This paper aims to provide a theoretical framework for explaining the subjective character of pain experience in terms of what we will call ‘embodied predictive processing’. The predictive processing (PP) theory is a family of views that take perception, action, emotion and cognition to all work together in the service of prediction error minimisation. In this paper we propose an embodied perspective on the PP theory we call the ‘embodied predictive processing (...) (EPP) theory. The EPP theory proposes to explain pain in terms of processes distributed across the whole body. The prediction error minimising system that generates pain experience comprises the immune system, the endocrine system, and the autonomic system in continuous causal interaction with pathways spread across the whole neural axis. We will argue that these systems function in a coordinated and coherent manner as a single complex adaptive system to maintain homeostasis. This system, which we refer to as the neural-endocrine-immune (NEI) system, maintains homeostasis through the process of prediction error minimisation. We go on to propose a view of the NEI ensemble as a multiscale nesting of Markov blankets that integrates the smallest scale of the cell to the largest scale of the embodied person in pain. We set out to show how the EPP theory can make sense of how pain experience could be neurobiologically constituted. We take it to be a constraint on the adequacy of a scientific explanation of subjectivity of pain experience that it makes it intelligible how pain can simultaneously be a local sensing of the body, and, at the same time, a more global, all-encompassing attitude towards the environment. Our aim in what follows is to show how the EPP theory can meet this constraint. (shrink)

This article is a comparative study between predictive processing (PP, or predictive coding) and cognitive dissonance (CD) theory. The theory of CD, one of the most influential and extensively studied theories in social psychology, is shown to be highly compatible with recent developments in PP. This is particularly evident in the notion that both theories deal with strategies to reduce perceived error signals. However, reasons exist to update the theory of CD to one of (...) “predictive dissonance.” First, the hierarchical PP framework can be helpful in understanding varying nested levels of CD. If dissonance arises from a cascade of downstream and lateral predictions and consequent prediction errors, dissonance can exist at a multitude of scales, all the way up from sensory perception to higher order cognitions. This helps understand the previously problematic dichotomy between “dissonant cognitive relations” and “dissonant psychological states,” which are part of the same perception-action process while still hierarchically distinct. Second, since PP is action-oriented, it can be read to support recent action-based models of CD. Third, PP can potentially help us understand the recently speculated evolutionary origins of CD. Here, the argument is that responses to CD can instill meta-learning which serves to prevent the overfitting of generative models to ephemeral local conditions. This can increase action-oriented ecological rationality and enhanced capabilities to interact with a rich landscape of affordances. The downside is that in today’s world where social institutions such as science a priori separate noise from signal, some reactions to predictive dissonance might propagate ecologically unsound (underfitted, confirmation-biased) mental models such as climate denialism. (shrink)

Predictive Processing theory, hotly debated in neuroscience, psychology and philosophy, promises to explain a number of perceptual and cognitive phenomena in a simple and elegant manner. In some of its versions, the theory is ambitiously advertised as a new theory of conscious perception. The task of this paper is to assess whether this claim is realistic. We will be arguing that the Predictive Processing theory cannot explain the transition from unconscious to conscious (...) perception in its proprietary terms. The explanations offer by PP theorists mostly concern the preconditions of conscious perception, leaving the genuine material substrate of consciousness untouched. (shrink)

Predictive processing (PP) has been repeatedly presented as a unificatory account of perception, action, and cognition. In this paper, we argue that this is premature: As a unifying theory, PP fails to deliver general, simple, homogeneous, and systematic explanations. By examining its current trajectory of development, we conclude that PP remains only loosely connected both to its computational framework and to its hypothetical biological underpinnings, which makes its fundamentals unclear. Instead of offering explanations that refer to (...) the same set of principles, we observe systematic equivocations in PP‐based models, or outright contradictions with its avowed principles. To make matters worse, PP‐based models are seldom empirically validated, and they are frequently offered as mere just‐so stories. The large number of PP‐based models is thus not evidence of theoretical progress in unifying perception, action, and cognition. On the contrary, we maintain that the gap between theory and its biological and computational bases contributes to the arrested development of PP as a unificatory theory. Thus, we urge the defenders of PP to focus on its critical problems instead of offering mere re‐descriptions of known phenomena, and to validate their models against possible alternative explanations that stem from different theoretical assumptions. Otherwise, PP will ultimately fail as a unified theory of cognition. (shrink)

Both mindreading and stereotyping are forms of social cognition that play a pervasive role in our everyday lives, yet too little attention has been paid to the question of how these two processes are related. This paper offers a theory of the influence of stereotyping on mental-state attribution that draws on hierarchical predictive coding accounts of action prediction. It is argued that the key to understanding the relation between stereotyping and mindreading lies in the fact that stereotypes (...) centrally involve character-trait attributions, which play a systematic role in the action–prediction hierarchy. On this view, when we apply a stereotype to an individual, we rapidly attribute to her a cluster of generic character traits on the basis of her perceived social group membership. These traits are then used to make inferences about that individual’s likely beliefs and desires, which in turn inform inferences about her behavior. (shrink)

This essay presents the conditional probability of co-contribution account of the individuation of cognitive systems (CPC) and argues that CPC provides an attractive basis for a theory of the cognitive self. The argument proceeds in a largely indirect way, by emphasizing empirical challenges faced by an approach that relies entirely on predictive processing (PP) mechanisms to ground a theory of the cognitive self. Given the challenges faced by PP-based approaches, we should prefer a theory of (...) the cognitive self of the sort CPC offers, one that accommodates variety in the kinds of mechanism that, when integrated, constitute a cognitive system (and thus the cognitive self), to a theory according to which the cognitive self is composed of essentially one kind of thing, for instance, prediction-error minimization mechanisms. The final section focuses on one of the central functions of the cognitive self: to engage in conscious reasoning. It is argued that the phenomenon of conscious, deliberate reasoning poses an apparently insoluble problem for a PP-based view, one that seems to rest on a structural limitation of predictive-processing models. In a nutshell, conscious reasoning is a single-stream phenomenon, but, in order for PP to apply, two streams of activity must be involved, a prediction stream and an input stream. Thus, with regard to the question of the nature of the self, PP-based views must yield to an alternative approach, regardless of whether proponents of the predictive processing, as a comprehensive theory of cognition, can handle the various empirical challenges canvassed in the preceding section. (shrink)

The predictive processing account of action, cognition, and perception is one of the most influential approaches to unifying research in cognitive science. However, its promises of grand unification will remain unfulfilled unless the account becomes theoretically robust. In this paper, we focus on empirical commitments of PP, since they are necessary both for its theoretical status to be established and for explanations of individual phenomena to be falsifiable. First, we argue that PP is a varied research tradition, (...) which may employ various kinds of scientific representations, differing in the scope of empirical commitments they entail. Two major perspectives on PP qua cognitive theory may then be distinguished: generalized vs. hierarchical. The first one fails to provide empirical detail, and the latter constrains possible physical implementations. However, we show that even hierarchical PP is insufficiently restrictive to disallow incorrect models and may be adjusted to explain any neurocognitive phenomenon–including non-existent or impossible ones–through flexible adjustments. This renders PP a universal modeling tool with an unrestricted number of degrees of freedom. Therefore, in contrast with declarations of its proponents, it should not be understood as a unifying theoretical perspective, but as a computational framework, possibly informing further theory development in cognitive science. (shrink)

