The development of predictive brain implant (PBI) technology that is able to forecast specific neuronal events and advise and/or automatically administer appropriate therapy for diseases of the brain raises a number of ethical issues. Provided that this technology satisfies basic safety and functionality conditions, one of the most pressing questions to address is its relation to the autonomy of patients. As Frederic Gilbert in his article asks, if autonomy implies a certain idea of freedom, or self-government, how (...) can an individual be considered to decide freely if the implanted device stands at the inception of the causal chain producing his decisions? He claims that PBIs threaten persons’ autonomy by diminishing their post-operative experience of self-control. In this commentary, I wish to discuss this claim. Contrary to Gilbert, I will suggest that PBIs do not pose a significant threat to patient’s autonomy, as self-control, but rather to his/her sense of authenticity. My claim is that the language of authenticity, already introduced in the recent bioethical literature, may offer a better way to voice some of the concerns with PBIs that Gilbert recognized. (shrink)

Is any unified theory of brain function possible? Following a line of thought dat- ing back to the early cybernetics (see, e.g., Cordeschi, 2002), Clark (in press) has proposed the action-oriented Hierarchical Predictive Coding (HPC) as the account to be pursued in the effort of gain- ing the “Grand Unified Theory of the Mind”—or “painting the big picture,” as Edelman (2012) put it. Such line of thought is indeed appealing, but to be effectively pursued it should be confronted (...) with experimental findings and explana- tory capabilities (Edelman, 2012). The point we are making in this note is that a brain with predictive capa- bilities is certainly necessary to endow the agent situated in the environment with forethought or foresight, a crucial issue to outline the unified account advocated by Clark. But the capacity for fore- thought is deeply entangled with the capacity for emotions and when emotions are brought into the game, cogni- tive functions become part of a large-scale functional brain network. However, for such complex networks a consistent view of hierarchical organization in large-scale functional networks has yet to emerge (Bressler and Menon, 2010), whilst heterarchical organization is likely to play a strategic role (Berntson et al., 2012). This raises the necessity of a multilevel approach that embraces causal relations across levels of explanation in either direc- tion (bottom–up or top–down), endorsing mutual calibration of constructs across levels (Berntson et al., 2012). Which, in turn, calls for a revised perspective on Marr’s levels of analysis framework (Marr, 1982). In the following we highlight some drawbacks of Clark’s proposal in address- ing the above issues. (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)

A cognitivist account of decision-making views choice behaviour as a serial process of deliberation and commitment, which is separate from perception and action. By contrast, recent work in embodied decision-making has argued that this account is incompatible with emerging neurophysiological data. We argue that this account has significant overlap with an embodied account of predictive processing, and that both can offer mutual development for the other. However, more importantly, by demonstrating this close connection we uncover an alternative perspective on (...) the nature of decision-making, and the mechanisms that underlie our choice behaviour. This alternative perspective allows us to respond to a challenge for predictive processing, which claims that the satisfaction of distal goal-states is underspecified. Answering this challenge requires the adoption of an embodied perspective. (shrink)

According to the predictive coding theory of cognition , brains are predictive machines that use perception and action to minimize prediction error, i.e. the discrepancy between bottom–up, externally-generated sensory signals and top–down, internally-generated sensory predictions. Many consider PCT to have an explanatory scope that is unparalleled in contemporary cognitive science and see in it a framework that could potentially provide us with a unified account of cognition. It is also commonly assumed that PCT is a representational theory of (...) sorts, in the sense that it postulates that our cognitive contact with the world is mediated by internal representations. However, the exact sense in which PCT is representational remains unclear; neither is it clear that it deserves such status—that is, whether it really invokes structures that are truly and nontrivially representational in nature. In the present article, I argue that the representational pretensions of PCT are completely justified. This is because the theory postulates cognitive structures—namely action-guiding, detachable, structural models that afford representational error detection—that play genuinely representational functions within the cognitive system. (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)

In this paper an Artificial Neural Network (ANN) model, for predicting the category of a tumor was developed and tested. Taking patients’ tests, a number of information gained that influence the classification of the tumor. Such information as age, sex, histologic-type, degree-of-diffe, status of bone, bone-marrow, lung, pleura, peritoneum, liver, brain, skin, neck, supraclavicular, axillar, mediastinum, and abdominal. They were used as input variables for the ANN model. A model based on the Multilayer Perceptron Topology was established and trained (...) using data set which its title is “primary tumor” and was obtained from the University Medical Centre, Institute of Oncology, Ljubljana, Yugoslavia Test data evaluation shows that the ANN model is able to correctly predict the tumor category with 76.67 % accuracy. (shrink)

