Although there is a substantial philosophical literature on dynamical systems theory in the cognitive sciences, the same is not the case for neuroscience. This paper attempts to motivate increased discussion via a set of overlapping issues. The first aim is primarily historical and is to demonstrate that dynamical systems theory is currently experiencing a renaissance in neuroscience. Although dynamical concepts and methods are becoming increasingly popular in contemporary neuroscience, the general approach should not be viewed as something entirely new to (...) neuroscience. Instead, it is more appropriate to view the current developments as making central again approaches that facilitated some of neuroscience’s most significant early achievements, namely, the Hodgkin–Huxley and FitzHugh–Nagumo models. The second aim is primarily critical and defends a version of the “dynamical hypothesis” in neuroscience. Whereas the original version centered on defending a noncomputational and nonrepresentational account of cognition, the version I have in mind is broader and includes both cognition and the neural systems that realize it as well. In view of that, I discuss research on motor control as a paradigmatic example demonstrating that the concepts and methods of dynamical systems theory are increasingly and successfully being applied to neural systems in contemporary neuroscience. More significantly, such applications are motivating a stronger metaphysical claim, that is, understanding neural systems as being dynamical systems, which includes not requiring appeal to representations to explain or understand those phenomena. Taken together, the historical claim and the critical claim demonstrate that the dynamical hypothesis is undergoing a renaissance in contemporary neuroscience. (shrink)

Advances in artificial intelligence and robotics stand to change many aspects of our lives, including our values. If trends continue as expected, many industries will undergo automation in the near future, calling into question whether we can still value the sense of identity and security our occupations once provided us with. Likewise, the advent of social robots driven by AI, appears to be shifting the meaning of numerous, long-standing values associated with interpersonal relationships, like friendship. Furthermore, powerful actors’ and institutions’ (...) increasing reliance on AI to make decisions that may affect how people live their lives may have a significant impact on privacy while also raising issues about algorithmic transparency and human control. In this paper, building and expanding on previous works, we will look at how the deployment of Artificial Intelligence technology may lead to changes in identity, security, and other crucial values. We will discuss what challenges we may face in the process, while critically reflecting on whether such changes may be desirable. Finally, drawing on a series of considerations underlying virtue ethics, we will formulate a set of preliminary suggestions, which—we hope—can be used to more carefully guide the future roll out of AI technologies for human flourishing; that is, for social and moral good. (shrink)

There has been debate between those who maintain that indexical expressions are not essential and those who maintain that such indexicals cannot be dispensed with without an important loss of content. This version of the essentialist view holds that thoughts must also have indexical elements. Indexical thoughts appear to be in tension with the computational theory of mind. In this case we have the following inconsistent triad: De se thoughts are essential. De se thoughts are indexical, they have a character. (...) Computations can only take the syntactic type into account, they cannot take tokens into account. If is correct, then it seems we cannot make sense of a thought which uses a character such that its referent could vary from tokening to tokening. I argue that need not cause a problem, while maintaining the CTM. I claim that computations need not be sensitive to the features of a tokened symbol in the way that character demands. This job may be performed by a non‐modular part of the mind. Resolving the triad in this way provides a reason to accept that indexicals in thought are possible. (shrink)

To account for the explanatory role representations play in cognitive science, Egan’s deflationary account introduces a distinction between cognitive and mathematical contents. According to that account, only the latter are genuine explanatory posits of cognitive-scientific theories, as they represent the arguments and values cognitive devices need to represent to compute. Here, I argue that the deflationary account suffers from two important problems, whose roots trace back to the introduction of mathematical contents. First, I will argue that mathematical contents do not (...) satisfy important and widely accepted desiderata all theories of content are called to satisfy, such as content determinacy and naturalism. Secondly, I will claim that there are cases in which mathematical contents cannot play the explanatory role the deflationary account claims they play, proposing an empirical counterexample. Lastly, I will conclude the paper highlighting two important implications of my arguments, concerning recent theoretical proposals to naturalize representations via physical computation, and the popular predictive processing theory of cognition. (shrink)

