-/- The aim of this paper is to grasp the relevant distinctions between various ways in which models and simulations in Artificial Intelligence (AI) relate to cognitive phenomena. In order to get a systematic picture, a taxonomy is developed that is based on the coordinates of formal versus material analogies and theory-guided versus pre-theoretic models in science. These distinctions have parallels in the computational versus mimetic aspects and in analytic versus exploratory types of computer simulation. The proposed taxonomy cuts across (...) the traditional dichotomies between symbolic and embodied AI, general intelligence and symbol and intelligence and cognitive simulation and human/non-human-like AI. -/- According to the taxonomy proposed here, one can distinguish between four distinct general approaches that figured prominently in early and classical AI, and that have partly developed into distinct research programs: first, phenomenal simulations (e.g., Turing’s “imitation game”); second, simulations that explore general-level formal isomorphisms in pursuit of a general theory of intelligence (e.g., logic-based AI); third, simulations as exploratory material models that serve to develop theoretical accounts of cognitive processes (e.g., Marr’s stages of visual processing and classical connectionism); and fourth, simulations as strictly formal models of a theory of computation that postulates cognitive processes to be isomorphic with computational processes (strong symbolic AI). -/- In continuation of pragmatic views of the modes of modeling and simulating world affairs, this taxonomy of approaches to modeling in AI helps to elucidate how available computational concepts and simulational resources contribute to the modes of representation and theory development in AI research—and what made that research program uniquely dependent on them. (shrink)

The problem of epistemic opacity in Artificial Intelligence is often characterised as a problem of intransparent algorithms that give rise to intransparent models. However, the degrees of transparency of an AI model should not be taken as an absolute measure of the properties of its algorithms but of the model’s degree of intelligibility to human users. Its epistemically relevant elements are to be specified on various levels above and beyond the computational one. In order to elucidate this claim, I first (...) contrast computer models and their claims to algorithm-based universality with cybernetics-style analogue models and their claims to structural isomorphism between elements of model and target system. While analogue models aim at perceptually or conceptually accessible model-target relations, computer models give rise to a specific kind of underdetermination in these relations that needs to be addressed in specific ways. I then undertake a comparison between two contemporary AI approaches that, although related, distinctly align with the above modelling paradigms and represent distinct strategies towards model intelligibility: Deep Neural Networks and Predictive Processing. I conclude that their respective degrees of epistemic transparency primarily depend on the underlying purposes of modelling, not on their computational properties. (shrink)

Drawing on previous models of anxiety, intermediate memory, the positive symptoms of schizophrenia, and goal-directed behaviour, a neuropsychological hypothesis is proposed for the generation of the contents of consciousness. It is suggested that these correspond to the outputs of a comparator that, on a moment-by-moment basis, compares the current state of the organism's perceptual world with a predicted state. An outline is given of the information-processing functions of the comparator system and of the neural systems which mediate them. The hypothesis (...) appears to be able to account for a number of key features of the contents of consciousness. However, it is argued that neitherthis nor any existing comparable hypothesis is yet able to explain why the brain should generate conscious experience of any kind at all. (shrink)

The first claim in the target article was that there is as yet no transparent, causal account of the relations between consciousness and brain-and-behaviour. That claim remains firm. The second claim was that the contents of consciousness consist, psychologically, of the outputs of a comparator system; the third consisted of a description of the brain mechanisms proposed to instantiate the comparator. In order to defend these claims against criticism, it has been necessary to clarify the distinction between consciousness-as-such and the (...) contents of consciousness, to widen the description of the neural machinery instantiating the comparator system, and to clarify the relationship between the contents of consciousness in the here-and-now and episodic memory. (shrink)

In the wake of Frege's attack on psychologism and the subsequent influence of Logical Positivism, psychological considerations in philosophy came to be viewed with suspicion. Philosophical questions, especially epistemological ones, were viewed as 'logical' questions, and logic was sharply separated from psychology. Various efforts have been made of late to reconnect epistemology with psychology. But there is little agreement about how such connections should be made, and doubts about the place of psychology within epistemology are still much in evidence. It (...) therefore remains to be clarified just how such links should be established, and what impact they would have on the direction of epistemology. (shrink)

