Andrew Clark

The notion of folk‐psychology as a primitive speculative theory of the mental is called into question. There is cause to believe that folk‐psychology has more in common with a naive physics than with early speculative physical theorising. The distinction between these is elaborated. The conclusion drawn is that commonsense ascription of psychological content, though not a suitable finishing point for cognitive science, should still provide a more reliable source of data than some contemporary theorists are willing to admit.

How do intelligent agents spawn and exploit integrated processing regimes spanning brain, body, and world? The answer may lie in the ability of the biological brain to select actions and policies in the light of counterfactual predictions – predictions about what kinds of futures will result if such-and-such actions are launched. Appeals to the minimization of ‘counterfactual prediction errors’ (the ones that would result under various scenarios) already play a leading role in attempts to apply the basic toolkit of the neurocomputational theory known as ‘predictive processing’ to higher cognitive functions such as policy selection and planning. In this paper, I show that this also leads naturally to the discovery and use of extended processing regimes defined across heterogeneous mixtures of biological and non-biological resource. This solves a long-standing puzzle concerning the ‘recruitment’ of the right non-neural processing resources at the right time. It reveals how (and why) human brains spawn and maintain extended human minds.

Cognitive science is in some sense the science of the mind. But an increasingly influential theme, in recent years, has been the role of the physical body, and of the local environment, in promoting adaptive success. No right-minded cognitive scientist, to be sure, ever claimed that body and world were completely irrelevant to the understanding of mind. But there was, nonetheless, an unmistakeable tendency to marginalize such factors: to dwell on inner complexity whilst simplifying or ignoring the complex inner-outer interplays that characterize the bulk of basic biological problem-solving. This tendency was expressed in, for example, the development of planning algorithms that treated real-world action as merely a way of implementing solutions arrived at by pure cognition (more recent work, by contrast, allows such actions to play important computational and problem-solving roles). It also surfaced in David Marr's depiction of the task of vision as the construction of a detailed threedimensional image of the visual scene. For possession of such a rich inner model effectively allows the system to ‘throw away’ the world and to focus subsequent computational activity on the inner model alone.

Does the material basis of conscious experience extend beyond the boundaries of the brain and central nervous system? In Clark 2009 I reviewed a number of ‘enactivist’ arguments for such a view and found none of them compelling. Ward (2012) rejects my analysis on the grounds that the enactivist deploys an essentially world-involving concept of experience that transforms the argumentative landscape in a way that makes the enactivist conclusion inescapable. I present an alternative (prediction-and-generative-model-based) account that neatly accommodates all the positive evidence that Ward cites on behalf of this enactivist conception, and that (I argue) makes richer and more satisfying contact with the full sweep of human experience.

Connectionism and classicism, it generally appears, have at least this much in common: both place some notion of internal representation at the heart of a scientific study of mind. In recent years, however, a much more radical view has gained increasing popularity. This view calls into question the commitment to internal representation itself. More strikingly still, this new wave of anti-representationalism is rooted not in armchair theorizing but in practical attempts to model and understand intelligent, adaptive behavior. In this paper we first present, and then critically assess, a variety of recent anti-representationalist treatments. We suggest that so far, at least, the sceptical rhetoric outpaces both evidence and argument. Some probable causes of this premature scepticism are isolated. Nonetheless, the anti-representationalist challenge is shown to be both important and progressive insofar as it forces us to see beyond the bare representational/non-representational dichotomy and to recognize instead a rich continuum of degrees and types of representationality.

Neural organization raises, in an especially clear way, a major problem confronting contemporary cognitive science. The problem (the “big issue” of my title) is: What is the relation between the strategies used to solve basic problems of perception and action and those used to solve more abstract or “cognitive” problems? Is there a smooth, incremental route from what Arbib et al. call “instinctual schemas” to higher-level kinds of cognitive prowess? I argue that, despite some suggestive comments, Arbib et al. do not resolve this issue.

Adams and Aizawa, in a series of recent and forthcoming papers,, ) seek to refute, or perhaps merely to terminally embarrass, the friends of the extended mind. One such paper begins with the following illustration: "Question: Why did the pencil think that 2+2=4? Clark's Answer: Because it was coupled to the mathematician" Adams and Aizawa ms p.1 "That" the authors continue "about sums up what is wrong with Clark's extended mind hypothesis". The example of the pencil, they suggest, is just an especially egregious version of a fallacy said to pervade the literature on the extended mind. This fallacy, which they usefully dub the " coupling-constitution fallacy ", is attributed, in varying degrees and manners, to Van Gelder and Port, Clark and Chalmers, Haugeland, Dennett, Clark, Gibbs, and Wilson. The fallacy, of course, is to move from the causal coupling of some object or process to some cognitive agent, to the conclusion that the object or process is part of the cognitive agent, or part of the agent's cognitive processing ms p.2). Proponents of the extended mind and related theses, Adams and Aizawa repeatedly assert, are prone to this fallacy in part because they either ignore or fail to properly appreciate the importance of " the mark of the cognitive" viz the importance of an account of "what makes something a cognitive agent". The positive part of Adams and Aizawa's critique then emerges as a combination of the assertion that this "mark of the cognitive" involves the idea that "cognition is constituted by certain sorts of causal process that involve non-derived contents" and that these processes look to be characterized by psychological laws that turn out to apply to many internal goings-on but not currently to any processes that take place in non-biological tools and artifacts. In what follows, I shall try to show why these arguments display nothing so much as mutual failures of communication: crossed wires concealing a couple of real, important, but much more subterranean, disagreements. In particular, I try to show why the negative considerations advanced by Adams and Aizawa fail to successfully undermine the argument for the extended mind, and why their more radical positive story, unless supplemented by implausible additional claims, fails to cast doubt on the claim that minds like ours can extend into the world.

