There are plenty of intelligent machines in our world today: digital computers and autonomous robots. At the heart of each of these machines there are automatic formal systems (programs running on a digital computer). Now, if the interpretation of a formal system does not belong to the formal system itself, if the interpretation has to be added, it is worth asking: in the case of these intelligent machines that are massively interspersed in our social interactions, where does the interpretation come (...) from? In this paper, we analyse what we call the invisibility of interpretation. Dealing with various types of formal systems (computers, robots, formalist approaches to Economics), the human source of the interpretation of these systems is sometimes concealed by a formalist restriction. To show how the formalist restriction produces the invisibility of interpretation allows us to underline our responsibility, as human agents, for all this interpretative work—and its importance for us as human beings. (shrink)

This dissertation will compare the concept of nature as it appears in the philosophies of the American pragmatist John Dewey and the Chinese daoist Zhuangzi and will defend two central claims. The first of these is that Dewey and Zhuangzi share a view of nature that is non-reductive, philosophically liberal, and more comprehensive than the accounts recurrent in much of the Western tradition. This alternate conception of nature is non-reductive in the way that it avoids the physically mechanistic outlook underwriting (...) much of contemporary Anglo-American thought. It is philosophically liberal in that it accepts a more generous and progressive position than predominant Western orthodoxies. And, it is more comprehensive in scope insofar as it draws as much from the social sciences as it does from the natural sciences. The second claim defended will be that the synoptic vision gained from such a comparison offers a new heuristic program for research into the philosophical position known as naturalism, a program that can, at once, avoid the scientistic tendencies of the current, mainstream treatment of nature and reconnect with earlier, more inclusive models. Where Dewey's and Zhuangzi's ideas converge, one finds similarities in the prescriptions each made for human action, and where they differ, one finds mutually complementary insights. Finally, this heuristic will be used to refute various interpretations of Dewey and Zhuangzi that tend to understate or ignore the importance of nature within their schemes. (shrink)

The paper questions the expert system paradigm, both in terms of its range of application, and as a significant contribution to the understanding of artificial intelligence. The viewpoint is that of the systems designer who must judge the applicability of these methods in imminent and future systems. The expert system paradigm, (ESP for short), is criticised not because it is ubiquitously wrong, but because its range of application appears to be very limited, and much promise is made of its application (...) in areas where its success is likely to be little more than a matter of luck. The paper considers the success in both academic and commercial settings. It is suggested that the contribution of the ESP to the wider ambitions of AI is modest, and to the practical user is still a considerable and largely unquantifiable risk. (shrink)

The proper treatment of computationalism, as the thesis that cognition is computable, is presented and defended. Some arguments of James H. Fetzer against computationalism are examined and found wanting, and his positive theory of minds as semiotic systems is shown to be consistent with computationalism. An objection is raised to an argument of Selmer Bringsjord against one strand of computationalism, namely, that Turing-Test± passing artifacts are persons, it is argued that, whether or not this objection holds, such artifacts will inevitably (...) be persons. (shrink)

The idea that human cognitive capacities are explainable by computational models is often conjoined with the idea that, while the states postulated by such models are in fact realized by brain states, there are no type-type correlations between the states postulated by computational models and brain states (a corollary of token physicalism). I argue that these ideas are not jointly tenable. I discuss the kinds of empirical evidence available to cognitive scientists for (dis)confirming computational models of cognition and argue that (...) none of these kinds of evidence can be relevant to a choice among competing computational models unless there are in fact type-type correlations between the states postulated by computational models and brain states. Thus, I conclude, research into the computational procedures employed in human cognition must be conducted hand-in-hand with research into the brain processes which realize those procedures. (shrink)

I propose a semi-eliminative reduction of Fodors concept of module to the concept of attractor basin which is used in Cognitive Dynamic Systems Theory (DST). I show how attractor basins perform the same explanatory function as modules in several DST based research program. Attractor basins in some organic dynamic systems have even been able to perform cognitive functions which are equivalent to the If/Then/Else loop in the computer language LISP. I suggest directions for future research programs which could find similar (...) equivalencies between organic dynamic systems and other cognitive functions. This type of research could help us discover how (and/or if) it is possible to use Dynamic Systems Theory to more accurately model the cognitive functions that are now being modeled by subroutines in Symbolic AI computer models. If such a reduction of subroutines to basins of attraction is possible, it could free AI from the limitations that prompted Fodor to say that it was impossible to model certain higher level cognitive functions. (shrink)

The frame problem is the problem of how we selectively apply relevant knowledge to particular situations in order to generate practical solutions. Some philosophers have thought that the frame problem can be used to rule out, or argue in favor of, a particular theory of belief states. But this is a mistake. Sentential theories of belief are no better or worse off with respect to the frame problem than are alternative theories of belief, most notably, the “map” theory of belief.

