It is common to distinguish two great families of representation. Symbolic representations include logical and mathematical symbols, words, and complex linguistic expressions. Iconic representations include dials, diagrams, maps, pictures, 3-dimensional models, and depictive gestures. This essay describes and motivates a new way of distinguishing iconic from symbolic representation. It locates the difference not in the signs themselves, nor in the contents they express, but in the semantic rules by which signs are associated with contents. The two kinds of rule have (...) divergent forms, occupying opposite poles on a spectrum of naturalness. Symbolic rules are composed entirely of primitive juxtapositions of sign types with contents, while iconic rules determine contents entirely by uniform natural relations with sign types. This distinction is marked explicitly in the formal semantics of familiar sign systems, both for atomic first-order representations, like words, pixel colors, and dials, and for complex second-order representations, like sentences, diagrams, and pictures. (shrink)

Ronald de Sousa is one of the few analytic philosophers to have explored the ineffability of emotion. Ineffability arises, for de Sousa, from attempts to translate experience, which involves non-conceptual content, into language, which involves conceptual content. As de Sousa himself rightly notes, such a characterization construes all perceptual experience as ineffable and does not explain what might set emotional ineffability apart. I build on de Sousa’s insights regarding what makes emotional ineffability distinctive by highlighting that in the case of (...) emotion the content in question is, crucially, evaluative. Evaluative content has normativity that makes the ineffability of emotion both particularly salient as well as particularly relevant, as the way in which an object is valuable is felt to be merited despite the experience’s ineffability. After proposing an improved working definition of emotional ineffability, I move to the question of how language and emotional experience interact, and whether these interactions can be evaluated in any systematic way. While de Sousa is pessimistic regarding the prospects of such an evaluation, I argue that if we move beyond an individual level of analysis it is possible to characterize cases where the ineffability of emotion leaves members of particular social groups vulnerable to a range of epistemic and affective injustices. I argue that we can similarly characterize cases where the ineffability of emotion holds radical potential to challenge and transform unjust social arrangements. I end by proposing that the representational content of emotion involves what I call ‘modal complexity’ and that this makes emotions particularly well-suited to play such radical roles. (shrink)

In the age of digitization, the world seems to be reducible to a digital computer. However, mathematically, modern quantum field theories do not only depend on discrete, but also continuous concepts. Ancient debates in natural philosophy on atomism versus the continuum are deeply involved in modern research on digital and computational physics. This example underlines that modern physics, in the tradition of Newton’s Principia Mathematica Philosophiae Naturalis, is a further development of natural philosophy with the rigorous methods of mathematics, measuring, (...) and computing. We consider fundamental concepts of natural philosophy with mathematical and computational methods and ask for their ontological and epistemic status. The following article refers to the author’s book, “The Digital and the Real World. Computational Foundations of Mathematics, Science, Technology, and Philosophy.”. (shrink)

Cognitive representations are typically analysed in terms of content, vehicle and format. While current work on formats appeals to intuitions about external representations, such as words and maps, in this paper we develop a computational view of formats that does not rely on intuitions. In our view, formats are individuated by the computational profiles of vehicles, i.e., the set of constraints that fix the computational transformations vehicles can undergo. The resulting picture is strongly pluralistic, it makes space for a variety (...) of different formats, and is intimately tied to the computational approach to cognition in cognitive science and artificial intelligence. (shrink)

The format of mental representation is the way information is organized in the mind. The discussion surrounding the format of representation addresses the problem of what representational primitives are and the rules of information processing. In philosophy, the discussion is dominated by the distinction between analog and digital representational systems. It is thought that this distinction can bring us closer to an understanding of the nature of perceptual and discursive representations. I argue that the analog-digital distinction cannot meet that expectation. (...) The analog-digital distinction is neither sufficient nor necessary to explain the distinction between perceptual and discursive representations. I propose an alternative interpretation of the concept of representational format which provides us a better understanding of the difference between iconic and discursive representations. I explain the differences between formats of representations in terms of differences in information processing. I demonstrate, how this alternative interpretation of the concept of the representational format can explain the constraints put on the contents of representational systems. (shrink)

The ‘received view’ of the analog–digital distinction holds that analog representations are continuous while digital representations are discrete. In this paper I first provide support for the received view by showing how it (1) emerges from the theory of computation, and (2) explains engineering practices. Second, I critically assess several recently offered alternatives, arguing that to the degree they are justified they demonstrate not that the received view is incorrect, but rather that distinct senses of the terms have become entrenched (...) specific fields, perhaps most notably in the cognitive psychology of mental imagery. (shrink)

