The common account of the analog vs digital distinction is based on features of physical systems, being related to the usage of continuous vs discrete supports respectively. It is proposed here to alternatively characterize the concepts of analog and digital as related to coding systems, of which a formal definition is given, by suggesting that the distinction refers to the strategy adopted to define the coding function: extensional in digital systems, isomorphic intensional in analog systems. This thesis is supported by (...) examples, in particular of analog systems exploiting discrete supports, and is discussed to explain why digital coding is currently so widespread in technological and social practice. (shrink)

Qualitative-consciousness arises at the sensory level of olfactory processing and pervades our experience of smells to the extent that qualitative character is maintained whenever we are aware of undergoing an olfactory experience. Building upon the distinction between Access and Phenomenal Consciousness the paper offers a nuanced distinction between Awareness and Qualitative-consciousness that is applicable to olfaction in a manner that is conceptual precise and empirically viable. Mounting empirical research is offered substantiating the applicability of the distinction to olfaction and showing (...) that olfactory qualitative-consciousness can occur without awareness, but any olfactory state that we are aware of being in is always qualitative. Evidence that olfactory sensory states have a qualitatively character in the absence of awareness derives from research on mate selection, the selection of social preference for social interaction and acquaintances, as well as the role of olfactory deficits in causing affective disorders. Furthermore, the conservation of secondary processing measures of olfactory valence during olfactory imagery experiments provides verification that olfactory awareness is always qualitatively conscious—all olfactory consciousness smells phenomenal. (shrink)

Mind &Language, Volume 35, Issue 1, Page 90-114, February 2020.

After more than twenty years of representational debate in the cognitive sciences, anti-representational dynamicism may be seen as offering a rival and radically new kind of explanation of systematicity phenomena. In this paper, I argue that, on the contrary, anti-representational dynamicism must face a version of the old systematicity challenge: either it does not explain systematicity, or else, it is just an implementation of representational theories. To show this, I present a purely behavioral and representation-free account of systematicity. I then (...) consider a case of insect sensorimotor systematic behavior: communicating behavior in honey bees. I conclude that anti-representational dynamicism fails to capture the fundamental trait of systematic behaviors qua systematic, i.e., their involving exercises of the same behavioral capacities. I suggest, finally, a collaborative strategy in pursuit of a rich and powerful account of this central phenomenon of high cognition at all levels of explanation, including the representational level. (shrink)

Marr’s celebrated contribution to cognitive science (Marr 1982, chap. 1) was the introduction of (at least) three levels of description/explanation. However, most contemporary research has relegated the distinction between levels to a rather dispensable remark. Ignoring such an important contribution comes at a price, or so we shall argue. In the present paper, first we review Marr’s main points and motivations regarding levels of explanation. Second, we examine two cases in which the distinction between levels has been neglected when considering (...) the structure of mental representations: Cummins et al.’s distinction between structural representation and encodings (Cummins in Journal of Philosophy, 93(12):591–614, 1996; Cummins et al. in Journal of Philosophical Research, 30:405–408, 2001) and Fodor’s account of iconic representation (Fodor 2008). These two cases illustrate the kind of problems in which researchers can find themselves if they overlook distinctions between levels and how easily these problems can be solved when levels are carefully examined. The analysis of these cases allows us to conclude that researchers in the cognitive sciences are well advised to avoid risks of confusion by respecting Marr’s old lesson. (shrink)

One of the main challenges that Jerry Fodor and Zenon Pylyshyn (Cognition 28:3–71, 1988) posed for any connectionist theory of cognitive architecture is to explain the systematicity of thought without implementing a Language of Thought (LOT) architecture. The systematicity challenge presents a dilemma: if connectionism cannot explain the systematicity of thought, then it fails to offer an adequate theory of cognitive architecture; and if it explains the systematicity of thought by implementing a LOT architecture, then it fails to offer an (...) alternative to the LOT hypothesis. Given that thought is systematic, connectionism can offer an adequate alternative to the LOT hypothesis only if it can meet the challenge. Although some critics tried to meet the challenge, others argued that it need not be met since thought is not in fact systematic; and some claimed not to even understand the claim that thought is systematic. I do not here examine attempts to answer the challenge. Instead, I defend the challenge itself by explicating the notion of systematicity in a way that I hope makes clear that thought is indeed systematic, and so that to offer an adequate alternative to the LOT hypothesis, connectionism must meet the challenge. (shrink)

