper is the example of the influence of cognitivism's equation of mind and computer in education. Within education, this paper focuses on a particular area of concern to which both mind and computer are simultaneously central: educational technology. It examines the profound and lasting effect of cognitive science (...) on our understandings of the educational potential of information and communication technologies, and further argues that recent and multiple ‘signs of discontent’, ‘crises’ and even ‘failures’ in cognitive science and psychology should result in changes in these understandings. It concludes by suggesting new directions that educational technology research might take in the light of this crisis of cognitivsm. (shrink)

There is currently a debate over whether cognitive architecture is classical or connectionist in nature. One finds the following three comparisons between classical architecture and connectionist architecture made in the pro-connectionist literature in this debate: (1) connectionist architecture is neurally plausible and classical architecture is not; (2) connectionist architecture is far better suited to model pattern recognition capacities than is classical architecture; and (3) connectionist architecture is far better suited to model the acquisition of pattern recognition capacities by learning than (...) is classical architecture. If true, (1)–(3) would yield a compelling case against the view that cognitive architecture is classical, and would offer some reason to think that cognitive architecture may be connectionist. We first present the case for (1)–(3) in the very words of connectionist enthusiasts. We then argue that the currently available evidence fails to support any of (1)–(3). (shrink)

In this paper I assess the explanatory role of internal representations in connectionist models of cognition. Focusing on both the internal‘hidden’units and the connection weights between units, I argue that the standard reasons for viewing these components as representations are inadequate to bestow an explanatorily useful notion of representation. Hence, nothing would be lost from connectionist accounts of cognitive processes if we were to stop viewing the weights and hidden units as internal representations.

The emperor's new mind (hereafter Emperor) is an attempt to put forward a scientific alternative to the viewpoint of according to which mental activity is merely the acting out of some algorithmic procedure. John Searle and other thinkers have likewise argued that mere calculation does not, of itself, evoke conscious mental attributes, such as understanding or intentionality, but they are still prepared to accept the action the brain, like that of any other physical object, could in principle be simulated by (...) a computer. In Emperor I go further than this and suggest that the outward manifestations ofconscious mental activity cannot even be properly simulated by calculation. To support this view, I use various arguments to show that the results of mathematical insight, in particular, do not seem to be obtained algorithmically. The main thrust ofthis work, however, is to present an overview ofthe present state of physical understanding and to show that an important gap exists at the point where, quantum and classical physics meet, as well as to speculate on how the conscious brain might be taking advantage ofwhatever new physics is needed to fill this gap to achieve its nonalgorithmic effects. (shrink)

On a literal reading of `Computing Machinery and Intelligence'', Alan Turing presented not one, but two, practical tests to replace the question `Can machines think?'' He presented them as equivalent. I show here that the first test described in that much-discussed paper is in fact not equivalent to the second one, which has since become known as `the Turing Test''. The two tests can yield different results; it is the first, neglected test that provides the more appropriate indication of intelligence. (...) This is because the features of intelligence upon which it relies are resourcefulness and a critical attitude to one''s habitual responses; thus the test''s applicablity is not restricted to any particular species, nor does it presume any particular capacities. This is more appropriate because the question under consideration is what would count as machine intelligence. The first test realizes a possibility that philosophers have overlooked: a test that uses a human''s linguistic performance in setting an empirical test of intelligence, but does not make behavioral similarity to that performance the criterion of intelligence. Consequently, the first test is immune to many of the philosophical criticisms on the basis of which the (so-called) `Turing Test'' has been dismissed. (shrink)

I offer support for the view that physicalist theories of cognition don't reduce to neurophysiological theories. On my view, the mind-brain relationship is to be explained in terms of evolutionary forces, some of which tug in the direction of a reductionistic mind-brain relationship, and some of which which tug in the opposite direction. This theory of forces makes possible an anti-reductionist account of the cognitive mind-brain relationship which avoids psychophysical anomalism. This theory thus also responds to the complaint which arguably (...) lies behind the Churchlands' strongest criticisms of anti-reductionism — namely the complaint that anti-reductionists fail to supply principled explanations for the character of the mind-brain relationship. While lending support to anti-reductionism, the view defended here also insures a permanent place for mind-brain reduction as an explanatory ideal analogous to Newtonian inertial motion or Aristotelian natural motion. (shrink)