Predictive processing models of perception take issue with standard models of perception as hierarchical bottom-up processing modulated by memory and attention. The predictive framework posits that the brain generates predictions about stimuli, which are matched to the incoming signal. Mismatches between predictions and the incoming signal – so-called prediction errors – are then used to generate new and better predictions until the prediction errors have been minimized, at which point a perception arises. Predictive models hold that (...) all bottom-up processes are signals conveying prediction errors to higher areas, which respond by updating their predictions. We take issue with this claim and argue that object recognition requires bottom-up processing that cannot be understood in terms of prediction errors. Along the way, we expand on previous work casting doubt on the framework's ability to account for attention. Specifically, we argue that the type of attention that allows us to rapidly extract the gist of an object or scene presents an additional challenge to the predictive approach. We conclude by considering how the framework may be augmented to avoid these problems. (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)

Prediction Error Minimization theory (PEM) is one of the most promising attempts to model perception in current science of mind, and it has recently been advocated by some prominent philosophers as Andy Clark and Jakob Hohwy. Briefly, PEM maintains that “the brain is an organ that on aver-age and over time continually minimizes the error between the sensory input it predicts on the basis of its model of the world and the actual sensory input” (Hohwy 2014, p. 2). An (...) interesting debate has arisen with regard to which is the more adequate epistemological interpretation of PEM. Indeed, Hohwy maintains that given that PEM supports an inferential view of perception and cognition, PEM has to be considered as conveying an internalist epistemological perspective. Contrary to this view, Clark maintains that it would be incorrect to interpret in such a way the indirectness of the link between the world and our inner model of it, and that PEM may well be combined with an externalist epistemological perspective. The aim of this paper is to assess those two opposite interpretations of PEM. Moreover, it will be suggested that Hohwy’s position may be considerably strengthened by adopting Carlo Cellucci’s view on knowledge (2013). (shrink)

An exciting theory in neuroscience is that the brain is an organ for prediction error minimization. This theory is rapidly gaining influence and is set to dominate the science of mind and brain in the years to come. PEM has extreme explanatory ambition, and profound philosophical implications. Here, I assume the theory, briefly explain it, and then I argue that PEM implies that the brain is essentially self-evidencing. This means it is imperative to identify an evidentiary boundary (...) between the brain and its environment. This boundary defines the mind-world relation, opens the door to skepticism, and makes the mind transpire as more inferentially secluded and neurocentrically skull-bound than many would nowadays think. Therefore, PEM somewhat deflates contemporary hypotheses that cognition is extended, embodied and enactive; however, it can nevertheless accommodate the kinds of cases that fuel these hypotheses. (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)

Some modern cosmological models predict the appearance of Boltzmann Brains: observers who randomly fluctuate out of a thermal bath rather than naturally evolving from a low-entropy Big Bang. A theory in which most observers are of the Boltzmann Brain type is generally thought to be unacceptable, although opinions differ. I argue that such theories are indeed unacceptable: the real problem is with fluctuations into observers who are locally identical to ordinary observers, and their existence cannot be swept under the (...) rug by a choice of probability distributions over observers. The issue is not that the existence of such observers is ruled out by data, but that the theories that predict them are cognitively unstable: they cannot simultaneously be true and justifiably believed. (shrink)

A recent surge of work on prediction-driven processing models--based on Bayesian inference and representation-heavy models--suggests that the material basis of conscious experience is inferentially secluded and neurocentrically brain bound. This paper develops an alternative account based on the free energy principle. It is argued that the free energy principle provides the right basic tools for understanding the anticipatory dynamics of the brain within a larger brain-body-environment dynamic, viewing the material basis of some conscious experiences as extensive--relational and (...) thoroughly world-involving. (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 (...) class='Hi'>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)

In his paper, Jakob Hohwy outlines a theory of the brain as an organ for prediction-error minimization, which he claims has the potential to profoundly alter our understanding of mind and cognition. One manner in which our understanding of the mind is altered, according to PEM, stems from the neurocentric conception of the mind that falls out of the framework, which portrays the mind as “inferentially-secluded” from its environment. This in turn leads Hohwy to reject certain theses of embodied (...) cognition. Focusing on this aspect of Hohwy’s argument, we first outline the key components of the PEM framework such as the “evidentiary boundary,” before looking at why this leads Hohwy to reject certain theses of embodied cognition. We will argue that although Hohwy may be correct to reject specific theses of embodied cognition, others are in fact implied by the PEM framework and may contribute to its development. We present the metaphor of the “body as a laboratory” in order to highlight wha... (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)