Characterizing different kinds of representation is of fundamental importance to cognitive science, and one traditional way of doing so is in terms of the analog–digital distinction. Indeed the distinction is often appealed to in ways both narrow and broad. In this paper I argue that the analog–digital distinction does not apply to representational schemes but only to representational systems, where a representational system is constituted by a representational scheme and its user, and that whether a representational system is analog or (...) non-analog depends on facts about that user. This aspect of the distinction has gone unnoticed, and I argue that the failure to notice it can be an impediment to scientific progress. (shrink)

: Fodor argues that perceptual representations are a subset of iconic representations, which are distinguished from symbolic/discursive representations. Iconic representations are nonconceptual and they do not support the abilities afforded by concepts. Iconic representations, for example, cannot support object individuation. If someone thinks that perception or some of its parts has imagistic NCC, they face the following dilemma. Either they will have to accept that this NCC does not allow for object individuation, but it represents instead conglomerations of properties and (...) at some stage of visual processing it must interface with cognition and its conceptual capacities for the visual objects to be individuated. Or, they will have to hold that the imagistic, NCC of perception, allows for object individuation. I opt for the second thesis because I think there is strong empirical evidence that objects are individuated during early vision. I also think that early vision individuates objects by means of, what I had previously called nonconceptual perceptual demonstrative reference. I argue, first, why Fodor’s view that iconic NCC does not enable object individuation is false. I also argue, contra Fodor, that early vision allows the perception of the cardinality of sets of objects. Keywords : Early Vision; Analog Representations; Object Individuation; Arithmetic Cognition; Cardinality of Sets L'individuazione di oggetti mediante il contenuto iconico: come è rappresentata la numerosità nella rappresentazione iconica? Riassunto: Per Fodor le rappresentazioni percettive sono un sottoinsieme delle rappresentazioni iconiche, distinte dalle rappresentazioni simbolico/discorsive. Le rappresentazioni iconiche sono nonconcettuali e non supportano le abilità richieste dai concetti. Le rappresentazioni iconiche, per esempio, non supportano l'individuazione di oggetti. Se si pensa che la percezione o qualche sua parte abbia un contenuto nonconcettuale come immagine, si ci si imbatte nel seguente dilemma. O si accetta che il NCC non permetta di individuare oggetti, ma che rappresenti conglomerati di proprietà e che si interfacci con la cognizione e le sue capacità concettuali, per individuare gli oggetti visivi. O si dice che l'immagine, il NCC, della percezione consenta di individuare oggetti. Propendo per la seconda tesi, poiché penso che ci sia solida evidenza empirica per cui gli oggetti vengono individuati durante le prime fasi della visione, in cui l’individuazione avviene mediante quanto definito come riferimento dimostrativo del contenuto nonconcettuale percettivo. Chiarirò le ragioni per cui la concezione di Fodor, per cui il contenuto nonconcettuale iconico non supporta l’individuazione di oggetti, è falsa. Inoltre, contra Fodor, sosterrò che le prime fasi della visione permettono la percezione della cardinalità di insiemi di oggetti. Parole chiave: Prime fasi della visione; Rappresentazioni analogiche; Individuazione di oggetti; Cognizione aritmetica; Cardinalità degli insiemi. (shrink)

I argue that analogue mental representations possess a canonical decomposition into privileged constituents from which they compose. I motivate this suggestion, and rebut arguments to the contrary, through reflection on the approximate number system, whose representations are widely expected to have an analogue format. I then argue that arguments for the compositionality and constituent structure of these analogue representations generalize to other analogue mental representations posited in the human mind, such as those in early vision and visual imagery.

It is often claimed that pre-attentive vision has an ‘iconic’ format. This is seen to explain pre-attentive vision's characteristically high processing capacity and to make sense of an overlap in the mechanisms of early vision and mental imagery. But what does the iconicity of pre-attentive vision amount to? This paper considers two prominent ways of characterising pre-attentive visual icons and argues that neither is adequate: one approach renders the claim ‘pre-attentive vision is iconic’ empirically false while the other obscures its (...) ability to do the explanatory work, which motivates positing pre-attentive visual icons in the first place. With this noted, I introduce the notion of an ‘Analogue Map’ and argue that it provides a superior characterisation of pre-attentive vision's iconicity. I then argue that this forces a reassessment of debates which have traditionally presupposed the iconicity of pre-attentive vision, emphasising ramifications for the viability of a format-based perception-thought border. (shrink)

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)

Relative to digital computation, analogue computation has been neglected in the philosophical literature. To the extent that attention has been paid to analogue computation, it has been misunderstood. The received view—that analogue computation has to do essentially with continuity—is simply wrong, as shown by careful attention to historical examples of discontinuous, discrete analogue computers. Instead of the received view, I develop an account of analogue computation in terms of a particular type of analogue representation that allows for discontinuity. This account (...) thus characterizes all types of analogue computation, whether continuous or discrete. Furthermore, the structure of this account can be generalized to other types of computation: analogue computation essentially involves analogue representation, whereas digital computation essentially involves digital representation. Besides being a necessary component of a complete philosophical understanding of computation in general, understanding analogue computation is important for computational explanation in contemporary neuroscience and cognitive science. (shrink)