This study attempts to determine a correlation effect between people’s perception and awareness of the operationalization of artificial intelligence in their everyday lives and in the production, presentation, and publication of news media in the U.S. By looking at the effect individual characteristics may have on a person’s perception and awareness of AI operationalized for news media and looking at whether perception and/or awareness of AI operationalized in a person’s daily life affects their perception and awareness of AI operationalized for (...) news media, we seek to find correlation between these two factors. The research relies on Actor-network theory, the MAIN Model, and utilizes a convenience sample survey method using the MTurk participant platform. (shrink)

Cognition is not, and could not possibly be, entirely representational in character. There is also a phenomenal form of cognitive expression that registers the intrinsic properties of mental states themselves. Arguments against the reality of this intrinsic phenomenal dimension to mental experience have focused either on its supposed impossibility, or secondly, the non-appearance of any such qualities to introspection. This paper argues to the contrary, that the registration of cognitive state properties does take place independently of representational content; and necessarily (...) so, since it supports an independent function—self-management. Given the fact that unlike a computer, the brain must, of necessity, operate itself, it needs to be in touch with itself to do so. Intrinsic phenomenal forms of cognitive expression allow the brain to do just that by registering characteristics of the cognitive states themselves. Self-management might well prove to constitute the prime reason for the emergence of subjectivity itself. (shrink)

There is an enduring tension in thinking about the architecture of systems that select behaviours, including evolved organisms. One line of reasoning supports convergence in control systems and conversion of the values of all options into a common currency, in part because this seems the best or only way of trading off costs and benefits associated with outcomes of varying types. A competing consideration supports parallelism or other forms of fragmentation, because of inefficiencies associated with integration, and suspicion towards general-purpose (...) cognitive systems. In addition, recent neuroscience has given particular attention to the question of how partly independent ‘habit based’ and ‘planning based’ decision-systems might interact. The issues here are, at least in part, a special case of the more general integration versus parallelism tension. This tension provides a useful framework for thinking about the implementation of different kinds of sensitivity to risks of various types, the variety of mechanisms by means of which risk sensitivity might be modulated, and how risk might be traded off against other components of value or disincentive. I describe the tension, briefly survey some of the relevant empirical evidence, and conclude with tentative observations on the topic of risk. (shrink)

It is widely believed that neural elements interact by communicating messages. Neurons, or groups of neurons, are supposed to send packages of data with informational content to other neurons or to the body. Thus, behavior is traditionally taken to consist in the execution of commands or instructions sent by the nervous system. As a consequence, neural elements and their organization are conceived as literally embodying and transmitting representations that other elements must in some way read and conform to. In opposition (...) to this conception, growing approaches such as enactivism and ecological psychology hold that neurons are not in the business of representing. However, by insisting that neural causation is not of a representational kind, these anti-representationalist approaches seem to be left with only one rather implausible alternative, viz. that behavior is the result of nothing but basic physical causation such as push-pull forces. In this paper it is argued that a third form of causation—termed “modulation”—exists and is at work in the coordination of animal behavior. Modulation is the quasi-direct guidance of dynamical systems through specific yet emerging trajectories. By setting the constraints that coordinate the free interaction of multi-element systems, modulation influences without forcing nor representing goal states. The basic properties of modulatory causation are analyzed and shown to be present in some fundamental aspects of neural and bodily interaction. (shrink)

In this paper we examine the question of whether complexity-like explanations can be applied to the psychology of individuals, and its implications for the scope of complexity explanations of social phenomena. We start by outlining two representational-cum-computational models of the mind—a symbolic model and a networks or connectionist one—and their pros and cons. Based on this we then outline a radical, non-representational and non-computational alternative model that has been gaining ground recently, and which has significant affinities with complexity explanations in (...) social science. Deploying neo-Kantian considerations, we then argue that due to the discursivity, or conceptual dimension of our cognitive system, the radical alternative must be incorrect insofar as humans are concerned. Indeed, human psychology must involve, at least partly, a representational understanding of the sort provided by the symbolic model. Relatedly, we show how the discursiviry of human cognition complicates our psychology and makes it difficult to account for. Finally, we briefly address the question of how the complicated nature of individual psychology, implied by human discursivity, may affect complexity explanations of social behavior. (shrink)