Perception can’t have disjunctive content. Whereas you can think that a box is blue or red, you can’t see a box as being blue or red. Based on this fact, I develop a new problem for the ambitious predictive processing theory, on which the brain is a machine for minimizing prediction error, which approximately implements Bayesian inference. I describe a simple case of updating a disjunctive belief given perceptual experience of one of the disjuncts, in which Bayesian (...) inference and predictive coding pull in opposite directions, with the former implying that one’s confidence in the belief should increase, and the latter implying that it should decrease. Thus, predictive coding fails to approximately implement Bayesian inference across the interface between belief and perception. (shrink)

Sleep and dreaming are important daily phenomena that are receiving growing attention from both the scientific and the philosophical communities. The increasingly popular predictive brain framework within cognitive science aims to give a full account of all aspects of cognition. The aim of this paper is to critically assess the theoretical advantages of Predictive Processing (PP, as proposed by Clark 2013, Clark 2016; and Hohwy 2013) in defining sleep and dreaming. After a brief introduction, we overview (...) the state of the art at the intersection between dream research and PP (with particular reference to Hobson and Friston 2012; Hobson et al. 2014). In the following sections we focus on two theoretically promising aspects of the research program. First, we consider the explanations of phenomenal consciousness during sleep (i.e. dreaming) and how it arises from the neural work of the brain. PP provides a good picture of the peculiarity of dreaming but it can’t fully address the problem of how consciousness comes to be in the first place. We propose that Integrated Information Theory (IIT) (Oizumi et al. 2014; Tononi et al. 2016) is a good candidate for this role and we will show its advantages and points of contact with PP. After introducing IIT, we deal with the evolutionary function of sleeping and dreaming. We illustrate that PP fits with contemporary researches on the important adaptive function of sleep and we discuss why IIT can account for sleep mentation (i.e. dreaming) in evolutionary terms (Albantakis et al. 2014). In the final section, we discuss two future avenues for dream research that can fruitfully adopt the perspective offered by PP: (a) the role of bodily predictions in the constitution of the sleeping brain activity and the dreaming experience, and (b) the precise role of the difference stages of sleep (REM (Rapid eye movement), NREM (Non-rapid eye movement) in the constitution and refinement of the predictive machinery. (shrink)

Despite their popularity, relatively scant attention has been paid to the upshot of Bayesian and predictive processing models of cognition for views of overall cognitive architecture. Many of these models are hierarchical ; they posit generative models at multiple distinct "levels," whose job is to predict the consequences of sensory input at lower levels. I articulate one possible position that could be implied by these models, namely, that there is a continuous hierarchy of perception, cognition, and (...) action control comprising levels of generative models. I argue that this view is not entailed by a general Bayesian/predictive processing outlook. Bayesian approaches are compatible with distinct formats of mental representation. Focusing on Bayesian approaches to motor control, I argue that the junctures between different types of mental representation are places where the transitivity of hierarchical prediction may be broken, and I consider the upshot of this conclusion for broader discussions of cognitive architecture. (shrink)

Latimer & Stevens (1997) develop a useful framework for discussing issues surrounding the definition and explanation of perceptual gestalts. They use this framework to raise some doubts about the possibility of “holistic” perceptual processing. However, I suspect that these doubts ultimately stem from assumptions about the nature of representation and processing in the brain, rather than from an analysis of part/whole concepts. I attempt to spell out these assumptions, and sketch an alternative perspective (deriving from Gestalt theory) (...) that has the potential to make sense of holism in perception. (shrink)

The predictive processing literature contains at least two different versions of the framework with different theoretical resources at their disposal. One version appeals to so-called optimistic priors to explain agents’ motivation to act (call this optimistic predictive processing). A more recent version appeals to expected free energy minimization to explain how agents can decide between different action policies (call this preference predictive processing). The difference between the two versions has not been properly appreciated, and (...) they are not sufficiently separated in the literature. They constitute two different theories with strikingly different accounts of motivation and action. By reducing all desire-like constructs to belief-like constructs, optimistic predictive processing entails a substantial revision of standard accounts of motivation and action in philosophy and cognitive science. By contrast, preference predictive processing introduces desire-like constructs that play Humean motivational roles in the explanation of action. In this Humean iteration, predictive processing resembles other prominent computational frameworks implementing a distinction between beliefs and desires, such as reinforcement learning and Bayesian decision theory. Ultimately, predictive processing faces a dilemma between parsimony of mental constructs and completeness of its explanations of agency and the mind. (shrink)

Courtesy of its free energy formulation, the hierarchical predictive processing theory of the brain (PTB) is often claimed to be a grand unifying theory. To test this claim, we examine a central case: activity of mesocorticolimbic dopaminergic (DA) systems. After reviewing the three most prominent hypotheses of DA activity—the anhedonia, incentive salience, and reward prediction error hypotheses—we conclude that the evidence currently vindicates explanatory pluralism. This vindication implies that the grand unifying claims of advocates of PTB (...) are unwarranted. More generally, we suggest that the form of scientific progress in the cognitive sciences is unlikely to be a single overarching grand unifying theory. (shrink)

This paper concerns how extant theorists of predictive coding conceptualize and explain possible instances of cognitive penetration. §I offers brief clarification of the predictive coding framework and relevant mechanisms, and a brief characterization of cognitive penetration and some challenges that come with defining it. §II develops more precise ways that the predictive coding framework can explain, and of course thereby allow for, genuine top-down causal effects on perceptual experience, of the kind discussed in the context of cognitive (...) penetration. §III develops these insights further with an eye towards tracking one extant criterion for cognitive penetration, namely, that the relevant cognitive effects on perception must be sufficiently direct. Throughout these discussions, we extend the analyses of the predictive coding models, as we know them. So one open question that surfaces is how much of the extended analyses are genuinely just part of the predictive coding models, or something that must be added to them in order to generate these additional explanatory benefits. In §IV, we analyze and criticize a claim made by some theorists of predictive coding, namely, that (interesting) instances of cognitive penetration tend to occur in perceptual circumstances involving substantial noise or uncertainty. It is here that our analysis is most critical. We argue that, when applied, the claim fails to explain (or perhaps even be consistent with) a large range of important and uncontroversially interesting possible cases of cognitive penetration. We conclude with a general speculation about how the recent work on the predictive mind may influence the current dialectic concerning top-down effects on perception. (shrink)

I argue that Sellars’s distinction between signifying and picturing should be taken seriously by philosophers of mind, language, and cognition. I begin with interpretations of key Sellarsian texts in order to show that picturing is best understood as a theory of non-linguistic cognitive representations through which animals navigate their environments. This is distinct from the kind of discursive cognition that Sellars called ‘signifying’ and which is best understood in terms of socio-linguistic inferences. I argue that picturing is (...) required because reflection on signifying cannot adequately explain our need for cognitive friction. I then show how the idea of picturing is further developed by Paul Churchland, Ruth Garrett Millikan, and Huw Price. I finally turn to predictive processing as a theory of cognitive representation, and in particular Andy Clark’s ‘radical predictive processing’, to further characterize picturing. However, doing so has the cost of pushing picturing and signifying further apart than Sellars intended. (shrink)