In light of technology that may reveal the content of a person’s innermost thoughts, I address the question of whether there is a right to ‘brain privacy’—a right not to have one’s inner thoughts revealed to others–even if exposing these thoughts might be beneficial to society. I draw on a conception of privacy as the ability to control who has access to information about oneself and to an account that connects one’s interest in privacy to one’s interests in autonomy (...) and associated reputational interests, and preserving one’s dignity. Focusing on the controversial case of Gilberto Valle, known as the ‘cannibal cop’, who faced legal punishment and moral reproach for deeply disturbing thoughts of doing violence to women, thoughts he claimed were mere fantasies, I argue that Valle has a right to brain privacy if he has a legitimate privacy interest that is not outweighed by competing societal interests in avoiding harm. Our weighing of competing privacy and societal interests will depend on the magnitude of the privacy interests in autonomy and dignity, and on how reliable the technology used to expose inner thoughts is in predicting future harmful behavior and identifying true threats. (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)

Respiratory rhythms sustain biological life, governing the homeostatic exchange of oxygen and carbon dioxide. Until recently, however, the influence of breathing on the brain has largely been overlooked. Yet new evidence demonstrates that the act of breathing exerts a substantive, rhythmic influence on perception, emotion, and cognition, largely through the direct modulation of neural oscillations. Here, we synthesize these findings to motivate a new predictive coding model of respiratory brain coupling, in which breathing rhythmically modulates both local (...) and global neural gain, to optimize cognitive and affective processing. Our model further explains how respiratory rhythms interact with the topology of the functional connectome, and we highlight key implications for the computational psychiatry of disordered respiratory and interoceptive inference. (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)

Parts of the genome of a single individual can have conflicting interests, depending on which parent they were inherited from. One mechanism by which these conflicts are expressed in some taxa, including mammals, is genomic imprinting, which modulates the level of expression of some genes depending on their parent of origin. Imprinted gene expression is known to affect body size, brain size, and the relative development of various tissues in mammals. A high fraction of imprinted gene expression occurs in (...) the brain. Biologists including Hamilton, Trivers and Haig have proposed that this may explain some intrapersonal conflict in humans. This speculation amounts to an inference from conflict within the genome to conflict within the brain or mind. This is a provocative proposal, which deserves serious attention. In this paper I assess aspects of Haig’s version of the proposal. I argue, first, that the notion that intragenomic conflict predicts personal inconsistency should be rejected. Second, while it is unlikely that it credibly predicts sub-personal agents representing conflicting genetic interests, it is plausible that it predicts that the division of cognitive labour could be exploited to turn sub-systems into proxies for conflicting interests. (shrink)

The human brain consists of approximately 100 billion electrically active neurones that generate an endogenous electromagnetic field, whose role in neuronal computing has not been fully examined. The source, magnitude and likely influence of the brain's endogenous em field are here considered. An estimate of the strength and magnitude of the brain's em field is gained from theoretical considerations, brain scanning and microelectrode data. An estimate of the likely influence of the brain's em field is (...) gained from theoretical principles and considerations of the experimental effects of external em fields on neurone firing both in vitro and in vivo. Synchronous firing of distributed neurones phase-locks induced em field fluctuations to increase their magnitude and influence. Synchronous firing has previously been demonstrated to correlate with awareness and perception, indicating that perturbations to the brain's em field also correlate with awareness. The brain's em field represents an integrated electromagnetic field representation of distributed neuronal information and has dynamics that closely map to those expected for a correlate of consciousness. I propose that the brain's em information field is the physical substrate of conscious awareness - the cemi field - and make a number of predictions that follow from this proposal. Experimental evidence pertinent to these predictions is examined and shown to be entirely consistent with the cemi field theory. This theory provides solutions to many of the intractable problems of consciousness - such as the binding problem - and provides new insights into the role of consciousness, the meaning of free will and the nature of qualia. It thus places consciousness within a secure physical framework and provides a route towards constructing an artificial consciousness. (shrink)