Enactive approaches to cognition argue that cognition, including pretense, comes about through the dynamical interaction of agent and environment. Applied to cognition, these approaches cast cognition as an activity an agent _performs_ interacting in specific ways with her environment. This view is now under significant pressure: in a series of recent publications, Peter Langland-Hassan has proposed a number of arguments which purportedly should lead us to conclude that enactive approaches are unable to account for pretense without paying a way too (...) severe theoretical price. In this paper, we will defend enactive approaches to pretense, arguing that they can in fact explain pretense without incurring in the negative theoretical consequences Peter Langland-Hassan fears. To this effect, we start by exposing Langland-Hassan’s challenge (§2), to then highlight its core assumptions and demonstrate their falsity (§3). Having done so, we argue that none of the theoretical consequences Langland-Hassan fears follow (§4), and in fact enactive approaches to cognition may be explanatorily superior to the one Langland-Hassan favors (§5). A brief conclusion will then follow (§6). (shrink)

Attempts to apply the mathematical tools of dynamical systems theory to cognition in a systematic way has been well under way since the early 90s and has been recognised as a “third contender” to computationalist and connectionist approaches :441–463, 1996). Nevertheless, it was also realised that such an application will not lead to a solid paradigm as straightforwardly as was initially hoped. In this paper I explicate a method for assessing such proposals by drawing upon Lakatos’s Criticism and the growth (...) of knowledge, Cambridge University Press, London, pp 91–195, 1970) methodology of scientific research programs. MSRP focuses on the heuristics of a particular field and gauges the model/theory building stratagems by reference to theoretical and empirical progress, on the one hand, and the continuity and the autonomy of the way the field’s heuristic generates its series of models/theories, on the other. The requirement of continuity and autonomy afford distinct senses of ad hoc-ness, which serve as an effective tool to detect various subtleties which may otherwise be missed: the present approach identifies shortcomings missed by Chemero’s radical embodied cognitive science and falsifies Chemero’s claim that the methodological powers of his model-based account is on a par with computationalism. In general, I claim that MSRP is relevant to current methodological issues in cognitive science and can supplement debates regarding “local” assessments of methodologies, such as that between mechanical versus covering-law explanations. MSRP must at least be viewed as a necessary constraint for any methodological considerations in cognitive science. (shrink)

Following Gilbert Ryle’s arguments, many philosophers took it for granted that someone knows how to do something just in case they have the ability to do it. Within the last couple decades, new intellectualists have challenged this longstanding anti-intellectualist assumption. Their central contention is that mere abilities aren’t on the same rational, epistemic level as know how. My goal is to intellectualize know how without over-intellectualizing it. Intelligent behavior is characteristically flexible or responsive to novelty, and the distinctive feature of (...) creatures who exhibit flexible behavior is their capacity to learn. As it turns out, Ryle already identified a core characteristic of learning shared widely across the animal kingdom from the lowly rat to the top athlete. Taking my cues from Ryle, I argue that know how is successful performance resulting from self-regulated abilities. To regulate an ability is to be disposed to adjust to error and respond to feedback. While regulating sophisticated human abilities often requires propositional knowledge, in many simpler cases it does not. I focus on the navigational know how of rats and honeybees. Although they possess know how, whether they possess propositional knowledge is at best an open question. (shrink)

Following Gilbert Ryle’s arguments, many philosophers took it for granted that someone knows how to do something just in case they have the ability to do it. Within the last couple decades, new intellectualists have challenged this longstanding anti-intellectualist assumption. Their central contention is that mere abilities aren’t on the same rational, epistemic level as know how. My goal is to intellectualize know how without over-intellectualizing it. Intelligent behavior is characteristically flexible or responsive to novelty, and the distinctive feature of (...) creatures who exhibit flexible behavior is their capacity to learn. As it turns out, Ryle already identified a core characteristic of learning shared widely across the animal kingdom from the lowly rat to the top athlete. Taking my cues from Ryle, I argue that know how is successful performance resulting from self-regulated abilities. To regulate an ability is to be disposed to adjust to error and respond to feedback. While regulating sophisticated human abilities often requires propositional knowledge, in many simpler cases it does not. I focus on the navigational know how of rats and honeybees. Although they possess know how, whether they possess propositional knowledge is at best an open question. (shrink)

The implicit content indicating location associated with “raining” and other weather predicates is a definite description meaning “the location occupied by x,” where the individual variable “x” can be referential or bound. This position has deleterious consequences for certain varieties of radical contextualism.