In this paper I return to Hubert Dreyfus’ old but influential critique of artificial intelligence, redirecting it towards contemporary predictive processing models of the mind (PP). I focus on Dreyfus’ arguments about the “frame problem” for artificial cognitive systems, and his contrasting account of embodied human skills and expertise. The frame problem presents as a prima facie problem for practical work in AI and robotics, but also for computational views of the mind in general, including for PP. Indeed, (...) some of the issues it presents seem more acute for PP, insofar as it seeks to unify all cognition and intelligence, and aims to do so without admitting any cognitive processes or mechanisms outside of the scope of the theory. I contend, however, that there is an unresolved problem for PP concerning whether it can both explain all cognition and intelligent behavior as minimizing prediction error with just the core formal elements of the PP toolbox, and also adequately comprehend (or explain away) some of the apparent cognitive differences between biological and prediction-based artificial intelligence, notably in regard to establishing relevance and flexible context-switching, precisely the features of interest to Dreyfus’ work on embodied indexicality, habits/skills, and abductive inference. I address several influential philosophical versions of PP, including the work of Jakob Hohwy and Andy Clark, as well as more enactive-oriented interpretations of active inference coming from a broadly Fristonian perspective. (shrink)

The essay explores the intersection of the Theory of Mind (T.O.M.) and Artificial Intelligence (AI), emphasizing the potential for AI to emulate cognitive processes fundamental to human social interactions. T.O.M., a concept crucial for understanding and interpreting human behavior through attributed mental states, contrasts with AI's behaviorist approach, which is rooted in data-driven pattern analysis and predictions. By examining foundational insights from cognitive sciences and the operational models of AI, this analysis highlights the potential advancements and implications of integrating (...) T.O.M.-like capabilities into AI systems. The discussion pivots around three critical questions: whether AI should emulate T.O.M. to enhance human interactions if AI can maintain its data-driven model while integrating cognitive processes, and how AI can expand its capabilities in social contexts. The arguments suggest that incorporating T.O.M.-like processes could significantly improve AI's interaction quality without compromising its analytical strengths, pointing towards a future where AI not only predicts but also empathizes, offering more nuanced and culturally aware interactions. This synthesis of cognitive theories and computational strategies advocates for deeper integration of diverse datasets and advanced computing methodologies, aiming to transform AI into a more empathetic and effective participant in human social environments. -/- Keywords: Theory of Mind, Artificial Intelligence, Human-AI Interaction, Cognitive Processes, Data-Driven Analysis. (shrink)

Philosophers and scientists have across the ages been amazed about the fact that development and learning often lead to not just a merely incremental and gradual change in the learner but sometimes to a result that is strikingly different from the learner’s original situation: amazed, but at times also worried. Both philosophical and cognitive neuroscientific insights suggest that experts appear to perform ‘different’ tasks compared to beginners who behave in a similar way. These philosophical and empirical perspectives give some insight (...) into what happens when a novice is transitioning to a stage of expertise. Generally, this implies that increased skill and expertise support better results and a more flexible performance, in part because these allow an agent to withdraw part of her attention and other cognitive resources from the tasks involved, enabling her to devote those resources to supporting, or completely different, tasks. As positive as these developments appear, these changes have also raised concerns. The main concern is whether gaining expertise is like raising a ‘cognitive monster’ which escapes the individual’s conscious control and influences her actions with undesirable automatisms. If so, we should ask ourselves whether experts are capable of taming this monster. The answer appears initially not to be positive. Indeed, it has been noted that since it is difficult for experts to withhold automatic responses this can lead to inflexibility or performance that is only optimal under certain conditions, because it is limited to a specific domain, often context-dependent, biased and inflexible. In what follows, I will consider this challenge of protecting expertise and harnessing this brittleness from philosophical and cognitive neuroscientific perspectives. Taking into account that action is in general determined by a multitude of factors, with learning and development affecting how these factors exert their influence, a philosophical question is how this complex and dynamic process can be explained and subsequently, how controlling it might be understood. First, though, I will present the issue at hand more closely: should we appreciate expertise if it is similar to growing a ‘cognitive monster’? Second, I will introduce the framework of a “Sculpted Space of Actions” (Keestra, 2014), which I developed in order to explain how the challenge of selecting an adequate option for action is facilitated by expertise as it helps to constrain the space of potential action options. Subsequently, the question is raised of how such a Sculpted Space of Actions influences an expert’s engagement with specific situations, like teaching students in a classroom setting. It will be argued that a well prepared expert—teacher or otherwise— is not only able to rely upon her routines but will at the same time be more perceptive and attentive to unforeseen events and actions, according to the recent cognitive neuroscientific theory of Predictive Processing. Integrating the theory of Predictive Processing with the Sculpted Space of Actions framework, I conclude that expertise contributes to adaptive and flexible responses to specific contexts, yet only if it is associated with explicit planning and articulation of situation specific intentions—the latter effectively putting the cognitive monster at rest for a while. (shrink)

The paper is dedicated to particular cases of interaction and mutual impact of philosophy and cognitive science. Thus, philosophical preconditions in the middle of the 20th century shaped the newly born cognitive science as mainly based on conceptual and propositional representations and syntactical inference. Further developments towards neural networks and statistical representations did not change the prejudice much: many still believe that network models must be complemented with some extra tools that would account for proper human cognitive traits. I address (...) some real implemented connectionist models that show how ‘new associationism ’ of the neural network approach may not only surpass Humean limitations, but, as well, realistically explain abstraction, inference and prediction. Then I stay on Predictive Processing theories in a little more detail to demonstrate that sophisticated statistical tools applied to a biologically realist ontology may not only provide solutions to scientific problems or integrate different cognitive paradigms but propose some philosophical insights either. To conclude, I touch on a certain parallelism of Predictive Processing and philosophical inferentialism as presented by Robert Brandom. (shrink)

Decision-making has traditionally been modelled as a serial process, consisting of a number of distinct stages. The traditional account assumes that an agent first acquires the necessary perceptual evidence, by constructing a detailed inner repre- sentation of the environment, in order to deliberate over a set of possible options. Next, the agent considers her goals and beliefs, and subsequently commits to the best possible course of action. This process then repeats once the agent has learned from the consequences of her (...) actions and subsequently updated her beliefs. Under this interpretation, the agent’s body is considered merely as a means to report the decision, or to acquire the relevant goods. However, embodied cognition argues that an agent’s body should be understood as a proper part of the decision-making pro- cess. Accepting this principle challenges a number of commonly held beliefs in the cognitive sciences, but may lead to a more unified account of decision-making. This thesis explores an embodied account of decision-making using a recent frame- work known as predictive processing. This framework has been proposed by some as a functional description of neural activity. However, if it is approached from an embodied perspective, it can also offer a novel account of decision-making that ex- tends the scope of our explanatory considerations out beyond the brain and the body. We explore work in the cognitive sciences that supports this view, and argue that decision theory can benefit from adopting an embodied and predictive perspective. (shrink)

The first premise of Schellenberg’s particularity argument reads, “If a subject S perceives a particular α, then S discriminates and singles out α” (2018: 25). But this is false if seeing a ganzfeld is possible (i.e., a homogeneous field without any particulars to discriminate). In response, Schellenberg argues that seeing a ganzfeld is impossible by appealing to the ganzfeld effect (viz. hallucinatory experiences caused by ganzfeld exposure) exclusively as a ‘sense of blindness’. I present two challenges for this line of (...) reasoning. The first concerns the need to account for the long delay before blindness is reported (if it is reported at all) and the second concerns the need to be consistent with potential causes of ganzfeld hallucinations (in general, not exclusive to the sense of blindness). I show how Schellenberg’s particularity argument can meet the first challenge but struggles to meet the second. I present evidence based on considerations related to sensory deprivation and that follow from the predictive processing theory of cognition, which describes seeing a ganzfeld as the cause of ganzfeld hallucinations. If correct, this means that you can see a homogeneous field, and thus we ought to be skeptical of the soundness of Schellenberg’s particularity argument. I conclude with a possible strategy for rehabilitating the particularity argument that reconceptualizes perceptual experience as fundamentally multimodal, constituted by both exteroceptive and interoceptive sensation. (shrink)