According to one theory, the brain is a sophisticated hypothesis tester: perception is Bayesian unconscious inference where the brain actively uses predictions to test, and then refine, models about what the causes of its sensory input might be. The brain’s task is simply continually to minimise prediction error. This theory, which is getting increasingly popular, holds great explanatory promise for a number of central areas of research at the intersection of philosophy and cognitive neuroscience. I show how (...) the theory can help us understand striking phenomena at three cognitive levels: vision, sensory integration, and belief. First, I illustrate central aspects of the theory by showing how it provides a nice explanation of why binocular rivalry occurs. Then I suggest how the theory may explain the role of the unified sense of self in rubber hand and full body illusions driven by visuotactile conflict. Finally, I show how it provides an approach to delusion formation that is consistent with one-deficit accounts of monothematic delusions. (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)

In recent years, neuroscience has begun to transform itself into a “big data” enterprise with the importation of computational and statistical techniques from machine learning and informatics. In addition to their translational applications such as brain-computer interfaces and early diagnosis of neuropathology, these tools promise to advance new solutions to longstanding theoretical quandaries. Here I critically assess whether these promises will pay off, focusing on the application of multivariate pattern analysis (MVPA) to the problem of reverse inference. I argue (...) that MVPA does not inherently provide a new answer to classical worries about reverse inference, and that the method faces pervasive interpretive problems of its own. Further, the epistemic setting of MVPA and other decoding methods contributes to a potentially worrisome shift towards prediction and away from explanation in fundamental neuroscience. (shrink)

This commentary (1) raises the question about the possible conflation of core affect with the neural representation of interoceptive changes in regard to whether biological value is subpersonal or must be experienced, and (2) proposes that Wundt’s third dimension of core affect – strain-relaxation – can be accounted for in the target model under a generalised predictive model of attention.

Proponents of the predictive processing (PP) framework often claim that one of the framework’s significant virtues is its unificatory power. What is supposedly unified are predictive processes in the mind, and these are explained in virtue of a common prediction error-minimisation (PEM) schema. In this paper, I argue against the claim that PP currently converges towards a unified explanation of cognitive processes. Although the notion of PEM systematically relates a set of posits such as ‘efficiency’ and ‘hierarchical coding’ (...) into a unified conceptual schema, neither the frameworks’ algorithmic specifications nor its hypotheses about their implementations in the brain are clearly unified. I propose a novel way to understand the fruitfulness of the research program in light of a set of research heuristics that are partly shared with those common to Bayesian reverse engineering. An interesting consequence of this proposal is that pluralism is at least as important as unification to promote the positive development of the predictive mind. (shrink)

Sertraline is one of the most commonly prescribed antidepressants. Major depressive disorder (MDD) is characterized by spontaneous thoughts that are laden with negative affect-a "malignant sadness". Prior neuroimaging studies have identified abnormal resting-state functional connectivity (rsFC) in the spontaneous brain networks of MDD patients. But how antidepressant medication acts to relieve the experience of depression as well as adjust its associated spontaneous networks and mood-regulation circuits remains an open question. In this study, we recruited 22 drug-naïve MDD patients along (...) with 35 normal controls and investigated whether the functional integrity of cortical networks associated with spontaneous thoughts is modulated by sertraline treatment. We attempted to predict post-treatment effects based upon what we observed in the pre-treatment rsFC of drug-naïve MDD patients. In the result, we demonstrated that (1) after the sertraline treatment, the medial temporal lobe of default network (DNMTL) and mood regulation pathway-the fronto-parietal control network (FPCN), the thalamus, and the salience network (SN)-were restored to normal connectivity, relative to the pre-treatment condition; however, the altered connections of FPCN-core DN (DNCORE), FPCN-SN, and intra-FPCN among MDD patients remained impaired; (2) thalamo-prefrontal connectivity provides moderate predictive power (r2 = 0.63) for the effectiveness of sertraline treatment. In summary, our findings contribute to a body of evidence that suggests salubrious effects of sertraline treatment primarily involve the FPCN-thalamus-SN pathway. The pre-treatment rsFC in this pathway could serve as a predictor of sertraline treatment outcome. (shrink)

Leading cosmological theories engender a controversial puzzle which has prompted philosophers to propose competing epistemological solutions and physicists to propose methodological changes to cosmology. The puzzle arises from the prediction that every brain on Earth will eventually be vastly outnumbered by physical duplicates formed by random collisions of particles in outer space. Supposing that this prediction is correct, shouldn't you believe that your brain is probably one of these vastly more typical extraterrestrial brains, since you cannot infer your (...) brain's origin from your experiential state? But supposing that your brain is one of these extraterrestrial brains, why be confident in the cosmological theories, since you never actually received testimony supporting these theories? Proposals in the literature either deny the rationality of believing theories that make the prediction or deny the typicality of your brain among its duplicates. This paper argues that these proposals are not entirely satisfactory. Instead, one should be confident in theories making the prediction on the supposition that your brain is one of the extraterrestrial brains. The upshots include that it may be rational to believe that your brain is probably an extraterrestrial brain and that cosmologists should not alter their methodology in response to the puzzle. (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)

Skeptical hypotheses such as the brain-in-a-vat hypothesis provide extremely poor explanations for our sensory experiences. Because these scenarios accommodate virtually any possible set of evidence, the probability of any given set of evidence on the skeptical scenario is near zero; hence, on Bayesian grounds, the scenario is not well supported by the evidence. By contrast, serious theories make reasonably specific predictions about the evidence and are then well supported when these predictions are satisfied.