Analog representation is often cast in terms of an engineering distinction between smooth and discrete systems. The engineering notion cuts across interesting representational categories, however, so it is poorly suited to thinking about kinds of representation. This paper suggests that analog representations support a pattern of interaction, specifically open-ended searches for content across levels of abstraction. They support the pattern by sharing a structure with what they represent. Continuous systems that satisfy the engineering notion are exemplars of this kind because (...) they are uninterpretable unless they are structure-preserving. Analog representations, so understood, include pictures, images, diagrams, and most graphs. This conception of analogicity also fits well with a line of thought about what makes perceptual states distinctive: they satisfy a “parts principle”. (shrink)

This paper develops a theory of analog representation. We first argue that the mark of the analog is to be found in the nature of a representational system’s interpretation function, rather than in its vehicles or contents alone. We then develop the rulebound structure theory of analog representation, according to which analog systems are those that use interpretive rules to map syntactic structural features onto semantic structural features. The theory involves three degree-theoretic measures that capture three independent ways in which (...) a system can be more or less analog. We explain how our theory improves upon prior accounts of analog representation, provides plausible diagnoses for novel challenge cases, extends to hybrid systems that are partially analog and partially symbolic, and accounts for some of the advantages and disadvantages of representing analogically versus symbolically. (shrink)

A weak version of the life-mind continuity thesis entails that every living system also has a basic mind (with a non-representational form of intentionality). The strong version entails that the same concepts that are sufficient to explain basic minds (with non-representational states) are also central to understanding non-basic minds (with representational states). We argue that recent work on the free energy principle supports the following claims with respect to the life-mind continuity thesis: (i) there is a strong continuity between life (...) and mind; (ii) all living systems can be described as if they had representational states; (iii) the ’as-if representationality’ entailed by the free energy principle is central to understanding both basic forms of intentionality and intentionality in non-basic minds. In addition to this, we argue that the free energy principle also renders realism about computation and representation compatible with a strong life-mind continuity thesis (although the free energy principle does not entail computational and representational realism). In particular, we show how representationality proper can be grounded in ’as-if representationality’. (shrink)

Recent philosophical and empirical contributions strongly suggest that perception attributes determinable properties to its objects. But a characterisation of determinability via attributed properties is restricted to the level of content and does not capture the difference between perceptual belief and perception on this score. In this paper, I propose a formal way of cashing out the difference between determinable belief and perception. On the view presented here, determinability in perception distinctively involves homogeneous representation or representation that exhibits special sorts of (...) formal type variability. This formal characterisation, I suggest, goes beyond traditional approaches to analog representation and parallels a baseline notion of analog computation. (shrink)

Various theorists contend that we may live in a computer simulation. David Chalmers in turn argues that the simulation hypothesis is a metaphysical hypothesis about the nature of our reality, rather than a sceptical scenario. We use recent work on consciousness to motivate new doubts about both sets of arguments. First, we argue that if either panpsychism or panqualityism is true, then the only way to live in a simulation may be as brains-in-vats, in which case it is unlikely that (...) we live in a simulation. We then argue that if panpsychism or panqualityism is true, then viable simulation hypotheses are substantially sceptical scenarios. We conclude that the nature of consciousness has wide-ranging implications for simulation arguments. (shrink)

The feature-matching approach pioneered by Amos Tversky remains a groundwork for psychological models of similarity and categorization but is rarely explicitly justified considering recent advances in thinking about cognition. While psychologists often view similarity as an unproblematic foundational concept that explains generalization and conceptual thought, long-standing philosophical problems challenging this assumption suggest that similarity derives from processes of higher-level cognition, including inference and conceptual thought. This paper addresses three specific challenges to Tversky’s approach: (i) the feature-selection problem, (ii) the problem (...) of cognitive implausibility, and (iii) the problem of unprincipled tweaking. It subsequently supports key insights from Tversky’s account based on recent developments in Bayesian modeling of cognition. A novel computational view of similarity as inference is proposed that addresses each challenge by considering the contrast class as constitutive of similarity and selecting for highly informative features. In so doing, this view illustrates the ongoing promise of the feature-matching approach in explaining perception, generalization and conceptual thought by grounding them in principles of probabilistic inference. (shrink)

