This paper argues against Oaksford and Chater's claim that logicist cognitive science is not possible. It suggests that there arguments against logicist cognitive science are too closely tied to the account of Pylyshyn and of Fodor, and that the correct way of thinking about logicist cognitive science is in a mental models framework.

This piece is a commentary on a precis of Maggie Boden's book "The creative mind" published in Behavioral and Brain Sciences.

This target article draws together two groups of experimental studies on the control of human movement through peripheral feedback and centrally generated signals of motor commands. First, during natural movement, feedback from muscle, joint, and cutaneous afferents changes; in human subjects these changes have reflex and kinesthetic consequences. Recent psychophysical and microneurographic evidence suggests that joint and even cutaneous afferents may have a proprioceptive role. Second, the role of centrally generated motor commands in the control of normal movements and movements (...) following acute and chronic deafferentation is reviewed. There is increasing evidence that subjects can perceive their motor commands under various conditions, but that this is inadequate for normal movement; deficits in motor performance arise when the reliance on proprioceptive feedback is abolished either experimentally or because of pathology. During natural movement, the CNS appears to have access to functionally useful input from a range of peripheral receptors as well as from internally generated command signals. The unanswered questions that remain suggest a number of avenues for further research. (shrink)

This paper is a review of the work that has been carried out on machine consciousness. A clear overview of this diverse field is achieved by breaking machine consciousness down into four different areas, which are used to understand its aims, discuss its relationship with other subjects and outline the work that has been carried out so far. The criticisms that have been made against machine consciousness are also covered, along with its potential benefits, and the work that has been (...) done on analysing systems for signs of consciousness. Some of the social and ethical issues raised by machine consciousness are examined at the end of the paper. (shrink)

Research is starting to identify correlations between consciousness and some of the spatiotemporal patterns in the physical brain. For theoretical and practical reasons, the results of experiments on the correlates of consciousness have ambiguous interpretations. At any point in time a number of hypotheses co-exist about and the correlates of consciousness in the brain, which are all compatible with the current experimental results. This paper argues that consciousness should be attributed to any system that exhibits spatiotemporal physical patterns that match (...) the hypotheses about the correlates of consciousness that are compatible with the current experimental results. Some computers running some programs should be attributed consciousness because they produce spatiotemporal patterns in the physical world that match those that are potentially linked with consciousness in the human brain. (shrink)

Information theory provides a quantitative conceptual framework for understanding the flow of information from the world into and through brains. It focuses our attention on the sets of possible messages a brain's anatomy and physiology enable it to receive. The meanings of the messages arise from the inferences licensed by the brain's processing of them. Different meanings arise at different levels because different representations of the input license different inferences.

The cognitive phenomenology thesis has it that conscious cognitive states essentially exhibit a phenomenal character. Defenders of ‘conservatism’ about cognitive phenomenology think that the phenomenology of thought is reducible to sensory phenomenology. In contrast, proponents of ‘liberalism’ hold that there is a proprietary, sui generis cognitive phenomenology. Horgan develops a morph-sequence argument to argue for liberalism. The argument is based on the conceivability of a cognitive phenomenology zombie, i.e. a man who does not understand Chinese but shares the behavior and (...) sensory phenomenology with his twin who does understand Chinese. I argue that the conceivability of a cognitive phenomenology-zombie fails to settle the debate between conservatives and liberals. The roots of the ineffectiveness of the argument lie in the diverse readings of sensory phenomenology which flesh out the relation between sensory phenomenology and concepts differently but explain the conceivability of the scenario equally well. The lesson to learn is that to adjudicate the debate about cognitive phenomenology, we first have to clarify the notion of sensory phenomenology. (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)

Gray has expanded his account of schizophrenia to explain consciousness as well. His theory explains neither phenomenon adequately because he treats individual minds in isolation. The primary function of consciousness is to permit high level interactions with other conscious beings. The key symptoms of schizophrenia reflect a failure of this mechanism.