The purpose of this study is to describe a conceptual framework for cognitive distortions, which notably allows to specify more accurately their intrinsic relationships. This conceptual framework aims at inserting itself within the apparatus of cognitive therapy and of critical thinking. The present analysis is based on the following fundamental concepts: the reference class, the duality and the system of taxa. With the help of these three notions, each cognitive distortion can be defined. A distinction is also made between, on (...) the one hand, general cognitive distortions and on the other hand, specific cognitive distortions. The present model allows then to define within the same conceptual framework the general cognitive distortions such as dichotomous reasoning, disqualifying a given pole, minimisation and maximisation. It also allows to describe as specific cognitive distortions: disqualifying the positive, selective abstraction and catastrophism. Furthermore, the present model predicts the existence of two other general cognitive distortions: the omission of the neutral and requalifying in the other pole. (shrink)

Based on the wealth of scientific evidence and concepts, this theory has been formed, and its essence is as follows: 1. From the physical properties of the mind and those of the brain (the alive, processing brain), it can be concluded that the mind occurs, exists, and functions with the brain (Chapter 1) and that it is the composite of all neural information-processing processes (Chapter 2). 2. Qualia—mental phenomena that appear phenomenally in our mind and that we (...) can consciously experience, such as the vision of a house, the sound of a song, and the odor of a rose in our mind—are physical phenomena. They are governed by physical laws and are physically predictable. Specifically, they are neural-process–associated physical phenomena. (Chapters 3 & 4) 3. From the physical properties of qualia and those of special kinds of neural-process signaling patterns, which are neural information and non-material, it can be concluded that qualia are special kinds of neural-process signaling patterns, called special signaling patterns. (Chapter 5) 4. From the physical properties of consciousness and those of a special kind of reentrant signaling state, which is the neural information of the consciousness neural process and is non-material, it can be concluded that consciousness is a special kind of reentrant signaling state. 5. The fact that qualia and conscious awareness and conscious experiences of the qualia occur in only the final-stage sensory perception neural processes and the highest-level cognitive and executive neural processes, which are the latest-evolved neural processes, and never occur in the more primitive neural processes, such as the brainstem, cerebellum, and basal ganglia, or over the whole brain randomly, indicates that they are not haphazardly occurring phenomena but are evolved phenomena of the nervous system. (Chapter 5 & Chapter 6) 6. Because a neural process that performs a certain function (such as perceiving a vision) without a quale occurring and a neural process that performs that same function (such as perceiving the same vision) with a quale occurring have different information in the processes, they have different signaling patterns (to convey different information). Therefore, they have different physical effects on other neural processes, at least from the different effects of different signaling patterns. Qualia thus have physical effects. Also, because we do have conscious awareness and conscious experiences of qualia, qualia must certainly induce the consciousness neural process to function to be consciously aware of and to consciously experience the qualia. Therefore, because the consciousness neural process is a physical process, qualia cause changes in a physical process and thus have physical effects. (Chapter 5) Similarly, it can be concluded that consciousness (conscious awareness and conscious experiences) has physical effects. (Chapter 6) Therefore, qualia and consciousness are evolved neural functions that have physical effects. 7. Because a function requires resources in building, maintaining, and operating the function and may have some negative effects, if its overall effects do not help increase the survival chances of the animals that have the function, those animals and the function will likely become extinct in the evolutionary process. This is especially true for a major function in a critical organ, such as in the case of qualia and consciousness in the brain. The fact that qualia and consciousness still exist today indicates that they have been selected to remain in the evolutionary process. This means that their overall effects must help increase the survival chances of the species that have them. Qualia and consciousness, in the form that they are—phenomenal qualia and phenomenal consciousness, or qualia and consciousness that appear phenomenally in our mind—are thus evolved functions to help increase the survival chances of the species, including humans, that have them. This is the scientific answer to the other part of the hard problem of consciousness: Why do qualia and consciousness in the form of phenomenal qualia and phenomenal consciousness occur in this universe? This is also the scientific answer to one of the most basic questions of our lives: Why do “we” exist? (Chapter 5 & Chapter 6). (shrink)

Our prominent definitions of cognition are too vague and lack empirical grounding. They have not kept up with recent developments, and cannot bear the weight placed on them across many different debates. I here articulate and defend a more adequate theory. On this theory, behaviors under the control of cognition tend to display a cluster of characteristic properties, a cluster which tends to be absent from behaviors produced by non-cognitive processes. This cluster is reverse-engineered from the (...) empirical tests that comparative psychologists use to determine whether a behavior was generated by a cognitive or a non-cognitive process. Cognition should be understood as the natural kind of psychological process that non-accidentally exhibits the properties assessed by these tests (as well as others we have not yet discovered). Finally, I review two plausible neural accounts of cognition's underlying mechanisms?one based in localization of function to particular brain regions and another based in the more recent distributed networks approach to neuroscience?which would explain why these properties non-accidentally cluster. While this notion of cognition may be useful for a number of debates, I here focus on its application to a recent crisis over the distinction between cognition and association in comparative psychology. (shrink)

4Es approaches to cognition draw an unconventional picture of cognitive processes and of the mind. Instead of conceiving of cognition as a process that always takes place within the boundaries of the skull and the skin, these approaches hold that cognition is a situated process that often extends beyond human agents’ physical boundaries. In particular, supporters of the extended mind theory and of the enactive approach claim that embodied action in a perceptually complex environment is constitutive (...) of cognitive processes, and thus of the mind. (Chapter 1). Although both draw an extended picture of cognition and of the mind, supporters of the extended mind and supporters of the enactive approach disagree on the value of internal representations in perceptually-guided action. The extended mind theory holds that we need to posit internal action-oriented representations (AORs). AORs are valuable -the argument goes- because they account for action-selection, action-control, and for the prediction of incoming perceptual information. Advocates of the enactive approach to cognition, instead, argue against AORs. Firstly, they argue that AORs do not fulfill the necessary conditions for the identification of representational entities. Therefore, that of AOR is an ill-conceived epistemic construct. Secondly, they argue that AORs are expressive of an internalist prejudice, which makes the extended mind theory weaker than it should be from an explanatory and metaphysical point of view. I endorse both these arguments advanced by supporters of the enactive approach. Moreover, through a semiotic analysis of the construct and of the workings of AORs, I show that AORs are not active at all. Hence, I argue that AORs do not do the job they are supposed to do: extending the mind’s boundaries by explaining our perceptual relation with the world as an active, embodied, and world-involving process. Therefore, I suggest that the construct of AOR ought to be dismissed - at least in current projects in 4Es cognition (Chapter 2). I argue that similar arguments apply to recent attempts to make predictive processing accounts of perceptually-guided action more aligned with 4Es approaches to cognitive science by appealing to predictive internal models of our perceptual world. I thus propose an alternative explanation of the key features of perceptually-guided action that AORs and these internal models are supposed to be grasp. Action-control, action-selection, and the anticipatory aspects of action-perception loops can be explained by appealing to embodied actions in a field of relevant affordances, which are perceived as such based on the agent’s motor skills and motives. Furthermore, I suggest that, by combining the enactive approach to cognition with an analysis of the indexical features of our perceptual environment, we can explain perceptually-guided action in a way that truly accounts for our minds as entities that often extend beyond our skulls and skin. And we can do so without holding onto spooking entities like AORs and internal predictive models. (Chapter 3). (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)