Some physical theories predict that almost all brains in the universe are Boltzmann brains, i.e. short-lived disembodied brains that are accidentally assembled as a result of thermodynamic or quantum fluctuations. Physicists and philosophers of physics widely regard this proliferation as unacceptable, and so take its prediction as a basis for rejecting these theories. But the putatively unacceptable consequences of this prediction follow only given certain philosophical assumptions. This paper develops a strategy for shielding physical theorizing from the threat of Boltzmann (...) brains. The strategy appeals to a form of phenomenal externalism about the physical basis of consciousness. Given that form of phenomenal externalism, the proliferation of Boltzmann brains turns out to be benign. While the strategy faces a psychophysical fine-tuning problem, it both alleviates cosmological fine-tuning concerns that attend physics-based solutions to Boltzmann brain problems and pays explanatory dividends in connection with time’s arrow. (shrink)

In the following review of Hohwy ‘The Predictive Mind’, I argue that enactive considerations can be used to challenge Hohwy’s claim that the brain is a ‘truth tracker’.

Disorders of consciousness (DoC)—that is, unresponsive wakefulness syndrome/vegetative state and minimally conscious state—are debilitating conditions for which no reliable markers of consciousness recovery have yet been identified. Evidence points to the GABAergic system being altered in DoC, making it a potential target as such a marker.

Whilst much has been said about the implications of predictive processing for our scientific understanding of cognition, there has been comparatively little discussion of how this new paradigm fits with our everyday understanding of the mind, i.e. folk psychology. This paper aims to assess the relationship between folk psychology and predictive processing, which will first require making a distinction between two ways of understanding folk psychology: as propositional attitude psychology and as a broader folk psychological discourse. It will (...) be argued that folk psychology in this broader sense is compatible with predictive processing, despite the fact that there is an apparent incompatibility between predictive processing and a literalist interpretation of propositional attitude psychology. The distinction between these two kinds of folk psychology allows us to accept that our scientific usage of folk concepts requires revision, whilst rejecting the suggestion that we should eliminate folk psychology entirely. (shrink)

Spontaneous activity levels prior to stimulus presentation can determine how that stimulus will be perceived. It has also been proposed that such spontaneous activity, particularly in the default-mode network (DMN), is involved in self-related processing. We therefore hypothesised that pre-stimulus activity levels in the DMN predict whether a stimulus is judged as self-related or not. Method: Participants were presented in the MRI scanner with a white noise stimulus that they were instructed contained their name or another. They then had to (...) respond with which name they thought they heard. Regions where there was an activity level difference between self and other response trials two seconds prior to the stimulus being presented were identified. Results: Pre-stimulus activity levels were higher in the right temporoparietal junction (RTPJ), the right temporal pole (RTP), and the left superior temporal gyrus in trials where the participant responded that they heard their own name than trials where they responded that they heard another. Conclusion: Pre-stimulus spontaneous activity levels in particular brain regions, largely overlapping with the DMN, predict the subsequent judgement of stimuli as self-related. This extends our current knowledge of self-related processing and its apparent relationship with intrinsic brain activity in what can be termed a rest-self overlap. (shrink)