Recently, connectionist models have been developed that seem to exhibit structuresensitive cognitive capacities without executing a program. This paper examines one such model and argues that it does execute a program. The argument proceeds by showing that what is essential to running a program is preserving the functional structure of the program. It has generally been assumed that this can only be done by systems possessing a certain temporalcausal organization. However, counterfactualpreserving functional architecture can be instantiated in other ways, for (...) example geometrically, which are realizable by connectionist networks. (shrink)

In this paper the issue of drawing inferences about biological cognitive systems on the basis of connectionist simulations is addressed. In particular, the justification of inferences based on connectionist models trained using the backpropagation learning algorithm is examined. First it is noted that a justification commonly found in the philosophical literature is inapplicable. Then some general issues are raised about the relationships between models and biological systems. A way of conceiving the role of hidden units in connectionist networks is then (...) introduced. This, in combination with an assumption about the way evolution goes about solving problems, is then used to suggest a means of justifying inferences about biological systems based on connectionist research. (shrink)

Discussion of Searle's case against strong AI has usually focused upon his Chinese Room thought-experiment. In this paper, however, I expound and then try to refute what I call his abstract argument against strong AI, an argument which turns upon quite general considerations concerning programs, syntax, and semantics, and which seems not to depend on intuitions about the Chinese Room. I claim that this argument fails, since it assumes one particular account of what a program is. I suggest an alternative (...) account which, however, cannot play a role in a Searle-type argument, and argue that Searle gives no good reason for favoring his account, which allows the abstract argument to work, over the alternative, which doesn't. This response to Searle's abstract argument also, incidentally, enables the Robot Reply to the Chinese Room to defend itself against objections Searle makes to it. (shrink)

For my part, my only hope is, that I may contribute a little to the advancement of knowledge, by giving in some particulars a different turn to the speculations of philosophers, and pointing out to them more distinctly those subjects, where alone they can expect assurance and conviction.

The crucial point of the mind-body-problem appears to be that mental phenome- na (events, properties, states) seem to have features which at first sight make it impossible to integrate these phenomena into a naturalistic world view, i.e. to identify them with, or to reduce them to, physical phenomena.1 In the contemp- orary discussion, there are mainly two critical features which are important in this context. The first of these is the feature of intentional states, e.g. beliefs and desires, to have (...) a representational or semantic content. The problem of the naturalization of these states I will call the problem of intentionality. The second critical feature is the property of other mental states, e.g. perceptions and sensations, to have a qualitative aspect, i.e. that it is somehow, or feels in a characteristic way, to be in one of those states. The problem of the naturalization of these states is generally called the qualia-problem. (shrink)

The rapid development of connectionist models in computer science and of powerful computational tools in neuroscience has encouraged eliminativist materialist philosophers to propose specific alternatives to traditional mentalistic theories of mind. One of the problems associated with such a move is that elimination of the mental would seem to remove access to ideas like truth as the foundations of normative epistemology. Thus, a successful elimination of propositional or sentential theories of mind must not only replace them for purposes of our (...) psychology, it must also replace them for purposes of the evaluation of our theories and explanations, psychological and otherwise. This paper briefly reviews eliminativist arguments for doubting the correctness of sentential accounts of explanation, understanding, and normative evaluation. It then considers Paul Churchland's (1989) proposed alternative norms, which are framed neurocomputationally. The alternative is found wanting in several specific ways. The arguments for eliminating propositionally-based norms are then re-examined and it is suggested that the need for wholesale elimination is overstated. A clear gap in the traditional epistemological story is identified, however, and a more modest set of norms is proposed as a way of filling this gap, rather than as a way of entirely replacing the traditional framework. (shrink)

Roger Schank's research in AI takes seriously the ideas that understanding natural language involves mapping its expressions into an internal representation scheme and that these internal representations have a syntax appropriate for computational operations. It therefore falls within the computational approach to the study of mind. This paper discusses certain aspects of Schank's approach in order to assess its potential adequacy as a (partial) model of cognition. This version of the Language of Thought hypothesis encounters some of the same difficulties (...) that arise for Fodor's account. (shrink)