Perceptual filling-in for vision is the insertion of visual properties (e.g., color, contour, luminance, or motion) into one’s visual field, when those properties have no corresponding retinal input. This paper introduces and provides preliminary empirical support for filled/non-filled pairs, pairs of images that appear identical, yet differ by amount of filling-in. It is argued that such image pairs are important to the experimental testing of theories of consciousness. We review recent experimental research and conclude that filling-in involves brain activity with (...) relatively high integrated information (Phi) compared to veridical visual perceptions. We then present filled/non-filled pairs as an empirical challenge to the integrated information theory of consciousness, which predicts that phenomenologically identical experiences depend on brain processes with identical Phi. (shrink)

What is the content of a mental state? This question poses the problem of intentionality: to explain how mental states can be about other things, where being about them is understood as representing them. A framework that integrates predictive coding and signaling systems theories of cognitive processing offers a new perspective on intentionality. On this view, at least some mental states are evaluations, which differ in function, operation, and normativity from representations. A complete naturalistic theory of intentionality (...) must account for both types of intentional state. (shrink)

This chapter argues that the only tenable unconscious inferences theories of cognitive achievement are ones that employ a theory internal technical notion of representation, but that once we give cash-value definitions of the relevant notions of representation and inference, there is little left of the ordinary notion of representation. We suggest that the real value of talk of unconscious inferences lies in (a) their heuristic utility in helping us to make fruitful predictions, such as about illusions, and (b) their (...) providing a high-level description of the functional organization of subpersonal faculties that makes clear how they equip an agent to navigate its environment and pursue its goals. (shrink)

The predictive coding (PC) theory of attention identifies attention with the optimization of the precision weighting of prediction error. Here we provide some challenges for this identification. On the one hand, the precision weighting of prediction error is too broad a phenomenon to be identified with attention because such weighting plays a central role in multimodal integration. Cases of crossmodal illusions such as the rubber hand illusion and the McGurk effect involve the differential precision weighting of prediction error, (...) yet attention does not shift as one would predict. On the other hand, the precision weighting of prediction error is too narrow a phenomenon to be identified with attention, because it cannot accommodate the full range of attentional phenomena. We review criticisms that PC cannot account for volitional attention and affect-biased attention, and we propose that it may not be able to account for feature-based and intellectual attention. (shrink)

Dual-process theories of higher order cognition (DPTs) have been enjoying much success, particularly since Kahneman’s 2002 Nobel prize address and recent book Thinking, Fast and Slow (2009). Historically, DPTs have attempted to provide a conceptual framework that helps classify and predict differences in patterns of behavior found under some circumstances and not others in a host of reasoning, judgment, and decision-making tasks. As evidence has changed and techniques for examining behavior have moved on, so too have DPTs. Killing two (...) birds with one stone, Evans and Stanovich (2013, this issue) respond to five main criticisms of DPTs. Along with addressing each criticism in turn, they set out to clarify the essential defining characteristics that distinguish one form of higher order cognition from the other. The aim of this commentary is to consider the defining characteristics of Type 1 and Type 2 processing that have been proposed and to suggest that the evidence can be taken to support quantitative differences rather than qualitatively distinct processes. (shrink)

This chapter explores to what extent some core ideas of predictive processing can be applied to the phenomenology of time consciousness. The focus is on the experienced continuity of consciously perceived, temporally extended phenomena (such as enduring processes and successions of events). The main claim is that the hierarchy of representations posited by hierarchical predictive processing models can contribute to a deepened understanding of the continuity of consciousness. Computationally, such models show that sequences of events can (...) be represented as states of a hierarchy of dynamical systems. Phenomenologically, they suggest a more fine-grained analysis of the perceptual contents of the specious present, in terms of a hierarchy of temporal wholes. Visual perception of static scenes not only contains perceived objects and regions but also spatial gist; similarly, auditory perception of temporal sequences, such as melodies, involves not only perceiving individual notes but also slightly more abstract features (temporal gist), which have longer temporal durations (e.g., emotional character or rhythm). Further investigations into these elusive contents of conscious perception may be facilitated by findings regarding its neural underpinnings. Predictive processing models suggest that sensorimotor areas may influence these contents. (shrink)

Predictive approaches to the mind claim that perception, cognition, and action can be understood in terms of a single framework: a hierarchy of Bayesian models employing the computational strategy of predictive coding. Proponents of this view disagree, however, over the extent to which perception is direct on the predictive approach. I argue that we can resolve these disagreements by identifying three distinct notions of perceptual directness: psychological, metaphysical, and epistemological. I propose that perception is plausibly construed (...) as psychologically indirect on the predictive approach, in the sense of being constructivist or inferential. It would be wrong to conclude from this, however, that perception is therefore indirect in a metaphysical or epistemological sense on the predictive approach. In the metaphysical case, claims about the inferential properties of constructivist perceptual mechanisms are consistent with both direct and indirect solutions to the metaphysical problem of perception (e.g. naïve realism, representationalism, sense datum theory). In the epistemological case, claims about the inferential properties of constructivist perceptual mechanisms are consistent with both direct and indirect approaches to the justification of perceptual belief. In this paper, I demonstrate how proponents of the predictive approach have conflated these distinct notions of perceptual directness and indirectness, and I propose alternative strategies for developing the philosophical consequences of the approach. (shrink)

Studies of visual event individuation often consider people's representations of activities involving agents performing complex tasks. Concomitantly, theories of event individuation emphasize predictions about agents' intentions. Studies that have examined simple, non-agential occurrences leave open the possiblity that principles of visual object individuation play a role in visual event individuation. Unearthing principles that may be sufficient for event individuation which are distinct both from predictions about agents' intentions and from visual object individuation, we draw on and extend studies that reveal (...) object and event representation to be deeply analogous in our cognitive economy. We provide evidence that ‘temporal shaping' is a sufficient low-level perceptual criterion for the visual individuation of events. In our study, temporal shaping is effected by the introduction of pauses into an otherwise continuous process. Future studies should address other visual mechanisms for introducing temporal shaping (e.g., color changes). (shrink)