The Turing Test, originally proposed as a simple operational definition of intelligence, has now been with us for exactly half a century. It is safe to say that no other single article in computer science, and few other articles in science in general, have generated so much discussion. The present article chronicles the comments and controversy surrounding Turing's classic article from its publication to the present. The changing perception of the Turing Test over the last fifty years has paralleled the (...) changing attitudes in the scientific community towards artificial intelligence: from the unbridled optimism of 1960's to the current realization of the immense difficulties that still lie ahead. I conclude with the prediction that the Turing Test will remain important, not only as a landmark in the history of the development of intelligent machines, but also with real relevance to future generations of people living in a world in which the cognitive capacities of machines will be vastly greater than they are now. (shrink)

Do the dynamics of a physical system determine what function the system computes? Except in special cases, the answer is no: it is often indeterminate what function a given physical system computes. Accordingly, care should be taken when the question ‘What does a particular neuronal system do?’ is answered by hypothesising that the system computes a particular function. The phenomenon of the indeterminacy of computation has important implications for the development of computational explanations of biological systems. Additionally, the phenomenon lends (...) some support to the idea that a single neuronal structure may perform multiple cognitive functions, each subserved by a different computation. We provide an overarching conceptual framework in order to further the philosophical debate on the nature of computational indeterminacy and computational explanation. (shrink)

Which notion of computation (if any) is essential for explaining cognition? Five answers to this question are discussed in the paper. (1) The classicist answer: symbolic (digital) computation is required for explaining cognition; (2) The broad digital computationalist answer: digital computation broadly construed is required for explaining cognition; (3) The connectionist answer: sub-symbolic computation is required for explaining cognition; (4) The computational neuroscientist answer: neural computation (that, strictly, is neither digital nor analogue) is required for explaining cognition; (5) The extreme (...) dynamicist answer: computation is not required for explaining cognition. The first four answers are only accurate to a first approximation. But the “devil” is in the details. The last answer cashes in on the parenthetical “if any” in the question above. The classicist argues that cognition is symbolic computation. But digital computationalism need not be equated with classicism. Indeed, computationalism can, in principle, range from digital (and analogue) computationalism through (the weaker thesis of) generic computationalism to (the even weaker thesis of) digital (or analogue) pancomputationalism. Connectionism, which has traditionally been criticised by classicists for being non-computational, can be plausibly construed as being either analogue or digital computationalism (depending on the type of connectionist networks used). Computational neuroscience invokes the notion of neural computation that may (possibly) be interpreted as a sui generis type of computation. The extreme dynamicist argues that the time has come for a post-computational cognitive science. This paper is an attempt to shed some light on this debate by examining various conceptions and misconceptions of (particularly digital) computation. (shrink)

The convincing argument that Brette makes for the neural coding metaphor as imposing one view of brain behavior can be further explained through discourse analysis. Instead of a unified view, we argue, the coding metaphor's plasticity, versatility, and robustness throughout time explain its success and conventionalization to the point that its rhetoric became overlooked.

Because consciousness has an organizational, or functional, center, Gray supposes that there must be a corresponding physical center in the brain. He proposes further that since this center generates consciousness, ablating it would eliminate consciousness, while leaving behavior intact. But the center of consciousness is simply the product of the functional linkages among sensory input, memory, inner speech, and so on, and behavior.

Like everyone with a scientific bent of mind, Dennett thinks our capacity for meaningful language and states of mind is the product of evolution (Dennett [1987, ch. VIII]). But unlike many of this bent, he sees virtue in viewing evolution itself from the intentional stance. From this stance, ?Mother Nature?, or the process of evolution by natural selection, bestows intentionality upon us, hence we are not Unmeant Meaners. Thus, our intentionality is extrinsic, and Dennett dismisses the theories of meaning of (...) Dretske, Fodor, Burge, Putnam, and Kripke on the grounds that each requires that our mental states, unlike those of artifacts, have meaning intrinsically. I argue that we are Unmeant Meaners, incidentally defending Dretske et al., though my goal is to test the explanatory virtue of the intentional stance as applied to the evolution of intentionality. (shrink)

The aim of this paper is to offer an analysis of the notion of artificial moral agent (AMA) and of its impact on human beings’ self-understanding as moral agents. Firstly, I introduce the topic by presenting what I call the Continuity Approach. Its main claim holds that AMAs and human moral agents exhibit no significant qualitative difference and, therefore, should be considered homogeneous entities. Secondly, I focus on the consequences this approach leads to. In order to do this I take (...) into consideration the work of Bostrom and Dietrich, who have radically assumed this viewpoint and thoroughly explored its implications. Thirdly, I present an alternative approach to AMAs—the Discontinuity Approach—which underscores an essential difference between human moral agents and AMAs by tackling the matter from another angle. In this section I concentrate on the work of Johnson and Bryson and I highlight the link between their claims and Heidegger’s and Jonas’s sug-gestions concerning the relationship between human beings and technological products. In conclusion I argue that, although the Continuity Approach turns out to be a necessary postulate to the machine ethics project, the Discontinuity Approach highlights a relevant distinction between AMAs and human moral agents. On this account, the Discontinuity Approach generates a clearer understanding of what AMAs are, of how we should face the moral issues they pose, and, finally, of the difference that separates machine ethics from moral philosophy. (shrink)