Theories of cognition and theories of social practices and institutions have often each separately acknowledged the relevance of the other; but seldom have there been consistent and sustained attempts to synthesize these two areas within one explanatory framework. This is precisely what my dissertation aims to remedy. I propose that certain recent developments and themes in philosophy of mind and cognitive science, when understood in the right way, can explain the emergence and dynamics of social practices and institutions. Likewise, the (...) view I construct explains how social practices and institutions shape the character of cognition of their constituent agents. Moreover, I explain both cognitive and social agency under the single explanatory framework provided by Dynamic Systems Theory. Drawing upon the phenomenological tradition, "embodied, "extended", "embedded", "enactive", and "ecological" approaches to cognition, as well as the conceptual resources of Dynamic Systems Theory, I construct a theory of agency that sees cognitive and social agents as far-from-equilibrium, open, recursively self-maintenant dynamic systems. Depending on the specifics of concrete circumstances, such systems, which I call "Dynamic Embodied Agents", may develop and possess emergent capacities for error-detection, flexible learning, normative behavior, representation, self-reflection, various modes of pattern-recognition, a temporal sense of self, and even moral responsibility. Some such systems are also sensitive to perceived social influences ; while reciprocally constituting and causally affecting them. (shrink)

The recent development of the research field of Computing and Philosophy has triggered investigations into the theoretical foundations of computing and information. This thesis consists of two parts which are the result of studies in two areas of Philosophy of Computing and Philosophy of Information regarding the production of meaning and the value system with applications. The first part develops a unified dual-aspect theory of information and computation, in which information is characterized as structure, and computation is the information dynamics. (...) This enables naturalization of epistemology, based on interactive information representation and communication. In the study of systems modeling, meaning, truth and agency are discussed within the framework of the PI/PC unification. The second part of the thesis addresses the necessity of ethical judgment in rational agency illustrated by the problem of information privacy and surveillance in the networked society. The value grounds and socio-technological solutions for securing trustworthiness of computing are analyzed. Privacy issues clearly show the need for computing professionals to contribute to understanding of the technological mechanisms of Information and Communication Technology. The main original contribution of this thesis is the unified dual-aspect theory of computation/information. Semantics of information is seen as a part of the data-information-knowledge structuring, in which complex structures are self-organized by the computational processing of information. Within the unified model, complexity is a result of computational processes on informational structures. The thesis argues for the necessity of computing beyond the Turing-Church limit, motivated by natural computation, and wider by pancomputationalism and paninformationalism, seen as two complementary views of the same physical reality. Moreover, it follows that pancomputationalism does not depend on the assumption that the physical world on some basic level is digital. Contrary to many believes it is entirely compatible with dual quantum-mechanical computing. (shrink)

There is currently a debate over whether cognitive architecture is classical or connectionist in nature. One finds the following three comparisons between classical architecture and connectionist architecture made in the pro-connectionist literature in this debate: (1) connectionist architecture is neurally plausible and classical architecture is not; (2) connectionist architecture is far better suited to model pattern recognition capacities than is classical architecture; and (3) connectionist architecture is far better suited to model the acquisition of pattern recognition capacities by learning than (...) is classical architecture. If true, (1)-(3) would yield a compelling case against the view that cognitive architecture is classical, and would offer some reason to think that cognitive architecture may be connectionist. We first present the case for (1)-(3) in the very words of connectionist enthusiasts. We then argue that the currently available evidence fails to support any of (1)-(3). (shrink)

Many philosophers worry that the classical computational theory of mind (CTM) engenders epiphenomenalism. Building on Block’s (1990) discussion, I formulate a particularly troubling version of this worry. I then present a novel solution to CTM’s epiphenomenalist conundrum. I develop my solution within an interventionist theory of causal relevance. My solution departs substantially from orthodox versions of CTM. In particular, I reject the widespread picture of digital computation as formal syntactic manipulation.1.