The aim of this study is to justify the belief that there are biological normative mechanisms that fulfill non-trivial causal roles in the explanations (as formulated by researchers) of actions and behaviors present in specific systems. One example of such mechanisms is the predictive mechanisms described and explained by predictive processing (hereinafter PP), which (1) guide actions and (2) shape causal transitions between states that have specific content and fulfillment conditions (e.g. mental states). Therefore, I am guided (...) by a specific theoretical goal associated with the need to indicate those conditions that should be met by the non-trivial theory of normative mechanisms and the specific models proposed by PP supporters. In this work, I use classical philosophical methods, such as conceptual analysis and critical reflection. I also analyze selected studies in the field of cognitive science, cognitive psychology, neurology, information theory and biology in terms of the methodology, argumentation and language used, in accordance with their theoretical importance for the issues discussed in this study. In this sense, the research presented here is interdisciplinary. My research framework is informed by the mechanistic model of explanation, which defines the necessary and sufficient conditions for explaining a given phenomenon. The research methods I chose are therefore related to the problems that I intend to solve. In the introductory chapter, “The concept of predictive processing”, I discuss the nature of PP as well as its main assumptions and theses. I also highlight the key concepts and distinctions for this research framework. Many authors argue that PP is a contemporary version of Kantianism and is exposed to objections similar to those made against the approach of Immanuel Kant. I discuss this thesis and show that it is only in a very general sense that the PP framework is neo-Kantian. Here we are not dealing with transcendental deduction nor with the application of transcendental arguments. I argue that PP is based on reverse engineering and abduction inferences. In the second part of this chapter, I respond to the objection formulated by Dan Zahavi, who directly accuses this research framework of anti-realistic consequences. I demonstrate that the position of internalism, present in the so-called conservative PP, does not imply anti-realism, and that, due to the explanatory role played in it by structural representations directed at real patterns, it is justified to claim that PP is realistic. In this way, I show that PP is a non-trivial research framework, having its subject, specific methods and its own epistemic status. Finally, I discuss positions classified as the socalled radical PP. In the chapter “Predictive processing as a Bayesian explanatory model” I justify the thesis according to which PP offers Bayesian modeling. Many researchers claim that the brain is an implemented statistical probabilistic network that is an approximation of the Bayesian 7 rule. In practice, this means that all cognitive processes are to apply Bayes' rule and can be described in terms of probability distributions. Such a solution arouses objections among many researchers and is the subject of wide criticism. The purpose of this chapter is to justify the thesis that Bayesian PP is a non-trivial research framework. For this purpose, I argue that it explains certain phenomena not only at the computational level described by David Marr, but also at the level of algorithms and implementation. Later in this chapter I demonstrate that PP is normative modeling. Proponents of the use of Bayesian models in psychology or decision theory argue that they are normative because they allow the formulation of formal rules of action that show what needs to be done to make a given action optimal. Critics of this approach emphasize that such thinking about the normativity of Bayesian modeling is unjustified and that science should shift from prescriptive to descriptive positions. In a polemic with Shira Elqayam and Jonathan Evans (2011), I show that the division they propose into prescriptivism and Bayesian descriptivism is apparent, because, as I argue, there are two forms of prescriptivism, i.e. the weak and the strong. I argue that the weak version is epistemic and can lead to anti-realism, while the strong version is ontic and allows one to justify realism in relation to Bayesian models. I argue that a weak version of prescriptivism is valid for PP. It allows us to adopt anti-realism in relation to PP. In practice, this means that you can explain phenomena using Bayes' rule. This does not, however, imply that they are Bayesian in nature. However, the full justification of realism in relation to the Bayesian PP presupposes the adoption of strong prescriptivism. This position assumes that phenomena are explained by Bayesian rule because they are Bayesian as such. If they are Bayesian in nature, then they should be explained using Bayesian modeling. This thesis will be substantiated in the chapters “Normative functions and mechanisms in the context of predictive processing” and “Normative mechanisms and actions in predictive processing”. In the chapter “The Free Energy Principle in predictive processing”, I discuss the Free Energy Principle (hereinafter FEP) formulated by Karl Friston and some of its implications. According to this principle, all biological systems (defined in terms of Markov blankets) minimize the free energy of their internal states in order to maintain homeostasis. Some researchers believe that PP is a special case of applying this principle to cognition, and that predictive mechanisms are homeostatic mechanisms that minimize free energy. The discussion of FEP is important due to the fact that some authors consider it to be important for explanatory purposes and normative. If this is the case, then FEP turns out to be crucial in explaining normative predictive mechanisms and, in general, any normative biological mechanisms. To define the explanatory possibilities of this principle, I refer to the discussion of its supporters on the issue they define as the problem of continuity and discontinuity between life and mind. A critical analysis of this discussion and the additional arguments I have formulated have allowed me to revise the explanatory ambitions of FEP. I also reject the belief that this principle is necessary to explain the nature of predictive mechanisms. I argue that the principle formulated and defended by Friston is an important research heuristic for PP analysis. 8 In the chapter “Normative functions and mechanisms in predictive processing”, I start my analyzes by formulating an answer to the question about the normative nature of homeostatic mechanisms. I demonstrate that predictive mechanisms are not homeostatic. I defend the view that a full explanation of normative mechanisms presupposes an explanation of normative functions. I discuss the most important proposals for understanding the normativity of a function, both from a systemic and teleosemantic perspective. I conclude that the non-trivial concept of a function must meet two requirements which I define as explanatory and normative. I show that none of the theories I have invoked satisfactorily meets both of these requirements. Instead, I propose a model of normativity based on Bickhard's account, but supplemented by a mechanistic perspective. I argue that a function is normative when: (1) it allows one to explain the dysfunction of a given mechanism; (2) it contributes to the maintenance of the organism's stability by shaping and limiting possible relations, processes and behaviors of a given system; and when (3) (according to the representational and predictive functions) it enables explaining the attribution of logical values of certain representations / predictions. In such an approach, a mechanism is normative when it performs certain normative functions and when it is constitutive for a specific action or behavior, despite the fact that for some reason it cannot realize it either currently or in the long-term. Such an understanding of the normativity of mechanisms presupposes the acceptance of the epistemic hypothesis. I argue that this hypothesis is not cognitively satisfactory, and therefore the ontic hypothesis should be justified, which is directly related to adopting the position of ontic prescriptivism. For this reason, referring to the mechanistic theory of scientific explanations, I formulate an ontical interpretation of the concept of a normative mechanism. According to this approach, a mechanism or a function is normative when they perform such and such causal roles in explaining certain actions and behaviors. With regard to the normative properties of predictive mechanisms and functions, this means that they are the causes of specific actions an organism carries out in the environment. In this way, I justify the necessity of accepting the ontic hypothesis and rejecting the epistemic hypothesis. The fifth chapter, “Normative mechanisms and actions in predictive processing”, is devoted to the dark room problem and the related exploration-exploitation trade-off. A dark room is the state that an agent could be in if it minimized the sum of all potential prediction errors. I demonstrate that, in accordance with the basic assumption of PP about the need for continuous and long-term minimization of prediction errors, such a state should be desirable for the agent. Is it really so? Many authors believe it is not. I argue that the test of the value of PP is the possibility of a non-trivial solution of this problem, which can be reduced to the choice between active and uncertainty-increasing exploration and safe and easily predictable exploitation. I show that the solution proposed by PP supporters present in the literature does not enable a fully satisfactory explanation of this dilemma. Then I defend the position according to which the full explanation of the normative mechanisms, and, subsequently, the solution to the dilemma of exploration and exploitation, involves reference to the existence of constraints present in the environment. The constraints 9 include elements of the environment that make a given mechanism not only causal but also normative. They are therefore key to explaining the predictive mechanisms. They do not only play the role of the context in which the mechanism is implemented, but, above all, are its constitutive component. I argue that the full explanation of the role of constraints in normative predictive mechanisms presupposes the integration of individual models of specific cognitive phenomena, because only the mechanistic integration of PP with other models allows for a non-trivial explanation of the nature of normative predictive mechanisms that would have a strong explanatory value. The explanatory monism present in many approaches to PP makes it impossible to solve the problem of the dark room. Later in this chapter, I argue that the Bayesian PP is normative not because it enables the formulation of such and such rules of action, but because the predictive mechanisms themselves are normative. They are normative because they condition the choice of such and such actions by agents. In this way, I justify the hypothesis that normative mechanisms make it possible to explain the phenomenon of agent motivation, which is crucial for solving the dark room problem. In the last part of the chapter, I formulate the hypothesis of distributed normativity, which assumes that the normative nature of certain mechanisms, functions or objects is determined by the relations into which these mechanisms, functions or objects enter. This means that what is normative (in the primary sense) is the relational structure that constitutes the normativity of specific items included in it. I suggest that this hypothesis opens up many areas of research and makes it possible to rethink many problems. In the “Conclusion”, I summarize the results of my research and indicate further research perspectives. (shrink)