It is generally accepted that, in the cognitive and neural sciences, there are both computational and mechanistic explanations. We ask how computational explanations can integrate into the mechanistic hierarchy. The problem stems from the fact that implementation and mechanistic relations have different forms. The implementation relation, from the states of an abstract computational system to the physical, implementing states is a homomorphism mapping relation. The mechanistic relation, however, is that of part/whole; the explaining features in a mechanistic explanation are the (...) components of the explanandum phenomenon and their causal organization. Moreover, each component in one level of mechanism is constituted and explained by components of an underlying level of mechanism. Hence, it seems, computational variables and functions cannot be mechanistically explained by the medium-dependent states and properties that implement them. How then, do the computational and the implementational integrate to create the mechanistic hierarchy? After explicating the general problem, we further demonstrate it through a concrete example, of reinforcement learning, in the cognitive and neural sciences. We then examine two possible solutions. On one solution, the mechanistic hierarchy embeds at the same levels computational and implementational properties. This picture fits with the view that computational explanations are mechanistic sketches. On the other solution, there are two separate hierarchies, one computational and another implementational, which are related by the implementation relation. This picture fits with the view that computational explanations are functional and autonomous explanations. It is less clear how these solutions fit with the view that computational explanations are full-fledged mechanistic explanations. Finally, we argue that both pictures are consistent with the reinforcement learning example, but that scientific practice does not align with the view that computational models are merely mechanistic sketches. (shrink)

Richard Heersmink argues that self‐narratives are distributed across embodied organisms and their environment, given that their building blocks, autobiographical memories, are distributed. This argument faces two problems. First, it commits a fallacy of composition. Second, it relies on Marya Schechtman's narrative self‐constitution view, which is incompatible with the distributed cognition framework. To solve these problems, this article develops an alternative account of self‐narratives. On this account, we actively connect distributed autobiographical memories through distributed conversational and textual self‐narrative practices. This account (...) enhances our understanding of the memory–narrative nexus and has implications for philosophical conceptions of self. (shrink)

Traditional arguments against the identification of the language of thought with natural language assume a picture of natural language which is largely inconsistent with that suggested by contemporary linguistic theory. This has led certain philosophers and linguists to suggest that this identification is not as implausible as it once seemed. In this paper, I discuss the prospects for such an identification in light of these developments in linguistic theory. I raise a new challenge against the identification thesis: the existence of (...) ungrammatical but acceptable expressions seems to require a gap between thought and language. I consider what must be the case in order for this objection to be dealt with. (shrink)

Language has long been a problem‐case for subsymbolic theories of mind. The reason for this is obvious: Language seems essentially symbolic. However, recent work has developed a potential solution to this problem, arguing that linguistic symbols are public objects which augment a fundamentally subsymbolic mind, rather than components of cognitive symbol‐processing. I shall argue that this strategy cannot work, on the grounds that human language acquisition consists in projecting linguistic structure onto environmental entities, rather than extracting this structure from them.

Generative grammarians typically advocate for a rationalist understanding of language acquisition, according to which the structure of a developed language faculty reflects innate guidance rather than environmental influence. This proposal is developed in developmental linguistics by triggering models of language acquisition. Opposing this tradition, various theorists have advocated for empiricist views of language acquisition, according to which the structure of a developed linguistic competence reflects the linguistic environment in which this competence developed. On this picture, linguistic development is accounted for (...) by general statistical learning mechanisms. In this article I shall precisify the debate, provide a clearer picture of what is at stake, and show why an intermediate picture is needed. (shrink)

One of the main dividing lines within the debate on the problem of consciousness comes between representationalist separatism and phenomenalist inseparatism. According to the former, representational mental states are possible in the absence of phenomenal consciousness, and furthermore, an adequate naturalistic theory of representation is necessary and sufficient for the explanation of phenomenal consciousness. According to the later, phenomenal consciousness is necessary for the existence and the explanation of any representational state and, indeed, of any mental state. Several arguments have (...) tried to offer support to this inseparatist thesis. Those proposed by Galen Strawson and John Searle summarize this kind of argument, which is based on the introduction of implicit premises. In addition to this failure, inseparatism faces the problems of its empirical inoperativeness and inadequacy, as well as its lack of phylogenetic verisimilitude. (shrink)