A central debate in philosophy and neuroscience pertains to whether PFC activity plays an essential role in the neural basis of consciousness. Neuroimaging and electrophysiology studies have revealed that the contents of conscious perceptual experience can be successfully decoded from PFC activity, but these findings might be confounded by post- perceptual cognitive processes, such as thinking, reasoning, and decision-making, that are not necessary for con- sciousness. To clarify the involvement of the PFC in consciousness, we present a synthesis of research (...) that has used intracranial electrical stimulation (iES) for the causal modulation of neural activity in the human PFC. This research provides compelling evidence that iES of only certain prefrontal regions (i.e., orbitofrontal cortex and anterior cingu- late cortex) reliably perturbs conscious experience. Conversely, stimulation of anterolateral prefrontal sites, often con- sidered crucial in higher-order and global workspace theories of consciousness, seldom elicits any reportable alterations in consciousness. Furthermore, the wide variety of iES-elicited effects in the PFC (e.g., emotions, thoughts, and olfactory and visual hallucinations) exhibits no clear relation to the immediate environment. Therefore, there is no evidence for the kinds of alterations in ongoing perceptual experience that would be predicted by higher-order or global workspace theories. Nevertheless, effects in the orbitofrontal and anterior cingulate cortices suggest a specific role for these PFC subregions in supporting emotional aspects of conscious experience. Overall, this evidence presents a challenge for higher-order and global workspace theories, which commonly point to the PFC as the basis for con- scious perception based on correlative and possibly confounded information. (shrink)

The abstract basis of modern computation is the formal description of a finite state machine, the Universal Turing Machine, based on manipulation of integers and logic symbols. In this contribution to the discourse on the computer-brain analogy, we discuss the extent to which analog computing, as performed by the mammalian brain, is like and unlike the digital computing of Universal Turing Machines. We begin with ordinary reality being a permanent dialog between continuous and discontinuous worlds. So it is (...) with computing, which can be analog or digital, and is often mixed. The theory behind computers is essentially digital, but efficient simulations of phenomena can be performed by analog devices; indeed, any physical calculation requires implementation in the physical world and is therefore analog to some extent, despite being based on abstract logic and arithmetic. The mammalian brain, comprised of neuronal networks, functions as an analog device and has given rise to artificial neural networks that are implemented as digital algorithms but function as analog models would. Analog constructs compute with the implementation of a variety of feedback and feedforward loops. In contrast, digital algorithms allow the implementation of recursive processes that enable them to generate unparalleled emergent properties. We briefly illustrate how the cortical organization of neurons can integrate signals and make predictions analogically. While we conclude that brains are not digital computers, we speculate on the recent implementation of human writing in the brain as a possible digital path that slowly evolves the brain into a genuine (slow) Turing machine. (shrink)

When dissimilar images are presented to the two eyes, binocular rivalry (BR) occurs, and perception alternates spontaneously between the images. Although neural correlates of the oscillating perception during BR have been found in multiple sites along the visual pathway, the source of BR dynamics is unclear. Psychophysical and modeling studies suggest that both low- and high-level cortical processes underlie BR dynamics. Previous neuroimaging studies have demonstrated the involvement of high-level regions by showing that frontal and parietal cortices responded time locked (...) to spontaneous perceptual alternation in BR. However, a potential contribution of early visual areas to BR dynamics has been overlooked, because these areas also responded to the physical stimulus alternation mimicking BR. In the present study, instead of focusing on activity during perceptual switches, we highlighted brain activity during suppression periods to investigate a potential link between activity in human early visual areas and BR dynamics. We used a strong interocular suppression paradigm called continuous flash suppression to suppress and fluctuate the visibility of a probe stimulus and measured retinotopic responses to the onset of the invisible probe using functional MRI. There were ∼130-fold differences in the median suppression durations across 12 subjects. The individual differences in suppression durations could be predicted by the amplitudes of the retinotopic activity in extrastriate visual areas (V3 and V4v) evoked by the invisible probe. Weaker responses were associated with longer suppression durations. These results demonstrate that retinotopic representations in early visual areas play a role in the dynamics of perceptual alternations during BR. (shrink)

Ontologies formally represent reality in a way that limits ambiguity and facilitates automated reasoning and data fusion, but is often daunting to the non-technical user. Thus, many researchers have endeavored to hide the formal syntax and semantics of ontologies behind the constructs of Controlled Natural Languages (CNLs), which retain the formal properties of ontologies while simultaneously presenting that information in a comprehensible natural language format. In this paper, we build upon previous work in this field by evaluating prospects of implementing (...) International Technology Alliance Controlled English (ITACE) as a middleware for ontology editing. We also discuss at length a prototype of a natural language conversational interface application designed to facilitate ontology editing via the formulation of CNL constructs. (shrink)

How tight is the conceptual connection between imagination and perception? A number of philosophers, from the early moderns to present-day predictive processing theorists, tie the knot as tightly as they can, claiming that states of the imagination, i.e. mental imagery, are a proper subset of perceptual experience. This paper labels such a view ‘perceptualism’ about the imagination and supplies new arguments against it. The arguments are based on high-level perceptual content and, distinctly, cognitive penetration. The paper also defuses a (...) recent, influential argument for perceptualism based on the ‘discovery’ that visual perception and mental imagery share a significant neural substrate: circuitry in V1, the brain’s primary visual cortex. Current neuropsychology is shown to be equivocal at best on this matter. While experiments conducted on healthy, neurotypical subjects indicate substantial neural overlap, there is extensive clinical evidence of dissociations between imagery and perception in the brain, most notably in the case of aphantasia. (shrink)