Recent work in cognitive and computational neuroscience depicts the human brain as a complex, multi-layer prediction engine. This family of models has had great success in accounting for a wide variety of phenomena involving perception, action, and attention. But despite their clear promise as accounts of the neurocomputational origins of perceptual experience, they have not yet been leveraged so as to shed light on the so-called “hard problem” of consciousness—the problem of explaining why and how the world is subjectively experienced at all, and why those experiences seem just the way they do. To address this issue, I motivate and defend a picture of conscious experience as flowing from “generative entanglements” that mix predictions about the world, the body, and our own reactive dispositions.

The paper considers two recent accounts of the difference between human and animal thought. One deflationary account, due to Daniel Dennett, insists that the only real difference lies in our ability to use words and sentences to give artificial precision and determinacy to our mental contents. The other, due to Paul Smolensky, conjectures that we at times deploy a special purpose device (the Conscious Rule Interpreter) whose task is to deal with public, symbolically coded data and commands. Both these accounts make a crucial error. They offer what is in effect an extra top‐level processor to soothe our realist/classical prejudices. But in each case the extra ingredient turns out to be explanatorily hollow. Appealing to language use and language processing alone mistakes a cognitive effect for a cognitive cause. I argue instead that we need to seek a more profound architectural condition which may ground our conscious linguistic abilities but also explains a variety of deeper facts. I sketch a picture which seems to meet those needs and draw out its implications for the debates about belief and about classical Artificial Intelligence.

Recent work in cognitive and computational neuroscience depicts human brains as devices that minimize prediction error signals: signals that encode the difference between actual and expected sensory stimulations. This raises a series of puzzles whose common theme concerns a potential misfit between this bedrock informationtheoretic vision and familiar facts about the attractions of the unexpected. We humans often seem to actively seek out surprising events, deliberately harvesting novel and exciting streams of sensory stimulation. Conversely, we often experience some wellexpected sensations as unpleasant and to-be-avoided. In this paper, I explore several core and variant forms of this puzzle, using them to display multiple interacting elements that together deliver a satisfying solution. That solution requires us to go beyond the discussion of simple information-theoretic imperatives and to recognize the essential role of species-specific prestructuring, epistemic foraging, and cultural practices in shaping the restless, curious, novelty-seeking human mind.

In a short article in the May 2004 edition of Wired magazine (revealingly subtitled “Fear and Loathing on the Human‐Machine Frontier”) the futurist and science fiction writer Bruce Sterling sounds an increasingly familiar alarm. After warning us of the imminent dangers of “brain augmentation” he adds: Another troubling frontier is physical, as opposed to mental, augmentation. Japan has a rapidly growing elderly population and a serious shortage of caretakers. So Japanese roboticists … envision walking wheelchairs and mobile arms that manipulate and fetch. But there's ethical hell at the interfaces, The peripherals may be dizzyingly clever gizmos but the CPU is a human being: old, weak, vulnerable, pitifully limited, possibly senile. (Sterling 2004: 116)

Cognitive niche construction is the process whereby organisms create and maintain cause–effect models of their niche as guides for fitness influencing behavior. Extended mind theory claims that cognitive processes extend beyond the brain to include predictable states of the world. Active inference and predictive processing in cognitive science assume that organisms embody predictive (i.e., generative) models of the world optimized by standard cognitive functions (e.g., perception, action, learning). This paper presents an active inference formulation that views cognitive niche construction as a cognitive function aimed at optimizing organisms' generative models. We call that process of optimization extended active inference.

Recent work in computational and cognitive neuroscience depicts the brain as an ever‐active prediction machine: an inner engine continuously striving to anticipate the incoming sensory barrage. I briefly introduce this class of models before contrasting two ways of understanding the implied vision of mind. One way (Conservative Predictive Processing) depicts the predictive mind as an insulated inner arena populated by representations so rich and reconstructive as to enable the organism to ‘throw away the world’. The other (Radical Predictive Processing) stresses the use of fast and frugal, action‐involving solutions of the kind highlighted by much work in robotics and embodied cognition. But it goes further, by showing how predictive schemes can combine frugal and more knowledge‐intensive strategies, switching between them fluently and continuously as task and context dictate. I end by exploring some parallels with work in enactivism, and by noting a certain ambivalence concerning internal representations and their role in the predictive mind.

Biological brains are increasingly cast as ‘prediction machines’: evolved organs whose core operating principle is to learn about the world by trying to predict their own patterns of sensory stimulation. This, some argue, should lead us to embrace a brain-bound ‘neurocentric’ vision of the mind. The mind, such views suggest, consists entirely in the skull-bound activity of the predictive brain. In this paper I reject the inference from predictive brains to skull-bound minds. Predictive brains, I hope to show, can be apt participants in larger cognitive circuits. The path is thus cleared for a new synthesis in which predictive brains act as entry-points for ‘extended minds’, and embodiment and action contribute constitutively to knowing contact with the world.

Predictive processing accounts of neural function view the brain as a kind of prediction machine that forms models of its environment in order to anticipate the upcoming stream of sensory stimulation. These models are then continuously updated in light of incoming error signals. Predictive processing has offered a powerful new perspective on cognition, action, and perception. In this chapter we apply the insights from predictive processing to the study of emotions. The upshot is a picture of emotion as inseparable from perception and cognition, and a key feature of the embodied mind.