Some recent developments in Artificial Intelligence—especially the use of machine learning systems, trained on big data sets and deployed in socially significant and ethically weighty contexts—have led to a number of calls for “transparency”. This paper explores the epistemological and ethical dimensions of that concept, as well as surveying and taxonomising the variety of ways in which it has been invoked in recent discussions. Whilst “outward” forms of transparency may be straightforwardly achieved, what I call “functional” transparency about the inner (...) workings of a system is, in many cases, much harder to attain. In those situations, I argue that contestability may be a possible, acceptable, and useful alternative so that even if we cannot understand how a system came up with a particular output, we at least have the means to challenge it. (shrink)

Recently, many philosophers have been inclined to ascribe mentality to animals on the main grounds that they possess certain complex computational abilities. In this paper I contend that this view is misleading, since it wrongly assumes that those computational abilities demand a psychological explanation. On the contrary, they can be just characterised from a computational level of explanation, which picks up a domain of computation and information processing that is common to many computing systems but is autonomous from the domain (...) of psychology. Thus, I propose that it is possible to conceive insects and other animals as mere computing agents, without having any commitment to ascribe mentality to them. I conclude by sketching a proposal about how to draw the line between mere computing and genuine mentality. (shrink)

A fundamental problem in spoken language is the duality between the continuous aspects of phonetic performance and the discrete aspects of phonological competence. We study 2 instances of this problem from the phenomenon of voicing neutralization and vowel harmony. In each case, we present a model where the experimentally observed continuous distinctions are linked to the discreteness of phonological form using the mathematics of nonlinear dynamics.

The current renewal of connectionist techniques using networks of neuron-like units has started to have an influence on cognitive modelling. However, compared with classical artificial intelligence methods, the position of connectionism is still not clear. In this article artificial intelligence and connectionism are systematically compared as cognitive models so as to bring out the advantages and shortcomings of each. The problem of structured representations appears to be particularly important, suggesting likely research directions.

In this essay we try an answer to the question has intentionality to be reduced to anything? We propose that it is possible to reduce any variety of intentionality to a specification of mechanisms (internal organization of the items involved in a given intentional phenomenon) and a historical pattern of interaction (structure of mutual significant relations historically acquired by different items involved in the same intentional phenomenon). We first clarify the meaning of this proposal having recourse to the Ruth Millikan’s (...) teleosemantics. Then, we assess the relevance and feasibility of our proposal, considering, in a succession, the case of animals and humans, of machines, and of sophisticated human collectives. We conclude arguing the heuristic nature of the proposed reduction. DOI:10.5007/1808-1711.2010v14n2p255. (shrink)

Der Kern des Leib-Seele-Problems besteht darin, dass mentale Phänomene (Ereignisse, Eigenschaften, Zustände) Merkmale zu haben scheinen, die es auf den ersten Blick unmöglich machen, diese Phänomene in ein naturalisti- sches Weltbild zu integrieren – sie mit physikalischen Phänomenen zu identifizieren oder auf physikalische Phänomene zu reduzieren.2 Heute stehen hauptsächlich zwei von in diesem Sinne kritischen Merkmalen im Mit- telpunkt des Interesses.3 Das erste ist das Merkmal intentionaler Zustände, einen repräsentationalen oder semantischen Inhalt zu besitzen. Das Problem der Naturalisierung dieser Zustände (...) möchte ich das ‘Problem der Intentiona- lität’ nennen. Das zweite kritische Merkmal ist die Eigenschaft von Wahr- nehmungseindrücken und körperlichen Empfindungen, einen qualitativen Aspekt zu besitzen. Dieses Merkmal beruht auf der Tatsache, dass es auf eine bestimmte Weise ist oder sich auf eine bestimmte Weise anfühlt, in diesen Zuständen zu sein. Das Problem der Naturalisierung dieser Zustände wird gewöhnlich das ‘Qualia-Problem’ genannt. (shrink)

We describe a project to capitalize on newly available levels of computational resources in order to understand human cognition. We are building an integrated physical system including vision, sound input and output, and dextrous manipulation, all controlled by a continuously operating large scale parallel MIMD computer. The resulting system will learn to "think" by building on its bodily experiences to accomplish progressively more abstract tasks. Past experience suggests that in attempting to build such an integrated system we will have to (...) fundamentally change the way artificial intelligence, cognitive science, linguistics, and philosophy think about the organization of intelligence. We expect to be able to better reconcile the theories that will be developed with current work in neuroscience. (shrink)