Polanyi and Transhumanism both place technologies in pivotal roles in bringing about Homo sapiens ’ species transitions. The question is asked whether Polanyi’s emphasis on the role of technology in Homo sapiens’ rise out of mute beasthood indicates that he might have been inclined to embrace the Transhumanist vision of Homo sapiens’ technological evolution into a postbiological, techno-cyber species. To answer this question, some of the core commitments of both Transhumanism and Polanyi’s postcritical philosophy are examined, especially as they bear (...) on Homo sapiens’ species transitions. The conclusion reached is that rather than being the next step dictated by the inner logic of Polanyi’s thought, Transhumanism is actually the final conclusion of epistemological ideals he spent most of his career denouncing. (shrink)

Human languages vary in terms of which meanings they lexicalize, but this variation is constrained. It has been argued that languages are under two competing pressures: the pressure to be simple (e.g., to have a small lexicon) and to allow for informative (i.e., precise) communication, and that which meanings get lexicalized may be explained by languages finding a good way to trade off between these two pressures. However, in certain semantic domains, languages can reach very high levels of informativeness even (...) if they lexicalize very few meanings in that domain. This is due to productive morphosyntax and compositional semantics, which may allow for construction of meanings which are not lexicalized. Consider the semantic domain of natural numbers: many languages lexicalize few natural number meanings as monomorphemic expressions, but can precisely convey very many natural number meanings using morphosyntactically complex numerals. In such semantic domains, lexicon size is not in direct competition with informativeness. What explains which meanings are lexicalized in such semantic domains? We will propose that in such cases, languages need to solve a different kind of trade‐off problem: the trade‐off between the pressure to lexicalize as few meanings as possible (i.e, to minimize lexicon size) and the pressure to produce as morphosyntactically simple utterances as possible (i.e, to minimize average morphosyntactic complexity of utterances). To support this claim, we will present a case study of 128 natural languages' numeral systems, and show computationally that they achieve a near‐optimal trade‐off between lexicon size and average morphosyntactic complexity of numerals. This study in conjunction with previous work on communicative efficiency suggests that languages' lexicons are shaped by a trade‐off between not two but three pressures: be simple, be informative, and minimize average morphosyntactic complexity of utterances. (shrink)

We examine schoolchildren’s reasoning with spatial relations, such as ‘is to the left of’. Our aims are to obtain a more precise account of the effect of working memory on reasoning, a more detaile...

Fodor argued that learning a concept by hypothesis testing would involve an impossible circularity. I show that Fodor's argument implicitly relies on the assumption that actually φ-ing entails an ability to φ. But this assumption is false in cases of φ-ing by luck, and just such luck is involved in testing hypotheses with the kinds of generative random sampling methods that many cognitive scientists take our minds to use. Concepts thus can be learned by hypothesis testing without circularity, and it (...) is plausible that this is how humans in fact acquire at least some of their concepts. (shrink)

Embodied cognition: assumptions, theses and challenges: The paper aims at providing a concise presentation of the concept of embodied cognition that emerged in the cognitive sciences a few decades ago and has gained great popularity among empirically and philosophically informed researchers. The term “embodied cognition” is used by the author in two senses. The narrow sense implies that the body plays an important role in the process of cognition. In the broad sense “embodied cognition” is to characterize the general tendency (...) within cognitive science which finds its articulation in the 4E perspective on cognition. The working hypothesis of the 4E perspective is that cognition depends on the characteristics of the agent’s body and its interaction with the physical and social environment. It emphasizes that cognition is: embodied, embedded, enacted, extended. After reconstructing the key concepts and basic assumptions the author offers a brief appraisal of the views under discussion. He claims that the characteristics of such a trend are incomplete and not homogeneity since the perspective encompasses at least a few related and partly overlapping views on cognition. The author concludes that “embodied cognition” serves as a label for a variety of research programs within cognitive science rather than a strictly defined and well-established research tradition or a new paradigm. (shrink)

According to act theories, propositions are structured cognitive act‐types. Act theories appear to make propositions inherently representational and truth‐evaluable, and to provide solutions to familiar problems with alternative theories, including Frege’s and Russell’s problems, and the third‐realm and unity problems. Act theories have critical problems of their own, though: acts as opposed to their objects are not truth evaluable, not structured in the right way, not expressed by sentences, and not the objects of propositional attitudes. I show how identifying propositions (...) with other cognitive event‐types, namely thoughts, has the perceived virtues of act theories without the defects. (shrink)