We begin by distinguishing computationalism from a number of other theses that are sometimes conflated with it. We also distinguish between several important kinds of computation: computation in a generic sense, digital computation, and analog computation. Then, we defend a weak version of computationalism—neural processes are computations in the generic sense. After that, we reject on empirical grounds the common assimilation of neural computation to either analog or digital computation, concluding that neural computation is sui generis. Analog computation requires continuous (...) signals; digital computation requires strings of digits. But current neuroscientific evidence indicates that typical neural signals, such as spike trains, are graded like continuous signals but are constituted by discrete functional elements (spikes); thus, typical neural signals are neither continuous signals nor strings of digits. It follows that neural computation is sui generis. Finally, we highlight three important consequences of a proper understanding of neural computation for the theory of cognition. First, understanding neural computation requires a specially designed mathematical theory (or theories) rather than the mathematical theories of analog or digital computation. Second, several popular views about neural computation turn out to be incorrect. Third, computational theories of cognition that rely on non-neural notions of computation ought to be replaced or reinterpreted in terms of neural computation. (shrink)

The debate about direct perception encompasses different topics, one of which concerns the richness of the contents of perceptual experiences. Can we directly perceive only low-level properties, like edges, colors etc., or can we perceive high-level properties and entities as well? The aim of the paper is to defend the claim that the content of our perceptual experience can include emotions and also person impressions. Using these examples, an argument is developed to defend a liberal-content view for core examples of (...) social cognition. This view is developed and contrasted with accounts which claim that in the case of registering another person’s emotion while seeing them, we have to describe the relevant content not as the content of a perceptual experience, but of a perceptual belief. The paper defends the view that perceptual experiences can have a rich content yet remain separable from beliefs formed on the basis of the experience. How liberal and enriched the content of a perceptual experience is will depend upon the expertise a person has developed in the field. This is supported by the argument that perceptual experiences can be systematically enriched by perceiving affordances of objects, by pattern recognition or by top-down processes, as analyzed by processes of cognitive penetration or predictive coding. (shrink)

Recently, a cottage industry has formed with the goal of analyzing reasoning. The relevant notion of reasoning in which philosophers are expressly interested is fixed through an epistemic functional description: reasoning—whatever it is—is our personal-level, rationally evaluable means of meeting our rational requirements through managing and updating our attitudes. Roughly, the dominant view in the extant literature as developed by Paul Boghossian, John Broome, and others is that reasoning is a rule-governed operation over propositional attitudes that results in a change (...) in attitude. In this paper, I argue that our personal-level operations over mental models and visuospatial imagery, which are representations in a non-propositional/analogue format, can be rationally evaluable processes of managing our attitudes and, thus, should be considered reasoning in the relevant sense. Furthermore, I show that if reasoning can occur through operations over mental models and imagery, then the dominant rule-following account mischaracterizes the cognitive operations and representational states assumed to be constitutive of reasoning and what grounds the rational status of a line of reasoning. (shrink)

Representation is typically taken to be importantly separate from its physical implementation. This is exemplified in Marr’s three-level framework, widely cited and often adopted in neuroscience. However, the separation between representation and physical implementation is not a necessary feature of information-processing systems. In particular, when it comes to analog computational systems, Marr’s representational/algorithmic level and implementational level collapse into a single level. Insofar as analog computation is a better way of understanding neural computation than other notions, Marr’s three-level framework must (...) then be amended into a two-level framework. However, far from being a problem or limitation, this sheds lights on how to understand physical media as being representational, but without a separate, medium-independent representational level. (shrink)

Computationalism about the brain is the view that the brain literally performs computations. For the view to be interesting, we need an account of computation. The most well-developed account of computation is Turing Machine computation, the account provided by theoretical computer science which provides the basis for contemporary digital computers. Some have thought that, given the seemingly-close analogy between the all-or-nothing nature of neural spikes in brains and the binary nature of digital logic, neural computation could be a species of (...) digital computation. A few recent authors have offered arguments against this idea; here, I review recent findings in neuroscience that further cement the implausibility of this view. However, I argue that we can retain the view that the brain is a computer if we expand what we mean by “computation” to include analog computation. I articulate an account of analog computation as the manipulation of analog representations based on previous work on the difference between analog and non-analog representations, extending a view originally articulated in Shagrir :271–279, 2010). Given that analog computation constitutes a significant chapter in the history of computation, this revision of computationalism to include analog computation is not an ad hoc addition. Brains may well be computers, but of the analog kind, rather than the digital kind. (shrink)

Current orthodoxy takes representation to be essential to computation. However, a philosophical account of computation that does not appeal to representation would be useful, given the difficulties involved in successfully theorizing representation. Piccinini's recent mechanistic account of computation proposes to do just that: it couches computation in terms of what certain mechanisms do without requiring the manipulation or processing of representations whatsoever (Piccinini 2015). Most crucially, mechanisms must process medium-independent vehicles. There are two ways to understand what "medium-independence" means on (...) this account; however, on either understanding, the account fails. Either too many things end up being counted as computational, or purportedly natural computations (e.g., neural computations) cannot be counted at all. In the end, illustrating this failure sheds some light on the way to revise the orthodoxy in the hope of a better account of computation. (shrink)