Fodor argued that in contrast to input systems which are informationally encapsulated, general intelligence is unencapsulated and hence non-modular; for this reason, he suggested, prospects for understanding it are not bright. It is argued that an additional property, primitive functionality, is required for non-modularity. A functionally primitive computational model for quantifier scoping, limited to some scoping influences, is then motivated, and an implementation described. It is argued that only such a model can be faithful to intuitive scope preferences. But it (...) is also argued that an extended model which includes all scoping influences is a hopeless prospect from a developmental perspective. Fodor's views are concluded to have some independent support: quantifier scoping is a mental ability parasitic on general intelligence that is non-modular though in a revised sense, warranting pessimism about our ability of model it. (shrink)

A myth has arisen concerning Turing's paper of 1936, namely that Turing set forth a fundamental principle concerning the limits of what can be computed by machine - a myth that has passed into cognitive science and the philosophy of mind, to wide and pernicious effect. This supposed principle, sometimes incorrectly termed the 'Church-Turing thesis', is the claim that the class of functions that can be computed by machines is identical to the class of functions that can be computed by (...) Turing machines. In point of fact Turing himself nowhere endorses, nor even states, this claim (nor does Church). I describe a number of notional machines, both analogue and digital, that can compute more than a universal Turing machine. These machines are exemplars of the class of _nonclassical_ computing machines. Nothing known at present rules out the possibility that machines in this class will one day be built, nor that the brain itself is such a machine. These theoretical considerations undercut a number of foundational arguments that are commonly rehearsed in cognitive science, and gesture towards a new class of cognitive models. (shrink)

Ramsey, Stich and Garon's recent paper Connectionism, Eliminativism, and the Future of Folk Psychology claims a certain style of connectionism to be the final nail in the coffin of folk psychology. I argue that their paper fails to show this, and that the style of connectionism they illustrate can in fact supplement, rather than compete with, the claims of a theory of cognition based in folk psychology's ontology. Ramsey, Stich and Garon's argument relies on the lack of easily identifiable symbols (...) inside the connectionist network they discuss, and they suggest that the existence of a system which behaves in a cognitively interesting way, but which cannot be explained by appeal to internal symbol processing, falsifies central assumptions of folk psychology. My claim is that this argument is flawed, and that the theorist need not discard folk psychology in order to accept that the network illustrated exhibits cognitively interesting behaviour, even if it is conceded that symbols cannot be readily identified within the network. (shrink)

Given (1) Wittgensteins externalist analysis of the distinction between following a rule and behaving in accordance with a rule, (2) prima facie connections between rule-following and psychological capacities, and (3) pragmatic issues about training, it follows that most, even all, future artificially intelligent computers and robots will not use language, possess concepts, or reason. This argument suggests that AIs traditional aim of building machines with minds, exemplified in current work on cognitive robotics, is in need of substantial revision.

Causal representation in shamanic consciousness is compared with causal representation in ordinary waking consciousness. Causal representation in shamanic experience and in ordinary waking experience can engage strategies involving attribution of intentionality , heuristics , and magical thinking . Such strategies have consequences involving social biases , locus of control, authorship of actions, and supernaturalizing of social life. Similarities of causal representation in shamanic experience and in ordinary waking experience have implications for theories of mind and theories of causal representation, and (...) these implications involve use of metaphor and analogy, modular processing of social information, use of behavioural criteria for mental states, differences between physical causality and social causality, property transmission in causal representation, and whether causal representation involves general or state-specific processes. Principles of causal representation in shamanic consciousness appear consistent with principles of causal representation in ordinary waking consciousness. (shrink)

Mechanism is the thesis that men can be considered as machines, that there is no essential difference between minds and machines.John Lucas has argued that it is a consequence of Gödel's theorem that mechanism is false. Men cannot be considered as machines, because the intellectual capacities of men are superior to that of any machine. Lucas claims that we can do something that no machine can do-namely to produce as true the Gödel-formula of any given machine. But no machine can (...) prove its own Gödel-formula. (shrink)

Digital computers play a special role in cognitive science—they may actually be instances of the phenomenon they are being used to model. This paper surveys some of the main issues involved in understanding the relationship between digital computers and cognition. It sketches the role of digital computers within orthodox computational cognitive science, in the light of a recently emerging alternative approach based around dynamical systems.