De Neys (2021) argues that the debate between single- and dual-process theorists of thought has become both empirically intractable and scientifically inconsequential. I argue that this is true only under the traditional framing of the debate—when single- and dual-process theories are understood as claims about whether thought processes share the same defining properties (e.g., making mathematical judgments) or have two different defining properties (e.g., making mathematical judgments autonomously versus via access to a central working memory capacity), respectively. But if single- (...) and dual-process theories are understood in cognitive modeling terms as claims about whether thought processes function to implement one or two broad types of algorithms, respectively, then the debate becomes scientifically consequential and, presumably, empirically tractable. So, I argue, the correct response to the current state of the debate is not to abandon it, as De Neys suggests, but to reframe it as a debate about cognitive models. (shrink)

Social cognition researchers have become increasingly interested in the ways that behavioral, physiological, and neural coupling facilitate social interaction and interpersonal understanding. We distinguish two ways of conceptualizing the role of such coupling processes in social cognition: strong and moderate interactionism. According to strong interactionism (SI), low-level coupling processes are alternatives to higher-level individual cognitive processes; the former at least sometimes render the latter superfluous. Moderate interactionism (MI) on the other hand, is an integrative approach. Its guiding assumption (...) is that higher-level cognitive processes are likely to have been shaped by the need to coordinate, modulate, and extract information from low-level coupling processes. In this paper, we present a case study on Möbius Syndrome (MS) in order to contrast SI and MI. We show how MS—a form of congenital bilateral facial paralysis—can be a fruitful source of insight for research exploring the relation between high-level cognition and low-level coupling. Lacking a capacity for facial expression, individuals with MS are deprived of a primary channel for gestural coupling. According to SI, they lack an essential enabling feature for social interaction and interpersonal understanding more generally and thus ought to exhibit severe deficits in these areas. We challenge SI’s prediction and show how MS cases offer compelling reasons for instead adopting MI’s pluralistic model of social interaction and interpersonal understanding. We conclude that investigations of coupling processes within social interaction should inform rather than marginalize or eliminate investigation of higher-level individual cognition. (shrink)

In the last few years, a remarkable convergence of interests and results has emerged between scholars interested in the arts and aesthetics from a variety of perspectives and cognitive scientists studying the mind and brain within the predictive processing (PP) framework. This convergence has so far proven fruitful for both sides: while PP is increasingly adopted as a framework for understanding aesthetic phenomena, the arts and aesthetics, examined under the lens of PP, are starting to be seen as (...) important windows into our mental functioning. The result is a vast and fast-growing research programme that promises to deliver important insights into our aesthetic encounters as well as a wide range of psychological phenomena of general interest. Here, we present this developing research programme, describing its grounds and highlighting its prospects. We start by clarifying how the study of the arts and aesthetics encounters the PP picture of mental functioning (§1). We then go on to outline the prospects of this encounter for the fields involved: philosophy and history of art (§2), psychology of aesthetics and neuroaesthetics (§3) and psychology and neuroscience more generally (§4). The upshot is an ambitious but well-defined framework within which aesthetics and cognitive science can partner up to illuminate crucial aspects of the human mind. -/- This article is part of the theme issue ‘Art, aesthetics and predictive processing: theoretical and empirical perspectives’. -/- . (shrink)

Fictionalist theories of metaphor hold that metaphorical utterances aim at fictionality. Fictionalism successfully explains speaker judgments about the truth and aptness of metaphorical utterances, and it also accurately predicts the data around metaphor and autistic individuals (who have deficits in both imaginative play and metaphor comprehension). But fictionalism is not a viable theory of metaphor, despite these merits, because of (what I call) the problem of semantic entailment: semantic entailments that are normally valid fail under metaphorical interpretation, but fictionalism (...) predicts otherwise. I argue this to ultimately show that theorists of metaphor should reject the linguistic side of the fictionalist story; but this leaves open the possibility of accepting psychological fictionalism, i.e., the hypothesis that fiction/make-believe is central to the cognitive processing of metaphor. Coupling psychological fictionalism with a different theory of metaphorical meaning and content (such as contextualism) promises to keep the explanatory upsides of traditional fictionalism while avoiding the problem of semantic entailment. (shrink)

This article synthesizes the current theoretical attempts to understand human-machine interactions and introduces seven premises to understand our emerging dynamics with increasingly competent, pervasive, and instantly accessible algorithms. The hope that these seven premises can build toward a social theory of human-AI cocreation. The focus on human-AI cocreation is intended to emphasize two factors. First, is the fact that our machine learning systems are socialized. Second, is the coevolving nature of human mind and AI systems as smart devices form (...) an indispensable part of our cognitive scaffolds, thus, shaping how we perceive the world and ourselves. The seven premises include: primacy of social structures; human’s desire for freedom and autonomy; AI systems will form inseparable parts of our cognitive/affective scaffolds and can change our self-understanding; philosophy and humanistic foundations on human flourishing as a guide to human-AI interaction; mindsponge information-filtering process; acculturative process of how values change and emerge from human-AI interaction; overlapping Venn diagram of the human-human, human-nature, and human-machine interactions. This article concludes with a discussion on human agency in our entanglements with socialized machines and the illusoriness of the Cartesian agent view of the mind. (shrink)

Philosophers interested in the theoretical consequences of predictive processing often assume that predictive processing is an inferentialist and representationalist theory of cognition. More specifically, they assume that predictive processing revolves around approximated Bayesian inferences drawn by inverting a generative model. Generative models, in turn, are said to be structural representations: representational vehicles that represent their targets by being structurally similar to them. Here, I challenge this assumption, claiming that, at present, it lacks (...) an adequate justification. I examine the only argument offered to establish that generative models are structural representations, and argue that it does not substantiate the desired conclusion. Having so done, I consider a number of alternative arguments aimed at showing that the relevant structural similarity obtains, and argue that all these arguments are unconvincing for a variety of reasons. I then conclude the paper by briefly highlighting three themes that might be relevant for further investigation on the matter. (shrink)

The extended mind thesis maintains that cognitive processes and systems can, on occasion, stretch to include parts of the brain, body, and world. One outstanding puzzle facing this view is the “recruitment puzzle.” The recruitment puzzle asks how cognisers are able to reliably recruit internal and external resources such that they form extended systems. Andy Clark has recently suggested that predictive processing helps to address this puzzle. I argue that, while promising, Clark’s proposal remains incomplete. I suggest that (...) Clark’s proposal can be productively extended by disambiguating two important senses of recruitment: ready-to-hand and adaptive recruitment. After outlining the recruitment puzzle and Clark’s proposal, I suggest that careful attention to these two senses of recruitment helps to reveal further constructive ways of developing the extended mind thesis. (shrink)

Predictive processing (PP) accounts of perception are unique not merely in that they postulate a unity between perception and imagination. Rather, they are unique in claiming that perception should be conceptualised in terms of imagination and that the two involve an identity of neural implementation. This paper argues against this postulated unity, on both conceptual and empirical grounds. Conceptually, the manner in which PP theorists link perception and imagination belies an impoverished account of imagery as cloistered from the (...) external world in its intentionality, akin to a virtual reality, as well as endogenously generated. Yet this ignores a whole class of imagery whose intentionality is directed on the actual environment—projected mental imagery—and also ignores the fact that imagery may be triggered crossmodally in a bottom-up, stimulus-driven way. Empirically, claiming that imagery and perception share neural circuitry ignores relevant clinical results in this area. These evidence substantial perception/imagery neural dissociations, most notably in the case of aphantasia. Taken together, the arguments here suggest that PP theorists should substantially temper, if not outright abandon, their claim to a perception/imagination unity. (shrink)