Perceptual representations are sometimes said to be iconic, or picture-like. But what does this mean, and is it true? I suggest that the most fruitful way to understand iconicity is in terms of similarity, but there are three importantly different grades of similarity that that might hold between perceptual representations and their objects, and these should be distinguished. It is implausible that all perceptual representations achieve even the weakest grade of iconicity, but I speculatively suggest a “Kantian” view, whereby all (...) perceptual representation involves fillers placed in a “strongly iconic” spatial framework. Those fillers will likely be hybrid structures, with varying grades of iconicity combined with non-iconic elements. (shrink)

An ongoing philosophical discussion concerns how various types of mental states fall within broad representational genera—for example, whether perceptual states are “iconic” or “sentential,” “analog” or “digital,” and so on. Here, I examine the grounds for making much more specific claims about how mental states are structured from constituent parts. For example, the state I am in when I perceive the shape of a mountain ridge may have as constituent parts my representations of the shapes of each peak and saddle (...) of the ridge. More specific structural claims of this sort are a guide to how mental states fall within broader representational kinds. Moreover, these claims have significant implications of their own about semantic, functional, and epistemic features of our mental lives. But what are the conditions on a mental state's having one type of constituent structure rather than another? Drawing on explanatory strategies in vision science, I argue that, other things being equal, the constituent structure of a mental state determines what I call its distributional properties—namely, how mental states of that type can, cannot, or must co‐occur with other mental states in a given system. Distributional properties depend critically on and are informative about the underlying structures of mental states, they abstract in important ways from aspects of how mental states are processed, and they can yield significant insights into the variegation of psychological capacities. (shrink)

Mental capacities for perceiving, remembering, thinking, and planning involve the processing of structured mental representations. A compositional semantics of such representations would explain how the content of any given representation is determined by the contents of its constituents and their mode of combination. While many have argued that semantic theories of mental representations would have broad value for understanding the mind, there have been few attempts to develop such theories in a systematic and empirically constrained way. This paper contributes to (...) that end by developing a semantics for a ‘fragment’ of our mental representational system: the visual system’s representations of the bounding contours of objects. At least three distinct kinds of composition are involved in such representations: ‘concatenation’, ‘feature composition’, and ‘contour composition’. I sketch the constraints on and semantics of each of these. This account has three principal payoffs. First, it models a working framework for compositionally ascribing structure and content to perceptual representations, while highlighting core kinds of evidence that bear on such ascriptions. Second, it shows how a compositional semantics of perception can be compatible with holistic, or Gestalt, phenomena, which are often taken to show that the whole percept is ‘other than the sum of its parts’. Finally, the account illuminates the format of a key type of perceptual representation, bringing out the ways in which contour representations exhibit domain-specific form of the sort that is typical of structured icons such as diagrams and maps, in contrast to typical discursive representations of logic and language. (shrink)

Nelson Goodman’s theory of symbol systems expounded in his Languages of Art has been frequently criticized on many counts. Yet it exerts a strong influence and is treated as one of the major twentieth-century theories on the subject.While many of Goodman’s controversial theses are criticized, the technical notions he used to formulate them seem to have been treated as neutral tools. One such technical notion is that of the density of symbol systems. This serves to distinguish linguistic symbols from pictorial (...) representations and is a crucial part of Goodman’s explanation of what constitutes aesthetic experience. Thus its significance for Goodman’s theory is fundamental.The aim of this paper is a detailed, logical analysis of this notion. It turns out that Goodman’s definition is highly problematic and cannot be applied to symbol systems in the way Goodman envisaged. To conclude, Goodman’s theory is problematic not just because of its controversial theses but also because of logical problems with the technical notions used at its very core. Hence the controversial claims are not simply contestable, but inaccurately expressed. (shrink)

This paper explores the idea that vague predicates like “tall”, “loud” or “expensive” are applied based on a process of analog magnitude representation, whereby magnitudes are represented with noise. I present a probabilistic account of vague judgment, inspired by early remarks from E. Borel on vagueness, and use it to model judgments about borderline cases. The model involves two main components: probabilistic magnitude representation on the one hand, and a notion of subjective criterion. The framework is used to represent judgments (...) of the form “x is clearly tall” versus “x is tall”, as involving a shift of one’s criterion, and then to derive observed patterns of acceptance for borderline contradictions, namely sentences of the form “x is tall and not tall”, relative to the acceptance of their conjuncts. (shrink)

There has been an ongoing conflict regarding whether reality is fundamentally digital or analogue. Recently, Floridi has argued that this dichotomy is misapplied. For any attempt to analyse noumenal reality independently of any level of abstraction at which the analysis is conducted is mistaken. In the pars destruens of this paper, we argue that Floridi does not establish that it is only levels of abstraction that are analogue or digital, rather than noumenal reality. In the pars construens of this paper, (...) we reject a classification of noumenal reality as a deterministic discrete computational system. We show, based on considerations from classical physics, why a deterministic computational view of the universe faces problems (e.g., a reversible computational universe cannot be strictly deterministic). (shrink)