Predictive processing theorists have claimed PTSD and depression are maladaptive and epistemically distorting because they entail undesirably wide gaps between top-down models and bottom-up information inflows. Without denying this is sometimes so, the “maladaptive” label carries questionable normative assumptions. For instance, trauma survivors facing significant risk of subsequent attacks may overestimate threats to circumvent further trauma, “bringing forth” concretely safer personal spaces, to use enactive terminology, ensuring the desired gap between predicted worries and outcomes. The violation of predictive (...) processing can go in the opposite direction too, as when depression coincides with energy-depletion, and hence objectively strenuous situations in which things look farther away because they are (accurately anticipated to be) harder to reach. These examples partly encapsulate what predictive processing theorists call “active inference,” yet with differences. In the first case, actions fruitfully obviate predictions rather than fulfilling them. In the second, mental models do not dysregulate bodily processes, making coping harder. Instead, problems (e.g., personal obstacles, gastric illness) deplete energy, eliciting a depressive and adaptive slow-down. Some predictive proponents apply correspondence criteria when alleging mismatches between internal models and the world, while incongruously asserting that the brain did not evolve to see things veridically, but to execute actions. An alternative is to adopt pluralistic, pragmatic epistemologies suited to the complexity of mind. The upshot is that mental outlooks can depart from the norm without epistemically being distorted and that mismatches between anticipatory worries and outcomes, when they actually exist, can be a measure of adaptive and epistemic success. (shrink)

Virtue reliabilism provides an account of epistemic integration that explains how a reliable-belief forming process can become a knowledge-conducive ability of one’s cognitive character. The univocal view suggests that this epistemic integration can also explain how an external process can extend one’s cognition into the environment. Andy Clark finds a problem with the univocal view. He claims that cognitive extension is a wholly subpersonal affair, whereas the epistemic integration that virtue reliabilism puts forward requires personal-level agential involvement. To adjust the (...) univocal view, Clark recommends a subpersonal epistemic integration account that also paves way for a wholly subpersonal epistemology. Accordingly, an epistemic agent can take responsibility for her reliable belief-forming process by way of entirely subpersonal mechanisms. The aim of this thesis is to argue against a subpersonal epistemology and the need for it. First, I bring into question the conditions that motivate extended cognition: the so-called ‘glue and trust’ requirements and the functional parity principle. Neither of these conditions demands that extension should be understood in entirely subpersonal terms. On the contrary, the glue and trust conditions suggest that agents should personally and actively engage with their external vehicles to extend cognition. Further, I consider an important disparity between the two kinds of integration. Integration that prompts extension can happen immediately, but the integration that makes a reliable belief-forming process knowledge-conducive is almost always a slow process. In light of this and other similar inconsistencies between the two integration accounts, I conclude that a type of univocal view is difficult to defend. And, since that type of univocal view is the main reason for a subpersonal epistemology, the need for it does not arise. Next, I locate Clark’s main motivation for his subpersonal epistemology in his account of the predictive brain. While the predictive brain provides useful insight into how an external process might extend one’s cognition, I show it runs into problems when it tries to account for epistemic integration. Then, I explore how the concept of epistemic defeaters informs epistemic integration. Agents have to meet a specific no-defeater condition to be sensitive to the reliability of their belief-forming processes and to employ them responsibly. In an entirely subpersonal epistemology, defeasibility theory has no means to explain how an agent is rendered sensitive to the reliability of her process. Subpersonal mechanisms can become sensitive to the new process, but that does not allow the agent to employ said process responsibly. Finally, I use an AI case, based on Amazon Alexa, to argue that all accounts of epistemic integration ought to explicitly describe how one’s subpersonal mechanisms link to one’s whole person, even if the link is weak and indirect. Without this connection between one’s subpersonal mechanisms and one’s person, it can become difficult to ascribe beliefs to the agent. This becomes apparent when Alexa leads to ever-increasing layers of cognitive, mental, and agential extension. (shrink)