One of the claims of Type Theory with Records is that it can be used to model types learned by agents in order to classify objects and events in the world, including speech events. That is, the types can be represented by patterns of neural activation in the brain. This claim would be empty if it turns out that the types are in principle impossible to represent on a finite network of neurons. We will discuss how to represent types in (...) terms of neural events on a network and present a preliminary computational implementation that maps types to events on a network. The kind of networks we will use are closely related to the transparent neural networks discussed by Strannegård. (shrink)

Where does a probabilistic language-of-thought (PLoT) come from? How can we learn new concepts based on probabilistic inferences operating on a PLoT? Here, I explore these questions, sketching a traditional circularity objection to LoT and canvassing various approaches to addressing it. I conclude that PLoT-based cognitive architectures can support genuine concept learning; but, currently, it is unclear that they enjoy more explanatory breadth in relation to concept learning than alternative architectures that do not posit any LoT.

The notion of intelligence is relevant to several fields of research, including cognitive and comparative psychology, neuroscience, artificial intelligence, and philosophy, among others. However, there is little agreement within and across these fields on how to characterise and explain intelligence. I put forward a behavioural, operational characterisation of intelligence that can play an integrative role in the sciences of intelligence, as well as preserve the distinctive explanatory value of the notion, setting it apart from the related concepts of cognition and (...) rationality. Finally, I examine a popular hypothesis about the underpinnings of intelligence: the capacity to manipulate internal representations of the environment. I argue that the hypothesis needs refinement, and that so refined, it applies only to some forms of intelligence. (shrink)

Is the mind flat? Chater (2018) has recently argued that it is and that, contrary to traditional psychology and standard folk image, depth of mind is just an illusory confabulation. In this paper, we argue that while there is a kernel of something correct in Chater’s thesis, this does not in itself add up to a critique of mental depth per se. We use Chater’s ideas as a springboard for creating a new understanding of mental depth which builds upon findings (...) in contemporary cognitive science. First, we rely on the predictive processing framework in order to determine a proposed neural contribution to mental depth, specifically in hierarchical predictive knowledge. Second, drawing from an embodied approach to cognition, we argue that mental depth results from the depth of our embodied skills and the situations in which we are embedded. This allows us to introduce to a new realist notion of mental depth, one which can only be explained once we attend to the dense patterns of skillful interaction within a rich artefactual and social environment. (shrink)

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 target article argues that language-of-thought hypothesis (LoTH) is applicable to various domains, including perception. However, it focusses exclusively on the visual case, which is limited in this regard. I argue for two ideas in this commentary: first, their case can be extended to other modalities such as touch; and second, the status of those six criteria needs to be further clarified.

Johnson et al. make a persuasive case that qualitative, story-like reasoning plays a crucial role in everyday thought and decision-making. This commentary questions the cohesiveness of this type of reasoning and the representations that generate it. Perhaps narratives do not underpin, but are ephemeral products of thought, created when we need to justify our actions to ourselves and others.

There are two versions of the language-of-thought hypothesis (LOT): Representational LOT (roughly, structured representation), introduced by Ockham, and computational LOT (roughly, symbolic computation) introduced by Fodor. Like many others, I oppose the latter but not the former. Quilty-Dunn et al. defend representational LOT, but they do not defend the strong computational LOT thesis central to the classical-connectionist debate.

Quilty-Dunn et al. defended the reemergence of language-of-thought hypothesis (LoTH). My commentary builds up implications for the study of the development of our logical capacities. Empirical support for logically augmented LoT systems calls for the investigation of their logical primitives and developmental origin. Furthermore, Quilty-Dunn et al.'s characterization of LoT helps the quest for the foundation of logic by dissociating logical cognition from natural language.