Dynamical systems theory (DST) is a branch of mathematics that assesses abstract or physical systems that change over time. It has a quantitative part (mathematical equations) and a related qualitative part (plotting equations in a state space). Nonlinear dynamical systems theory applies the same tools in research involving phenomena such as chaos and hysteresis. These approaches have provided different ways of investigating and understanding cognitive systems in cognitive science and neuroscience. The ‘dynamical hypothesis’ claims that cognition is and can be (...) understood as dynamical systems. Common consequences for such an approach include rejecting understanding cognition as information processing in nature, including eschewing explanatory roles for computation or representation. Contemporary applications of DST include mouse‐tracking studies in cognitive science and nonrepresentational perspectives on motor control in neuroscience. Such work has philosophical implications concerning the boundaries of cognition, explanation, and representations. DST offers powerful methodology and theories that raise many topics of philosophical significance. (shrink)

This paper presents a theoretical study of the binary oppositions underlying the mechanisms of natural computation understood as dynamical processes on natural information morphologies. Of special interest are the oppositions of discrete vs. continuous, structure vs. process, and differentiation vs. integration. The framework used is that of computing nature, where all natural processes at different levels of organisation are computations over informational structures. The interactions at different levels of granularity/organisation in nature, and the character of the phenomena that unfold through (...) those interactions, are modeled from the perspective of an observing agent. This brings us to the movement from binary oppositions to dynamic networks built upon mutually related binary oppositions, where each node has several properties. (shrink)

On a now orthodox view, humans and many other animals possess a “number sense,” or approximate number system, that represents number. Recently, this orthodox view has been subject to numerous critiques that question whether the ANS genuinely represents number. We distinguish three lines of critique – the arguments from congruency, confounds, and imprecision – and show that none succeed. We then provide positive reasons to think that the ANS genuinely represents numbers, and not just non-numerical confounds or exotic substitutes for (...) number, such as “numerosities” or “quanticals,” as critics propose. In so doing, we raise a neglected question: numbers of what kind? Proponents of the orthodox view have been remarkably coy on this issue. But this is unsatisfactory since the predictions of the orthodox view, including the situations in which the ANS is expected to succeed or fail, turn on the kind of number being represented. In response, we propose that the ANS represents not only natural numbers, but also non-natural rational numbers. It does not represent irrational numbers, however, and thereby fails to represent the real numbers more generally. This distances our proposal from existing conjectures, refines our understanding of the ANS, and paves the way for future research. (shrink)

Digital physics claims that the entire universe is, at the very bottom, made out of bits; as a result, all physical processes are intrinsically computational. For that reason, many digital physicists go further and affirm that the universe is indeed a giant computer. The aim of this article is to make explicit the ontological assumptions underlying such a view. Our main concern is to clarify what kind of properties the universe must instantiate in order to perform computations. We analyse the (...) logical form of the two models of computation traditionally adopted in digital physics, namely, cellular automata and Turing machines. These models are computationally equivalent, but we show that they support different ontological commitments about the fundamental properties of the universe. In fact, cellular automata are compatible with a rather traditional form of physicalism, whereas Turing machines support a dualistic ontology, which could be understood as a realism about the laws of nature or, alternatively, as a kind of panpsychism. (shrink)

Empirical discussions of mental representation appeal to a wide variety of representational kinds. Some of these kinds, such as the sentential representations underlying language use and the pictorial representations of visual imagery, are thoroughly familiar to philosophers. Others have received almost no philosophical attention at all. Included in this latter category are analogue magnitude representations, which enable a wide range of organisms to primitively represent spatial, temporal, numerical, and related magnitudes. This article aims to introduce analogue magnitude representations to a (...) philosophical audience by rehearsing empirical evidence for their existence and analysing their format, their content, and the computations they support. 1 Background1.1 Evidence of analogue magnitude representations1.2 Weber’s law1.3 Scepticism about analogue magnitude representations2 Format2.1 Carey’s analogy2.2 Neural realization2.3 Analogue representation2.4 Analogue magnitude representation components3 Content3.1 Do analogue magnitude representations have representational content?3.2 What do analogue magnitude representations represent?3.3 What content types do analogue magnitude representations have?4 Computations4.1 Arithmetic computation4.2 Practical deliberation5 Conclusion. (shrink)