The central mission of cognitive science is to reveal the real nature of the mind, however familiar or foreign that nature may be to naive preconceptions. The existence of naive conceptions is also important, however. Prescientific thought and language contain concepts of the mental, and these concepts deserve attention from cognitive science. Just as scientific psychology studies folk physics (McCloskey 1983, Hayes 1985), viz., the common understanding (or misunderstanding) of physical phenomena, so it must study folk psychology, the common understanding (...) of mental states. This subfield of scientific psychology is what I mean by the phrase 'the psychology of folk psychology'. (shrink)

The ordinary understanding and ascription of mental states is a multiply complex subject. Widely discussed approaches to the subject, such as functionalism and the theory-theory (TT), have many variations and interpretations. No surprise, then, that there are misunderstandings and disagreements, which place many items on the agenda. Unfortunately, the multiplicity of issues raised by the commentators and the limitations of space make it impossible to give a full reply to everyone. My response is divided into five topics: (1) Which version(s) (...) of functionalism are candidates for an account of folk psychology, and is any such version satisfactory? (2) Where does TT stand in light of the two target articles and commentaries? (3) Does a phenomenological story provide a promising account of mental states, and is there special first-person authority about them? (4) What are suitable methodological assumptions for our subject matter? (5) How well does the simulation theory fare as an account of third-person mentalistic ascription? (shrink)

Fodor & Pylyshyn (1981) criticize J. J. Gibson's ecological account of perception for failing to address what I call the 'correlation problem' in visual perception. That is, they charge that Gibson cannot explain how perceivers learn to correlate detectable properties of the light with perceptible properties of the environment. Furthermore, they identify the correlation problem as a crucial issue for any theory of visual perception, what I call a 'primary problem'—i.e. a problem which plays a definitive role in establishing the (...) concerns of a particular scientific research program. If they are correct, Gibson's failure to resolve this problem would cast considerable doubt upon his ecological approach to perception. In response, I argue that both Fodor & Pylyshyn's problem itself and their proposed inferential solution embody a significant mistake which needs to be eliminated from our thinking about visual perception. As part of my response, I also suggest a Gibsonian alternative to Fodor & Pylyshyn's primary problem formulation. (shrink)

This commentary questions the target articles inferences from a limited set of empirical data to support this model and conceptual scheme. Especially questionable is the attribution of internal representation properties to an assembly of cells in a discrete cortical module firing at a discrete attractor frequency. Alternative inferences are drawn from cortical cooling and cell-firing data that point to the internal representation as a broad and specific cortical network defined by cortico-cortical connectivity. Active memory, it is proposed, consists in the (...) sustained activation of the component neuron populations of the network. (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.

Recent experiments have shown that when individuals with a substance use disorder are confronted with drug-related cues, they exhibit an automatically activated tendency to approach these cues. The strength of the drug approach bias has been associated with clinically relevant measures, such as increased drug craving and relapse, and activations in brain reward areas. Retraining the approach bias by means of cognitive bias modification has been demonstrated to decrease relapse rates in patients with an alcohol use disorder and to reduce (...) alcohol cue-evoked limbic activity. Here, we review empirical and theoretical literature on the drug approach bias and explore two distinct models of how the drug approach bias may be embodied. First, we consider the “biological meaning” hypothesis, which grounds the automatic approach bias in the natural meaning of the body. Second, we consider the “sensorimotor hypothesis,” which appeals to the specific sensorimotor loops involved in the instantiation of addictive behaviors as the basis of the automatic approach bias. In order to differentiate between the adequacies of these competing explanations, we present specific, predictions that each model should make. (shrink)

Recurrent excitation is experimentally well documented in cortical populations. It provides for intracortical excitatory biases that linearize negative feedback interactions and induce macroscopic state transitions during perception. The concept of the local neighborhood should be expanded to spatial patterns as the basis for perception, in which large areas of cortex are bound into cooperative behavior with near-silent columns as important as active columns revealed by unit recording.

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.

Examines the theses that the postulation of mental processing is unnecessary to account for our perceptual relationship with the world, see turvey etal. for a criticque.

ArgumentKuhnian phases of paradigmatic development correspond to characteristic variations of citation measures. These correlations can in turn be predicted from a simple model of human information processing when applied to the common environments of scientists. By combining a scientometric and a human information processing approach to the history of scientific thought, structures of disciplinary development, and in particular paradigmatic cycles, can be more reliably assessed than before. Consequently, the quantitative historian of science is liberated to some extent from the vagaries (...) of qualitative judgment, as exemplified by traditional narrative type approaches to the history of science. (shrink)