I suggest that most discussions of intentional systems have overlooked an important aspect of living organisms: the intrinsic goal-directedness inherent in the behaviour of living eukaryotic cells. This goal directedness is nicely displayed by a normal cell’s ability to rearrange its own local material structure in response to damage, nutrient distribution or other aspects of its individual experience. While at a vastly simpler level than intentionality at the human cognitive level, I propose that this basic capacity of living things provides (...) a necessary building block for cognition and high-order intentionality, because the neurons that make up vertebrate brains, like most cells in our body, embody such capacities. I provisionally dub the capacities in question “nano-intentionality”: a microscopic form of “aboutness”. The form of intrinsic intentionality I propose is thoroughly materialistic, fully compatible with known biological facts, and derived non-mysteriously through evolution. Crucially, these capacities are not shared by any existing computers or computer components, and thus provide a clear, empirically-based distinction between brains and currently existing artificial information processing systems. I suggest that an appreciation of this aspect of living matter provides a potential route out of what may otherwise appear to be a hopeless philosophical quagmire confronting information-processing models of the mind. (shrink)

This paper aims to show that dominant conceptions of intelligence used in artificial intelligence (AI) are biased by normative assumptions that originate from the Global North, making it questionable if AI can be uncritically applied elsewhere without risking serious harm to vulnerable people. After the introduction in Sect. 1 we shortly present the history of IQ testing in Sect. 2, focusing on its multiple discriminatory biases. To determine how these biases came into existence, we define intelligence ontologically and underline its (...) constructed and culturally variable character. Turning to AI, specifically the Turing Test (TT), in Sect. 3, we critically examine its underlying intelligence conceptions. The test has been of central influence in AI research and remains an important point of orientation. We argue that both the test itself and how it is used in practice risk promoting a limited conception of intelligence which solely originated in the Global North. Hence, this conception should be critically assessed in relation to the different global contexts in which AI technologies are and will be used. In Sect. 4, we highlight how unequal power relations in AI research are a real threat, rather than just philosophical sophistry while considering the history of IQ testing and the TT’s practical biases. In the last section, we examine the limits of our account and identify fields for further investigation. Tracing colonial continuities in AI intelligence research, this paper points to a more diverse and historically aware approach to the design, development, and use of AI. (shrink)

The relationship between philosophy and research on artificial intelligence (AI) has been difficult since its beginning, with mutual misunderstanding and sometimes even hostility. By contrast, we show how an approach informed by both philosophy and AI can be productive. After reviewing some popular frameworks for computation and learning, we apply the AI methodology of “build it and see” to tackle the philosophical and psychological problem of characterizing perception as distinct from sensation. Our model comprises a network of very simple, but (...) interacting agents which have binary experiences of the “yes/no”-type and communicate their experiences with each other. When does such a network refer to a single agent instead of a distributed network of entities? We apply machine learning techniques to address the following related questions: i) how can the model explain stability of compound entities, and ii) how could the model implement a single task such as perceptual inference? We thereby find consistency with previous work on “interface” strategies from perception research. While this reflects some necessary conditions for the ascription of agency, we suggest that it is not sufficient. Here, AI research, if it is intended to contribute to conceptual understanding, would benefit from issues previously raised by philosophy. We thus conclude the article with a discussion of action-selection, the role of embodiment, and consciousness to make this more explicit. We conjecture that a combination of AI research and philosophy allows general principles of mind and being to emerge from a “quasi-empirical” investigation. (shrink)

Meaning has traditionally been regarded as a problem for philosophers and psychologists. Advances in cognitive science since the early 1960s, however, broadened discussions of meaning, or more technically, the semantics of perceptions, representations, and/or actions, into biology and computer science. Here, we review the notion of “meaning” as it applies to living systems, and argue that the question of how living systems create meaning unifies the biological and cognitive sciences across both organizational and temporal scales.

In this article I defend two theses. The first is that the centrality of recording in the social world is manifested through the production of documents, a phenomenon which has been present since the earliest phases of society and which has undergone an exponential growth through the technological developments of the last decades. The second is that the centrality of documents leads to a view of normativity according to which human beings are primarily passive receptors of rules manifested through documents. (...) We are not intentional producers of values. The latter, as I shall suggest in my conclusion, should be viewed as being ‘socially dependent’ rather than ‘socially constructed’. (shrink)