This article argues that if panpsychism is true, then there are grounds for thinking that digitally-based artificial intelligence may be incapable of having coherent macrophenomenal conscious experiences. Section 1 briefly surveys research indicating that neural function and phenomenal consciousness may be both analog in nature. We show that physical and phenomenal magnitudes—such as rates of neural firing and the phenomenally experienced loudness of sounds—appear to covary monotonically with the physical stimuli they represent, forming the basis for an analog relationship between (...) the three. Section 2 then argues that if this is true and micropsychism—the panpsychist view that phenomenal consciousness or its precursors exist at a microphysical level of reality—is also true, then human brains must somehow manipulate fundamental microphysical-phenomenal magnitudes in an analog manner that renders them phenomenally coherent at a macro level. However, Sect. 3 argues that because digital computation abstracts away from microphysical-phenomenal magnitudes—representing cognitive functions non-monotonically in terms of digits—digital computation may be inherently incapable of realizing coherent macroconscious experience. Thus, if panpsychism is true, digital AI may be incapable of achieving phenomenal coherence. Finally, Sect. 4 briefly examines our argument’s implications for Tononi’s Integrated Information Theory theory of consciousness, which we contend may need to be supplanted by a theory of macroconsciousness as analog microphysical-phenomenal information integration. (shrink)

(Penultimate draft) Embodied Cognition holds that bodily (e.g. sensorimotor) states and processes are directly involved in some higher-level cognitive functions (e.g. reasoning). This challenges traditional views of cognition according to which bodily states and processes are, at most, indirectly involved in higher-level cognition. Although some elements of Embodied Cognition have been integrated into mainstream cognitive science, others still face adamant resistance. In this paper, rather than straightforwardly defend Embodied Cognition against specific objections I will do the following. First, I will (...) present a concise account of embodied conceptual processing and highlight some of its advantages over non-embodied accounts, specifically focusing on the role of metaphors. Second, I will detail the influence of computational metaphors on theories of cognition and evaluation of these theories. Third, I will argue that embodied cognitive mechanisms, specifically those operating through computational metaphors, may drive some of the resistance to Embodied Cognition - and that Embodied Cognition is able to offer a uniquely compelling account of this. Ultimately, this will contribute to an improved understanding of Embodied Cognition, its explanatory power, and how it ought to be evaluated. Additionally, it will shed light on the role of metaphors in shaping philosophical thought and highlight the importance of these influences. (shrink)

The paper attempts to describe a kind of transformation of the way we represent the world in the digital age. Starting from the definition of a precise meaning of “the term "digital", a conceptualisation of digital representation is proposed based on some moments of Immanuel Kant’s thought and concluded with some current reflections.

This dissertation examines aspects of the interplay between computing and scientific practice. The appropriate foundational framework for such an endeavour is rather real computability than the classical computability theory. This is so because physical sciences, engineering, and applied mathematics mostly employ functions defined in continuous domains. But, contrary to the case of computation over natural numbers, there is no universally accepted framework for real computation; rather, there are two incompatible approaches --computable analysis and BSS model--, both claiming to formalise algorithmic (...) computation and to offer foundations for scientific computing. The dissertation consists of three parts. In the first part, we examine what notion of 'algorithmic computation' underlies each approach and how it is respectively formalised. It is argued that the very existence of the two rival frameworks indicates that 'algorithm' is not one unique concept in mathematics, but it is used in more than one way. We test this hypothesis for consistency with mathematical practice as well as with key foundational works that aim to define the term. As a result, new connections between certain subfields of mathematics and computer science are drawn, and a distinction between 'algorithms' and 'effective procedures' is proposed. In the second part, we focus on the second goal of the two rival approaches to real computation; namely, to provide foundations for scientific computing. We examine both frameworks in detail, what idealisations they employ, and how they relate to floating-point arithmetic systems used in real computers. We explore limitations and advantages of both frameworks, and answer questions about which one is preferable for computational modelling and which one for addressing general computability issues. In the third part, analog computing and its relation to analogue (physical) modelling in science are investigated. Based on some paradigmatic cases of the former, a certain view about the nature of computation is defended, and the indispensable role of representation in it is emphasized and accounted for. We also propose a novel account of the distinction between analog and digital computation and, based on it, we compare analog computational modelling to physical modelling. It is concluded that the two practices, despite their apparent similarities, are orthogonal. (shrink)

Why think that conscious experience of reality is any more epistemically valuable than testimony about it? I argue that conscious experience of reality is epistemically valuable because it provides cognitive contact with reality. Cognitive contact with reality is a goal of experiential inquiry which does not reduce to the goal of getting true beliefs or propositional knowledge. Such inquiry has awareness of the truth-makers of one’s true beliefs as its proper goal. As such, one reason why conscious experience of reality (...) is more epistemically valuable than testimony about reality is that it gives us more epistemic goods than only true belief or propositional knowledge. I defend this view from two rival accounts. First, that while conscious experience of reality has greater value than testimony, its value is only eudaimonic. Second, that while it has greater epistemic value than testimony, this value is not distinctive: for it only promotes truth better than testimony. (shrink)