In recent years, there has been a renewed concern about the dangers of eliminative materialism, as well as several attempts to discuss alternative positions such as new versions of interpretivism or fictionalism. Although expressivism has also emerged as a possibility, the problems with hybrid versions of expressivism in applying it to attitude ascriptions have led to a strong rejection of the proposal. The aim of this article is twofold. First, it argues that there are still theoretical tools available to defend (...) an expressivist analysis of mental state ascriptions. Second, the article contends that three of the most influential arguments in expressivism in meta-ethics and meta-epistemology are applicable to the case of mental state ascriptions. (shrink)

Many think that expressivists have a special problem with negation. I disagree. For if there is a problem with negation, I argue, it is a problem shared by those who accept some plausible claims about the nature of intentionality. Whether there is any special problem for expressivists turns, I will argue, on whether facts about what truth-conditions beliefs have can explain facts about basic inferential relations among those beliefs. And I will suggest that the answer to this last question is, (...) on most plausible attempts at solving the problem of intentionality, ‘no’. (shrink)

In order to argue that cognitive science should be more accepting of explanatory plurality, this paper presents the control of fetching movements in the octopus as an exemplar of a cognitive process that comprises distinct and non-redundant representation-using and non-representational elements. Fetching is a type of movement that representational analyses can normally account for completely—but not in the case of the octopus. Instead, a comprehensive account of octopus fetching requires the non-overlapping use of both representational and non-representational explanatory frameworks. What (...) this need for a pluralistic or hybrid explanation implies is that cognitive science should be more open to using both representational and non-representational accounts of cognition, depending on their respective appropriateness to the type of cognition in question. (shrink)

Epistemic Utility Theory is often identified with the project of *axiology-first epistemology*—the project of vindicating norms of epistemic rationality purely in terms of epistemic value. One of the central goals of axiology-first epistemology is to provide a justification of the central norm of Bayesian epistemology, Probabilism. The first part of this paper presents a new challenge to axiology first epistemology: I argue that in order to justify Probabilism in purely axiological terms, proponents of axiology first epistemology need to justify a (...) claim about epistemic value—what I label ‘Downwards Propriety’—much stronger than any they have offered justification. The second part of this paper offers an argument that this challenge cannot be met: that there is no hope for providing a purely axiological justification of Downwards Propriety, at least given widely accepted assumptions about epistemic value. (shrink)

Introspection has traditionally been defined as a privileged way of obtaining beliefs about one’s occurrent mental states, and the idea that it is psychologically and epistemically different from non-introspective belief formation processes has been widely defended. At the same time, philosophers and cognitive scientists alike have pointed out the unreliability of introspective reports in consciousness research. In this paper, I will argue that this dissonance in the literature can be explained by differentiating between infallible and informative introspective beliefs. I will (...) argue that the latter are formed similarly to beliefs about the external world, and are therefore susceptible to similar success and failure conditions. Understanding introspection as belief-like will help to locate possible sources of error in regular as well as in pathological cases, carrying relevant implications for the relationship between experience, belief, and delusion. (shrink)

Talk of ”mental representations” is ubiquitous in the philosophy of mind, psychology, and cognitive science. A slogan common to many different approaches says that representations ”stand in for” the things they represent. This slogan also attaches to most talk of "internal models" in cognitive science. We argue that this slogan is either false or uninformative. We then offer a new slogan that aims to do better. The new slogan ties the role of representations to the cognitive role played by the (...) deliverances of perception. After clarifying the new slogan and warding off some misunderstandings, we discuss how the new slogan still captures the seed of truth in the old, point to some specific misunderstandings that can be avoided, and then suggest some ways that the new slogan is useful in the project of giving a satisfying philosophical theory of representation. (shrink)

The counterfactual account of physical computation is simple and, for the most part, very attractive. However, it is usually thought to trivialize the notion of physical computation insofar as it implies ‘limited pancomputationalism’, this being the doctrine that every deterministic physical system computes some function. Should we bite the bullet and accept limited pancomputationalism, or reject the counterfactual account as untenable? Jack Copeland would have us do neither of the above. He attempts to thread a path between the two horns (...) of the dilemma by buttressing the counterfactual account with extra conditions intended to block certain classes of deterministic physical systems from qualifying as physical computers. His theory is called the ‘algorithm execution account’. Here we show that the algorithm execution account entails limited pancomputationalism, despite Copeland’s argument to the contrary. We suggest, partly on this basis, that the counterfactual account should be accepted as it stands, pancomputationalist warts and all. (shrink)