The systematicity argument only challenges connectionism if systematicity is a general property of cognition. I examine this thesis in terms of properties of concepts. First, I propose that Evans's Generality Constraint only applies to attributions of belief. Then I defend a variety of conceptual pluralism, arguing that concepts share two fundamental properties related to centrality and belief-attribution, and contending that there are two kinds of concepts that differ in their compositional properties. Finally, I rely on Dual Systems Theory and on (...) differences between animal and human cognition to suggest a scenario of two processing systems that work on different kinds of concepts, with only one of them supporting full systematicity. I sketch a non-classical systematicity argument that rules out classicism as the basis of one of those systems given that it would wrongly entail that both systems are fully systematic. (shrink)

It has been commonplace in epistemology since its inception to idealize away from computational resource constraints, i.e., from the constraints of time and memory. One thought is that a kind of ideal rationality can be specified that ignores the constraints imposed by limited time and memory, and that actual cognitive performance can be seen as an interaction between the norms of ideal rationality and the practicalities of time and memory limitations. But a cornerstone of naturalistic epistemology is that normative assessment (...) is constrained by capacities: you cannot require someone to do something they cannot or, as it is usually put, ought implies can. This much we take to be uncontroversial. We argue that differences in architectures, goals and resources imply substantial differences in capacity, and that some of these differences are ineliminable. It follows that some differences in goals and architectural and computational resources matter at the normative level: they constrain what principles of normative epistemology can be used to describe and prescribe their behavior. As a result, we can expect there to be important epistemic differences between the way brains, individuals, and science work. (shrink)

In this paper I argue that whether or not a computer can be built that passes the Turing test is a central question in the philosophy of mind. Then I show that the possibility of building such a computer depends on open questions in the philosophy of computer science: the physical Church-Turing thesis and the extended Church-Turing thesis. I use the link between the issues identified in philosophy of mind and philosophy of computer science to respond to a prominent argument (...) against the possibility of building a machine that passes the Turing test. Finally, I respond to objections against the proposed link between questions in the philosophy of mind and philosophy of computer science. (shrink)

Quality-space theory (QST) explains the nature of the mental qualities distinctive of perceptual states by appeal to their role in perceiving. QST is typically described in terms of the mental qualities that pertain to color. Here we apply QST to the olfactory modalities. Olfaction is in various respects more complex than vision, and so provides a useful test case for QST. To determine whether QST can deal with the challenges olfaction presents, we show how a quality space (QS) could be (...) constructed relying on olfactory perceptible properties and the olfactory mental qualities then defined by appeal to that QS of olfactory perceptible properties. We also consider how to delimit the olfactory QS from other modalities. We further apply QST to the role that experience plays in refining our olfactory discriminative abilities and the occurrence of olfactory mental qualities in non-conscious olfactory states. QST is shown to be fully applicable to and useful for understanding the complex domain of olfaction. (shrink)

I show that there are good arguments and evidence to boot that support the language as an instrument of thought hypothesis. The underlying mechanisms of language, comprising of expressions structured hierarchically and recursively, provide a perspective (in the form of a conceptual structure) on the world, for it is only via language that certain perspectives are avail- able to us and to our thought processes. These mechanisms provide us with a uniquely human way of thinking and talking about the world (...) that is different to the sort of thinking we share with other animals. If the primary function of language were communication then one would expect that the underlying mechanisms of language will be structured in a way that favours successful communication. I show that not only is this not the case, but that the underlying mechanisms of language are in fact structured in a way to maximise computational efficiency, even if it means causing communicative problems. Moreover, I discuss evidence from comparative, neuropatho- logical, developmental, and neuroscientific evidence that supports the claim that language is an instrument of thought. (shrink)