Thomas Hobbes (1588-1679), whose current reputation rests largely on his political philosophy, was a thinker with wide ranging interests. In philosophy, he defended a range of materialist, nominalist, and empiricist views against Cartesian and Aristotelian alternatives. In physics, his work was influential on Leibniz, and lead him into disputes with Boyle and the experimentalists of the early Royal Society. In history, he translated Thucydides's History of the Peloponnesian War into English, and later wrote his own history of the Long Parliament. (...) In mathematics he was less successful, and is best remembered for his repeated unsuccessful attempts to square the circle. But despite that, Hobbes was a serious and prominent participant in the intellectual life of his time. (shrink)

Abstract In this paper we address three concepts that are much talked about in the animal robotics community. These concepts are (1) representations, (2) goals, and (3) minimal cognition. We want to distinguish between information as an objective commodity and representation as something which involves a user, i.e. a system which accesses and uses information. Information per se lies out there and exists independently of any system that makes use of it. Representations presuppose design and require a user. We want (...) to distinguish different kinds of purposive behaviour, which involve different notions of goals, which themselves appear to be different from the point of view of the agent, the designer and the naive observer. We want to try to define cognition in terms of the minimal criteria that would be acceptable in view of our definitions of representations and goals. We recognise that full?blown cognition may require ingredients other than those of minimal cognition. (shrink)

How to model meaning processes (semiosis) in artificial semiotic systems? Once all computer simulation becomes tantamount to theoretical simulation, involving epistemological metaphors of world versions, the selection and choice of models will dramatically compromise the nature of all work involving simulation. According to the pragmatic Peircean based approach, semiosis is an interpreter-dependent process that cannot be dissociated from the notion of a situated (and actively distributed) communicational agent. Our approach centers on the consideration of relevant properties and aspects of Peirce’s (...) pragmatic concept of semiotics. Upon developing this approach, we have no pretensions of our being able to present an exhaustive analysis of the differences between Peirce and other theoretical positions. Nevertheless, our contribution will serve to demonstrate how theorists contribute toward revealing certain fundamental ‘semiotic constraints’ that will be of interest and importance. (shrink)

Many activities in Cognitive Science involve complex computer models and simulations of both theoretical and real entities. Artificial Intelligence and the study of artificial neural nets in particular, are seen as major contributors in the quest for understanding the human mind. Computational models serve as objects of experimentation, and results from these virtual experiments are tacitly included in the framework of empirical science. Cognitive functions, like learning to speak, or discovering syntactical structures in language, have been modeled and these models (...) are the basis for many claims about human cognitive capacities. Artificial neural nets (ANNs) have had some successes in the field of Artificial Intelligence, but the results from experiments with simple ANNs may have little value in explaining cognitive functions. The problem seems to be in relating cognitive concepts that belong in the `top-down' approach to models grounded in the `bottom-up' connectionist methodology. Merging the two fundamentally different paradigms within a single model can obfuscate what is really modeled. When the tools (simple artificial neural networks) to solve the problems (explaining aspects of higher cognitive functions) are mismatched, models with little value in terms of explaining functions of the human mind are produced. The ability to learn functions from data-points makes ANNs very attractive analytical tools. These tools can be developed into valuable models, if the data is adequate and a meaningful interpretation of the data is possible. The problem is, that with appropriate data and labels that fit the desired level of description, almost any function can be modeled. It is my argument that small networks offer a universal framework for modeling any conceivable cognitive theory, so that neurological possibility can be demonstrated easily with relatively simple models. However, a model demonstrating the possibility of implementation of a cognitive function using a distributed methodology, does not necessarily add support to any claims or assumptions that the cognitive function in question, is neurologically plausible. (shrink)

The Principle of Semantic Compositionality (sometimes called Frege''s Principle) is the principle that the meaning of a (syntactically complex) whole is a function only of the meanings of its (syntactic) parts together with the manner in which these parts were combined. This principle has been extremely influential throughout the history of formal semantics; it has had a tremendous impact upon modern linguistics ever since Montague Grammars became known; and it has more recently shown up as a guiding principle for a (...) certain direction in cognitive science.Despite the fact that The Principle is vague or underspecified at a number of points — such as what meaning is, what counts as a part, what counts as a syntactic complex, what counts as combination — this has not stopped some people from viewing The Principle as obviously true, true almost by definition. And it has not stopped other people from viewing The Principle as false, almost pernicious in its effect. And some of these latter theorists think that it is an empirically false principle while others think of it as a methodologically wrong-headed way to proceed. (shrink)