Radical Enactivism holds that the best explanation of basic forms of cognition is provided without involving information of any sort. According to this view, the ability to perceive visual affordances should be accounted for in terms of extensional covariations between variables spanning the agent’s body and the environment. Contrary to Radical Enactivism, I argue that the intensional properties of cognition cannot be ignored, and that the way in which an agent represents the world has consequences on the explanation of basic (...) sensorimotor abilities. To support this claim, I show that the perception of visual affordances is not segregated from higher forms of cognition; rather, it is modulated by the agent’s ability to recognize the semantic identity of the visual target. Accordingly, since the semantic recognition of an object involves a way of representing it under a certain description, it can be inferred that the perception of visual affordances cannot be accounted for without considering the intensional properties of cognition. This poses an explanatory issue for Radical Enactivism. (shrink)

: Fodor’s view of the mind is thoroughly computational. This means that the basic kind of mental entity is a “discursive” mental representation and operations over this kind of mental representation have broad architectural scope, extending out to the edges of perception and the motor system. However, in multiple epochs of his work, Fodor attempted to define a functional role for non-discursive, imagistic representation. I describe and critique his two considered proposals. The first view says that images play a particular (...) kind of functional role in certain types of deliberative tasks. The second says that images are solely restricted to the borders of perception, and act as a sort of medium for the fixing of conceptual reference. I argue, against the first proposal, that a broad-scope computationalism such as Fodor’s renders images in principle functionally redundant. I argue, against the second proposal, that empirical evidence suggests that non-discursive representations are learned through perceptual learning, and directly inform category judgments. In each case, I point out extant debates for which the arguments are relevant. The upshot is that there is motivation for limited scope computationalism, in which some, but not all, mental processes operate on discursive mental representations. Keywords: Computational Theory of Mind; Mental Representation; Perception; Mental Image; Jerry Fodor Fodor e le rappresentazioni mentali come immagini Riassunto: La concezione della mente di Fodor è rigorosamente computazionale, ossia le entità mentali di base sono rappresentazioni mentali “discorsive”. Le operazioni su queste rappresentazioni hanno un fine architettonico ampio, che va fino ai confini della percezione e del sistema motorio. In periodi diversi del suo lavoro, Fodor ha proposto due modi per definire un ruolo funzionale per la rappresentazione non-discorsiva come immagine. Tratterò criticamente entrambi. Per il primo, le immagini giocano un particolare tipo di ruolo funzionale in certi tipi di compiti deliberativi, mentre, per il secondo, sono relegate unicamente ai confini della percezione, agendo come medium per fissare il riferimento concettuale. Contro il primo sosterrò che un computazionalismo così ampio come quello di Fodor rende le immagini in principio funzionalmente ridondanti. Contro il secondo sosterrò che l’evidenza empirica suggerisce che le rappresentazioni non-discorsive vengono apprese percettivamente, agendo direttamente sui giudizi di categorizzazione. In entrambi i casi considererò gli argomenti più rilevanti nel dibattito corrente. Si vedrà che ci sono buone ragioni in favore di un computazionalismo più limitato, in cui alcuni processi mentali operano su rappresentazioni mentali discorsive. Parole chiave: Teoria computazionale della mente; Rappresentazione mentale; Percezione; Immagine mentale; Jerry Fodor. (shrink)

The notion of representation in neuroscience has largely been predicated on localizing the components of computational processes that explain cognitive function. On this view, which I call “algorithmic homuncularism,” individual, spatially and temporally distinct parts of the brain serve as vehicles for distinct contents, and the causal relationships between them implement the transformations specified by an algorithm. This view has a widespread influence in philosophy and cognitive neuroscience, and has recently been ably articulated and defended by Shea. Still, I am (...) skeptical about algorithmic homuncularism, and I argue against it by focusing on recent methods for complex data analysis in systems neuroscience. I claim that analyses such as principle components analysis and linear discriminant analysis prevent individuating vehicles as algorithmic homuncularism recommends. Rather, each individual part contributes to a global state space, trajectories of which vary with important task parameters. I argue that, while homuncularism is false, this view still supports a kind of “vehicle realism,” and I apply this view to debates about the explanatory role of representation. (shrink)