Consciousness vehicle externalism is the claim that the material machinery of a subject’s phenomenology partially leaks outside a subject’s brain, encompassing bodily and environmental structures. The DEUTS argument is the most prominent argument for CVE in the sensorimotor enactivists’ arsenal. In a recent series of publications, Kirchhoff and Kiverstein have deployed such an argument to claim that a prominent view of neural processing, namely predictive processing, is fully compatible with CVE. Indeed, in Kirchhoff and Kiverstein’s view, a (...) proper understanding of predictive processing mandates CVE. In this essay, we critically examine Kirchhoff and Kiverstein’s argument. Our aim is to argue in favor of the following three points. First, that Kirchhoff and Kiverstein’s emphasis on cultural practices lends no support to CVE: at best, it vindicates some form of content externalism about phenomenal content. Secondly, the criteria Kirchhoff and Kiverstein propose to identify a subject’s phenomenal machinery greatly overgeneralize, leaving them open to a “consciousness bloat” objection, which is an analog of the cognitive bloat objection against the extended mind. Lastly, we will argue that the “consciousness bloat” problem is inbuilt in the very argumentative structure of the DEUTS argument. We will thus conclude that, contrary to the philosophical mainstream, DEUTS is not the best argument for CVE in the sensorimotor enactivists’ argumentative arsenal. (shrink)

The direct social perception thesis claims that we can directly perceive some mental states of other people. The direct perception of mental states has been formulated phenomenologically and psychologically, and typically restricted to the mental state types of intentions and emotions. I will compare DSP to another account of mindreading: dual process accounts that posit a fast, automatic “Type 1” form of mindreading and a slow, effortful “Type 2” form. I will here analyze whether dual process accounts’ Type 1 mindreading (...) serves as a rival to DSP or whether some Type 1 mindreading can be perceptual. I will focus on Apperly and Butterfill’s dual process account of mindreading epistemic states such as perception, knowledge, and belief. This account posits a minimal form of Type 1 mindreading of belief-like states called registrations. I will argue that general dual process theories fit well with a modular view of perception that is considered a kind of Type 1 process. I will show that this modular view of perception challenges and has significant advantages over DSP’s phenomenological and psychological theses. Finally, I will argue that if such a modular view of perception is accepted, there is significant reason for thinking Type 1 mindreading of belief-like states is perceptual in nature. This would mean extending the scope of DSP to at least one type of epistemic state. (shrink)

I discuss Clark’s predictive processing/extended mind hybrid, diagnosing a problem: Clark’s hybrid suggests that, when we use them, we pay attention to mind-extending external resources. This clashes with a commonly accepted necessary condition of cognitive extension; namely, that mind-extending resources must be phenomenally transparent when used. I then propose a solution to this problem claiming that the phenomenal transparency condition should be rejected. To do so, I put forth a parity argument to the effect that phenomenal transparency cannot (...) be a necessary condition on cognitive extension: roughly, since internal cognitive resources can fail to be transparent when used, by parity, external resources can fail to be phenomenally transparent too. Further, I argue that phenomenal transparency is not even a reliable indicator of cognitive extension; hence its absence should not be considered a problem for Clark’s extended mind-predictive processing hybrid. Lastly, I consider and allay a number of worries my proposal might raise, and conclude the paper. (shrink)

Our intuition tells us that there is a general trend in the evolution of nature, a trend towards greater complexity. However, there are several definitions of complexity and hence it is difficult to argue for or against the validity of this intuition. Christoph Adami has recently introduced a novel measure called physical complexity that assigns low complexity to both ordered and random systems and high complexity to those in between. Physical complexity measures the amount of information that an organism stores (...) in its genome about the environment in which it evolves. The theory of physical complexity predicts that evolution increases the amount of ‘knowledge’ an organism accumulates about its niche. It might be fruitful to generalize Adami’s concept of complexity to the entire evolution (including the evolution of man). Physical complexity fits nicely into the philosophical framework of cognitive biology which considers biological evolution as a progressing process of accumulation of knowledge (as a gradual increase of epistemic complexity). According to this paradigm, evolution is a cognitive ‘ratchet’ that pushes the organisms unidirectionally towards higher complexity. Dynamic environment continually creates problems to be solved. To survive in the environment means to solve the problem, and the solution is an embodied knowledge. Cognitive biology (as well as the theory of physical complexity) uses the concepts of information and entropy and views the evolution from both the information-theoretical and thermodynamical perspective. Concerning humans as conscious beings, it seems necessary to postulate an emergence of a new kind of knowledge - a self-aware and self-referential knowledge. Appearence of selfreflection in evolution indicates that the human brain reached a new qualitative level in the epistemic complexity. (shrink)

Many philosophers claim that the neurocomputational framework of predictive processing entails a globally inferentialist and representationalist view of cognition. Here, I contend that this is not correct. I argue that, given the theoretical commitments these philosophers endorse, no structure within predictive processing systems can be rightfully identified as a representational vehicle. To do so, I first examine some of the theoretical commitments these philosophers share, and show that these commitments provide a set of necessary conditions (...) the satisfaction of which allows us to identify representational vehicles. Having done so, I introduce a predictive processing system capable of active inference, in the form of a simple robotic “brain”. I examine it thoroughly, and show that, given the necessary conditions highlighted above, none of its components qualifies as a representational vehicle. I then consider and allay some worries my claim could raise. I consider whether the anti-representationalist verdict thus obtained could be generalized, and provide some reasons favoring a positive answer. I further consider whether my arguments here could be blocked by allowing the same representational vehicle to possess multiple contents, and whether my arguments entail some extreme form of revisionism, answering in the negative in both cases. A quick conclusion follows. (shrink)

Predictive processing is an increasingly popular explanatory framework developed within cognitive neuroscience. It conceives of the brain as a prediction machine that tries to minimise prediction error. Predictive processing has also been employed to explain aspects of conscious experience. In this paper, I critically evaluate current predictive processing approaches to the phenomenology of time-consciousness from a Husserlian perspective. To do so, I introduce the notion of orthodox predictive processing to refer to interpretations (...) of the predictive processing framework that subscribe to representational views of cognition. As it turns out, current predictive processing accounts of time-consciousness are orthodox given their commitment to representational views of both brain functioning and perception, and, on the other hand, their reliance on the primacy of imagination over perception. However, I argue that such accounts are in fact closer to a Kantian-Brentanian approach to the phenomenology of time-consciousness than to the Husserlian account that they attempt to account for. (shrink)

Sometimes we learn through the use of imagination. The epistemology of imagination asks how this is possible. One barrier to progress on this question has been a lack of agreement on how to characterize imagination; for example, is imagination a mental state, ability, character trait, or cognitive process? This paper argues that we should characterize imagination as a cognitive ability, exercises of which are cognitive processes. Following dual process theories of cognition developed in cognitive science, the set of imaginative (...) processes is then divided into two kinds: one that is unconscious, uncontrolled, and effortless, and another that is conscious, controlled, and effortful. This paper outlines the different epistemological strengths and weaknesses of the two kinds of imaginative process, and argues that a dual process model of imagination helpfully resolves or clarifies issues in the epistemology of imagination and the closely related epistemology of thought experiments. (shrink)