This paper examines whether a classical model could be translated into a PDP network using a standard connectionist training technique called extra output learning. In Study 1, standard machine learning techniques were used to create a decision tree that could be used to classify 8124 different mushrooms as being edible or poisonous on the basis of 21 different Features (Schlimmer, 1987). In Study 2, extra output learning was used to insert this decision tree into a PDP network being trained on (...) the identical problem. An interpretation of the trained network revealed a perfect mapping from its internal structure to the decision tree, representing a precise translation of the classical theory to the connectionist model. In Study 3, a second network was trained on the mushroom problem without using extra output learning. An interpretation of this second network revealed a different algorithm for solving the mushroom problem, demonstrating that the Study 2 network was indeed a proper theory translation. (shrink)

When cognitive scientists apply computational theory to the problem of phenomenal consciousness, as many of them have been doing recently, there are two fundamentally distinct approaches available. Either consciousness is to be explained in terms of the nature of the representational vehicles the brain deploys; or it is to be explained in terms of the computational processes defined over these vehicles. We call versions of these two approaches _vehicle_ and _process_ theories of consciousness, respectively. However, while there may be space (...) for vehicle theories of consciousness in cognitive science, they are relatively rare. This is because of the influence exerted, on the one hand, by a large body of research which purports to show that the explicit representation of information in the brain and conscious experience are _dissociable_, and on the other, by the _classical_ computational theory of mind – the theory that takes human cognition to be a species of symbol manipulation. But two recent developments in cognitive science combine to suggest that a reappraisal of this situation is in order. First, a number of theorists have recently been highly critical of the experimental methodologies employed in the dissociation studies – so critical, in fact, it’s no longer reasonable to assume that the dissociability of conscious experience and explicit representation has been adequately demonstrated. Second, classicism, as a theory of human cognition, is no longer as dominant in cognitive science as it once was. It now has a lively competitor in the form of _connectionism; _and connectionism, unlike classicism, does have the computational resources to support a robust vehicle theory of consciousness. In this paper we develop and defend this connectionist vehicle theory of consciousness. It takes the form of the following simple empirical hypothesis: _phenomenal experience consists in the explicit_ _representation of information in neurally realized PDP networks_.. (shrink)

Cognitive science uses the notion of computational information processing to explain cognitive information processing. Some philosophers have argued that anything can be described as doing computational information processing; if so, it is a vacuous notion for explanatory purposes.An attempt is made to explicate the notions of cognitive information processing and computational information processing and to specify the relationship between them. It is demonstrated that the resulting notion of computational information processing can only be realized in a restrictive class of dynamical (...) systems called physical notational systems (after Goodman's theory of notationality), and that the systems generally appealed to by cognitive science-physical symbol systems-are indeed such systems. Furthermore, it turns out that other alternative conceptions of computational information processing, Fodor's (1975) Language of Thought and Cummins' (1989) Interpretational Semantics appeal to substantially the same restrictive class of systems. (shrink)

This is an amended version of material that first appeared in A. Clark, Microcognition: Philosophy, Cognitive Science, and Parallel Distributed Processing (MIT Press, Cambridge, MA, 1989), Ch. 1, 2, and 6. It appears in German translation in Metzinger,T (Ed) DAS LEIB-SEELE-PROBLEM IN DER ZWEITEN HELFTE DES 20 JAHRHUNDERTS (Frankfurt am Main: Suhrkamp. 1999).

In this paper I link two hitherto disconnected sets of results in the philosophy of emotions and explore their implications for the computational theory of mind. The argument of the paper is that, for just the same reasons that some computationalists have thought that cognition may be a natural kind, so the same can plausibly be argued of emotion. The core of the argument is that emotions are a representation-governed phenomenon and that the explanation of how they figure in behaviour (...) must as such be undertaken in those terms. I conclude with some interdisciplinary reflections in defence of the hypothesis that emotions might be more fundamental in the organization of behaviour than cognition; that, in effect, we may be emoters before we are cognizers . The aim of the paper is: (1) to introduce a number of promising results in philosophical and empirical emotion theory to a wider audience; and (2) to begin the task of organizing those results into a computational theoretical framework. (shrink)

In this paper I review some leading developments in the empirical theory of affect. I argue that (1) affect is a distinct perceptual representation governed system, and (2) that there are significant modular factors in affect. The paper concludes with the observation thatfeeler (affective perceptual system) may be a natural kind within cognitive science. The main purpose of the paper is to explore some hitherto unappreciated connections between the theory of affect and the computational theory of mind.