The full scope of enactivist approaches to cognition includes not only a focus on sensory-motor contingencies and physical affordances for action, but also an emphasis on affective factors of embodiment and intersubjective affordances for social interaction. This strong conception of embodied cognition calls for a new way to think about the role of the brain in the larger system of brain-body-environment. We ask whether recent work on predictive coding offers a way to think about brain function (...) in an enactive system, and we suggest that a positive answer is possible if we interpret predictive coding in a more enactive way, i.e., as involved in the organism’s dynamic adjustments to its environment. (shrink)

How much does stimulus input shape perception? The common-sense view is that our perceptions are representations of objects and their features and that the stimulus structures the perceptual object. The problem for this view concerns perceptual biases as responsible for distortions and the subjectivity of perceptual experience. These biases are increasingly studied as constitutive factors of brain processes in recent neuroscience. In neural network models the brain is said to cope with the plethora of sensory information by predicting (...) stimulus regularities on the basis of previous experiences. Drawing on this development, this chapter analyses perceptions as processes. Looking at olfaction as a model system, it argues for the need to abandon a stimulus-centred perspective, where smells are thought of as stable percepts, computationally linked to external objects such as odorous molecules. Perception here is presented as a measure of changing signal ratios in an environment informed by expectancy effects from top-down processes. (shrink)

Nick Bostrom’s recently patched ‘‘simulation argument’’ (Bostrom in Philos Q 53:243–255, 2003; Bos- trom and Kulczycki in Analysis 71:54–61, 2011) purports to demonstrate the probability that we ‘‘live’’ now in an ‘‘ancestor simulation’’—that is as a simulation of a period prior to that in which a civilization more advanced than our own—‘‘post-human’’—becomes able to simulate such a state of affairs as ours. As such simulations under consid- eration resemble ‘‘brains in vats’’ (BIVs) and may appear open to similar objections, the (...) paper begins by reviewing objections to BIV-type proposals, specifically those due a presumed mad envatter. In counter example, we explore the motivating rationale behind current work in the development of psychologically realistic social simula- tions. Further concerns about rendering human cognition in a computational medium are confronted through review of current dynamic systems models of cognitive agency. In these models, aspects of the human condition are repro- duced that may in other forms be considered incomputable, i.e., political voice, predictive planning, and consciousness. The paper then argues that simulations afford a unique potential to secure a post-human future, and may be nec- essary for a pre-post-human civilization like our own to achieve and to maintain a post-human situation. Long-s- tanding philosophical interest in tools of this nature for Aristotle’s ‘‘statesman’’ and more recently for E.O. Wilson in the 1990s is observed. Self-extinction-level threats from State and individual levels of organization are compared, and a likely dependence on large-scale psychologically realistic simulations to get past self-extinction-level threats is projected. In the end, Bostrom’s basic argument for the conviction that we exist now in a simulation is reaffirmed. (shrink)

Special Issue “Risks of artificial general intelligence”, Journal of Experimental and Theoretical Artificial Intelligence, 26/3 (2014), ed. Vincent C. Müller. http://www.tandfonline.com/toc/teta20/26/3# - Risks of general artificial intelligence, Vincent C. Müller, pages 297-301 - Autonomous technology and the greater human good - Steve Omohundro - pages 303-315 - - - The errors, insights and lessons of famous AI predictions – and what they mean for the future - Stuart Armstrong, Kaj Sotala & Seán S. Ó hÉigeartaigh - pages 317-342 - - (...) - The path to more general artificial intelligence - Ted Goertzel - pages 343-354 - - - Limitations and risks of machine ethics - Miles Brundage - pages 355-372 - - - Utility function security in artificially intelligent agents - Roman V. Yampolskiy - pages 373-389 - - - GOLEM: towards an AGI meta-architecture enabling both goal preservation and radical self-improvement - Ben Goertzel - pages 391-403 - - - Universal empathy and ethical bias for artificial general intelligence - Alexey Potapov & Sergey Rodionov - pages 405-416 - - - Bounding the impact of AGI - András Kornai - pages 417-438 - - - Ethics of brain emulations - Anders Sandberg - pages 439-457. (shrink)

The notion that the brain is a prediction error minimizer entails, via the notion of Markov blankets and self-evidencing, a form of global scepticism — an inability to rule out evil demon scenarios. This type of scepticism is viewed by some as a sign of a fatally flawed conception of mind and cognition. Here I discuss whether this scepticism is ameliorated by acknowledging the role of action in the most ambitious approach to prediction error minimization, namely under the free (...) energy principle. I argue that the scepticism remains but that the role of action in the free energy principle constrains the demon’s work. This yields new insights about the free energy principle, epistemology, and the place of mind in nature. (shrink)