This paper provides the first systematic philosophical analysis of an increasingly important part of modern scientific practice: analogue quantum simulation. We introduce the distinction between `simulation' and `emulation' as applied in the context of two case studies. Based upon this distinction, and building upon ideas from the recent philosophical literature on scientific understanding, we provide a normative framework to isolate and support the goals of scientists undertaking analogue quantum simulation and emulation. We expect our framework to be useful to both (...) working scientists and philosophers of science interested in cutting-edge scientific practice. (shrink)

This dissertation examines aspects of the interplay between computing and scientific practice. The appropriate foundational framework for such an endeavour is rather real computability than the classical computability theory. This is so because physical sciences, engineering, and applied mathematics mostly employ functions defined in continuous domains. But, contrary to the case of computation over natural numbers, there is no universally accepted framework for real computation; rather, there are two incompatible approaches --computable analysis and BSS model--, both claiming to formalise algorithmic (...) computation and to offer foundations for scientific computing. -/- The dissertation consists of three parts. In the first part, we examine what notion of 'algorithmic computation' underlies each approach and how it is respectively formalised. It is argued that the very existence of the two rival frameworks indicates that 'algorithm' is not one unique concept in mathematics, but it is used in more than one way. We test this hypothesis for consistency with mathematical practice as well as with key foundational works that aim to define the term. As a result, new connections between certain subfields of mathematics and computer science are drawn, and a distinction between 'algorithms' and 'effective procedures' is proposed. -/- In the second part, we focus on the second goal of the two rival approaches to real computation; namely, to provide foundations for scientific computing. We examine both frameworks in detail, what idealisations they employ, and how they relate to floating-point arithmetic systems used in real computers. We explore limitations and advantages of both frameworks, and answer questions about which one is preferable for computational modelling and which one for addressing general computability issues. -/- In the third part, analog computing and its relation to analogue (physical) modelling in science are investigated. Based on some paradigmatic cases of the former, a certain view about the nature of computation is defended, and the indispensable role of representation in it is emphasized and accounted for. We also propose a novel account of the distinction between analog and digital computation and, based on it, we compare analog computational modelling to physical modelling. It is concluded that the two practices, despite their apparent similarities, are orthogonal. (shrink)

The essay is a study of phenomenal specificity. By ‘phenomenal’ here we mean conscious awareness, which needs to be cashed out in detail throughout the study. Intuitively, one dimension of phenomenology is along with specificity. For example it seems appropriate to say that one’s conscious awareness in the middle of the visual field is in some sense more specific than the awareness in the periphery under normal circumstances. However, it is difficult to characterise the nature of phenomenal specificity in an (...) accurate way. This essay seeks to do just that. In the introduction, I set up the discussion by invoking a threefold Campbellian framework. Chapter 1 introduces a key notion of the analogue, its roots in sciences, and its applications in philosophy. Chapter 2 focuses on the major case study – the Sperling iconic memory paradigm – and explains how the relevant notion of the analogue can be used to explain phenomenal specificity involved in the Sperling case. Chapter 3 discusses functions of attention, as it is a crucial element in the Sperling case. Chapter 4 extends the project by explaining how visual demonstratives fit into the present picture. Finally chapter 5 discusses several directions for future researches. This essay is not an attempt to discuss all the issues concerning the Sperling case, but to provide a new angle in seeing the issue: most people agree that visual phenomenology is in some sense specific, but there are not enough attempts to model phenomenal specificity explicitly. On this occasion we use a notion of the analogue and related ideas to understand phenomenal specificity and how it applies to certain empirical cases. (shrink)

The distinction between the discrete and the continuous lies at the heart of mathematics. Discrete mathematics (arithmetic, algebra, combinatorics, graph theory, cryptography, logic) has a set of concepts, techniques, and application areas largely distinct from continuous mathematics (traditional geometry, calculus, most of functional analysis, differential equations, topology). The interaction between the two – for example in computer models of continuous systems such as fluid flow – is a central issue in the applicable mathematics of the last hundred years. This article (...) explains the distinction and why it has proved to be one of the great organizing themes of mathematics. (shrink)

Alan Turing’s pioneering work on computability, and his ideas on morphological computing support Andrew Hodges’ view of Turing as a natural philosopher. Turing’s natural philosophy differs importantly from Galileo’s view that the book of nature is written in the language of mathematics (The Assayer, 1623). Computing is more than a language used to describe nature as computation produces real time physical behaviors. This article presents the framework of Natural info-computationalism as a contemporary natural philosophy that builds on the legacy of (...) Turing’s computationalism. The use of info-computational conceptualizations, models and tools makes possible for the first time in history modeling of complex self-organizing adaptive systems, including basic characteristics and functions of living systems, intelligence, and cognition. (shrink)