Abilitism is an approach to the metaphysics of concepts according to which each concept consists of a managing cognitive ability coordinating other abilities (cognitive and non-cognitive) and a set of subordinate abilities associated with this managing ability. As I argue here, if we accept the abilitist approach, we can efficiently solve such puzzles in the metaphysics of concepts as the partial possession problem, the concept pluralism problem, etc. However, there are some possible objections to abilitism, concerning the abilitist explanation of (...) compositional properties of concepts, knowledge-that, an extension/intension of concepts, and the idea that concepts are constituents of thought. As I demonstrate here, these objections can be answered. (shrink)

A surge of empirical research demonstrating flexible cognition in animals and young infants has raised interest in the possibility of rational decision‐making in the absence of language. A venerable position, which I here call “Classical Inferentialism”, holds that nonlinguistic agents are incapable of rational inferences. Against this position, I defend a model of nonlinguistic inferences that shows how they could be practically rational. This model vindicates the Lockean idea that we can intuitively grasp rational connections between thoughts by developing the (...) Davidsonian idea that practical inferences are at bottom categorization judgments. From this perspective, we can see how similarity‐based categorization processes widely studied in human and animal psychology might count as practically rational. The solution involves a novel hybrid of internalism and externalism: intuitive inferences are psychologically rational (in the explanatory sense) given the intensional sensitivity of the similarity assessment to the internal structure of the agent's reasons for acting, but epistemically rational (in the justificatory sense) given an ecological fit between the features matched by that assessment and the structure of the agent's environment. The essay concludes by exploring empirical results that show how nonlinguistic agents can be sensitive to these similarity assessments in a way that grants them control over their opaque judgments. (shrink)

Nowadays, philosophers and scientists tend to agree that, even though human and artificial intelligence work quite differently, they can still illuminate aspects of each other, and knowledge in one domain can inspire progress in the other. For instance, the notion of “artificial” or “synthetic” phenomenology has been gaining some traction in recent AI research. In this paper, we ask the question: what (if anything) is the use of thinking about phenomenology in the context of AI, and in particular machine learning? (...) We will isolate one sense of “phenomenology”, namely the sense in which it is commonly understood within analytic philosophy of perception. Then, we will give examples of projects within sensory substitution and restoration science that rely heavily on machine learning and to which, according to us, phenomenology in the sense specified makes a relevant contribution. Finally, we will shed some light on what this contribution looks like and why it is important. (shrink)

The question of whether conscious experience is restricted by cognitive access and exhausted by report, or whether it overflows it—comprising more information than can be reported—is hotly debated. Recently, we provided evidence in favor of Overflow, showing that observers discriminated the color‐diversity (CD) of letters in an array, while their working‐memory and attention were dedicated to encoding and reporting a set of cued letters. An alternative interpretation is that CD‐discriminations do not entail conscious experience of the underlying colors. Here we (...) argue, based on conceptual considerations and consistency with neuroscience and phenomenology, in favor of the Overflow interpretation. (shrink)

Active materials are self-propelled non-living entities which, in some circumstances, exhibit a number of cognitively interesting behaviors such as gradient-following, avoiding obstacles, signaling and group coordination. This has led to scientific and philosophical discussion of whether this may make them useful as minimal models of cognition (Hanczyc, 2014; McGivern, 2019). Batterman and Rice (2014) have argued that what makes a minimal model explanatory is that the model is ultimately in the same universality class as the target system, which underpins why (...) it exhibits the same macrobehavior. We appeal to recent research in basal cognition (Lyon et al., 2021) to establish appropriate target systems and essential features of cognition as a target of modeling. Looking at self-propelled oil droplets, a type of active material, we do not find that organization alone indicates that these systems exhibit the essential features of cognition. We then examine the specific behaviors of oil droplets but also fail to find that these demonstrate the essential features of cognition. Without a universality class, Batterman & Rice’s account of the explanatory power of minimal models simply does not apply to cognition. However, we also want to stress that it is not intended to; cognition is not the same type of behavioral phenomena as those found in physics. We then look to the minimal cognition methodology of Beer (1996, 2020a, b) to show how active materials can be explanatorily valuable regardless of their cognitive status because they engage in specific behaviors that have traditionally been expected to involve internal representational dynamics, revealing misconceptions about the cognitive underpinnings of certain, specific behaviors in target systems where such behaviors are cognitive. Further, Beer’s models can also be genuinely explanatory by providing dynamical explanations. (shrink)