Several accounts of representation in cognitive systems have recently been proposed. These look for a theory that will establish how a representation comes to have a certain content, and how these representations are used by cognitive systems. Covariation accounts are unsatisfactory, as they make intelligent reasoning and cognition impossible. Cummins' interpretation-based account cannot explain the distinction between cognitive and non-cognitive systems, nor how certain cognitive representations appear to have intrinsic meaning. Cognitive systems can be defined as model-constructers, or systems that (...) use information from interpreted models as arguments in the functions they execute. An account based on this definition solves many of the problems raised by the earlier proposals. (shrink)

This paper addresses two methodological paths in Artificial Intelligence: the paths of Babbage and anti-Cartesianism. While those researchers who have followed the latter have attempted to reverse the Cartesian dictum according to which machines cannot think in principle, Babbage’s path, which has been partially neglected, implies that the replacement of humans—and not the creation of minds—should provide the foundation of AI. In view of the examined paths, the claim that we support here is this: in line with Babbage, AI researchers (...) have recently concentrated upon the replacement of human labour, and thus upon the creation of Machine Learning systems. After presenting and analysing the paths, we characterise Machine Learning via its developments and an illustrative example. Then, we put forward an argument that shows that total replacement of human labour will not be feasible for practical and conceptual reasons despite the successful developments in recent AI systems. Our discussion finally leads to optimism and awareness: AI’s advances allow humans to dedicate themselves to higher level tasks, but these advances also require that we be vigilant about the responsibilities granted to ML-based systems. (shrink)

The view that dominates the literature on intentional attitudes holds that beliefs and desires both have propositional content. A commitment to what I call “content uniformity” underlies this view. According to content uniformity, beliefs and desires are but different psychological modes having a uniform kind of content. Prima facie, the modes don’t place any constraint on the kinds of content the attitude can have. I challenge this consensus by pointing out an asymmetry between belief contents and desire contents which shows (...) content uniformity to be mistaken. I do this by revisiting the arguments of Richard (Philosophical Studies, 39(1): 1–13, 1981), and show that arguments which purport to show the temporal specificity of belief contents yield the opposite results for desire contents. I defend this preliminary conclusion from various strategies to neutralize the asymmetry claim. My defense provides occasions to respond to objections by Brogaard (2012) and Recanati (2007) to the Richard argument, and to get clearer on the role of temporal adjuncts in desire ascriptions. Finally, I consider whether the construal of attitude content as centered propositions (as in Lewis Philosophical Review, 88(4): 513–543, 1979) can be invoked to vindicate content uniformity. My conclusion is that while the framework itself doesn’t vindicate content uniformity, it could, but only if it availed itself of a further, substantive thesis about desire, which itself is in need of defense. (shrink)

I examine the following question: Do actions require representations that are intrinsic to the action itself? Recent work by Mark Rowlands, Michael Wheeler, and Andy Clark suggests that actions may require a minimal form of representation. I argue that the various concepts of minimal representation on offer do not apply to action per se and that a non‐representationalist account that focuses on dynamic systems of self‐organizing continuous reciprocal causation at the sub‐personal level is superior. I further recommend a scientific pragmatism (...) regarding the concept of representation. (shrink)

This paper considers the implications for higher education of recent work on narrative theory, distributed cognition and artificial intelligence. These perspectives are contrasted with the educational implications of Heidegger's ontological phenomenology [being‐there and being‐aware (Da‐sein)] and with the classic and classical foundations of education which Heidegger and Gadamer once criticised. The aim is to prompt discussion of what teaching might become if psychological insights (about collective minds let loose to learn) are associated with every realm of higher education (not just (...) teacher training). (shrink)