Andy Clark

How should we characterize the functional role of conscious visual experience? In particular, how do the conscious contents of visual experience guide, bear upon, or otherwise inform our ongoing motor activities? According to an intuitive and philosophically influential conception, the links are often quite direct. The contents of conscious visual experience, according to this conception, are typically active in the control and guidance of our fine-tuned, real-time engagements with the surrounding three-dimensional world. But this idea is hostage to empirical fortune. It is a hostage, moreover, whose safety is in serious doubt. Thus Milner and Goodale argue for a deep and abiding dissociation between the contents of conscious seeing, on the one hand, and the resources used for the on-line guidance of visuo-motor action, on the other. This ‘dual visual systems’ hypothesis, which finds many echoes in various other bodies of cognitive scientific research, poses a prima facie challenge to the Assumption of Experience-Based Control. More importantly, it provides fuel for an alternative and philosophically suggestive account of the functional role of conscious visual experience.

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. 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.

Mind, it has recently been argued1, is a thoroughly temporal phenomenon: so temporal, indeed, as to defy description and analysis using the traditional computational tools of cognitive scientific understanding. The proper explanatory tools, so the suggestion goes, are instead the geometric constructs and differential equations of Dynamical Systems Theory. I consider various aspects of the putative temporal challenge to computational understanding, and show that the root problem turns on the presence of a certain kind of causal web: a web that involves multiple components (both inner and outer) linked by chains of continuous and reciprocal causal influence. There is, however, no compelling route from such facts about causal and temporal complexity to the radical anti- computationalist conclusion. This is because, interactive complexities notwithstanding, the computational approach provides a kind of explanatory understanding that cannot (I suggest) be recreated using the alternative resources of pure Dynamical Systems Theory. In particular, it provides a means of mapping information flow onto causal structure -- a mapping that is crucial to understanding the distinctive kinds of flexibility and control characteristic of truly mindful engagements with the world. Where we confront especially complex interactive causal webs, however, it does indeed become harder to isolate the syntactic vehicles required by the computational approach. Dynamical Systems Theory, I conclude, may play a vital role in recovering such vehicles from the burgeoning mass of real-time interactive complexity

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.

Advanced biological brains are by nature open-ended opportunistic controllers. Such controllers compute, pretty much on a moment-to-moment basis, what problem-solving resources are readily available and recruit them into temporary problem-solving wholes. Neural plasticity, exaggerated in our own species, makes it possible for such resources to become factored deep into both our cognitive and physical problem-solving routines. One way to think about this is to depict the biological brain as a master of what I shall dub ‘ecological control’. Ecological control is the kind of top-level control that does not micro-manage every detail, but rather encourages substantial devolvement of power and responsibility. This kind of control allows much of our skill at walking to reside in the linkages and elastic properties of muscles and tendons. And it allows much of our prowess at thought and reason to depend upon the robust and reliable operation, often in dense brain-involving loops, of a variety of non-biological problem-solving resources spread throughout our social and technological surround. Are the complex distributed systems that result in some sense ‘out of control’, beyond the reach of useful governance? I shall argue that they are not, although understanding them requires us to re-think some key ideas about control and the nature of the self. To make this case, I shall first examine some strategies for efficient, external opportunity exploiting control in simple systems. I shall then argue that many of the same lessons apply to the case of higher-level human problem-solving.

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.

Advanced biological brains are by nature open-ended opportunistic controllers. Such controllers compute, pretty much on a moment-to-moment basis, what problem-solving resources are readily available and recruit them into temporary problem-solving wholes. Neural plasticity, exaggerated in our own species, makes it possible for such resources to become factored deep into both our cognitive and physical problem-solving routines. One way to think about this is to depict the biological brain as a master of what I shall dub ‘ecological control’. Ecological control is the kind of top-level control that does not micro-manage every detail, but rather encourages substantial devolvement of power and responsibility. This kind of control allows much of our skill at walking to reside in the linkages and elastic properties of muscles and tendons. And it allows much of our prowess at thought and reason to depend upon the robust and reliable operation, often in dense brain-involving loops, of a variety of non-biological problem-solving resources spread throughout our social and technological surround. Are the complex distributed systems that result in some sense ‘out of control’, beyond the reach of useful governance? I shall argue that they are not, although understanding them requires us to re-think some key ideas about control and the nature of the self. To make this case, I shall first examine some strategies for efficient, external opportunity exploiting control in simple systems. I shall then argue that many of the same lessons apply to the case of higher-level human problem-solving.

How does language (spoken or written) impact thought? One useful way to approach this important but elusive question may be to consider language itself as a cognition-enhancing animal-built structure. To take this perspective is to view language as a kind of self-constructed cognitive niche. These self-constructed cognitive niches play, I suggest, three distinct but deeply interlocking roles in human thought and reason. Working together, these three interlocking routines radically transform the human mind, and mark a genuine discontinuity in the space of anitnal minds

Of course, words aren’t magic. Neither are sextants, compasses, maps, slide rules and all the other paraphenelia which have accreted around the basic biological brains of homo sapiens. In the case of these other tools and props, however, it is transparently clear that they function so as to either carry out or to facilitate computational operations important to various human projects. The slide rule transforms complex mathematical problems (ones that would baffle or tax the unaided subject) into simple tasks of perceptual recognition. The map provides geographical information in a format well-suited to aid complex planning and strategic military operations. The compass gathers and displays a kind of information that (most) unaided human subjects do not seem to command. These various tools and props thus act to generate information, or to store it, or to transform it, or some combination of the three. In so doing, they impact our individual and collective problem- solving capacities in much the same dramatic ways as various software packages impact the performance of a simple pc.

There is a school of thought which links connectionist models of cognition to eliminativism-the thesis that the constructs of commonsense psychology do not exist. This way of construing the impact of connectionist modelling is, I argue, deeply mistaken and depends crucially on a shallow analysis of the notion of explanation. I argue that good, higher level descriptions may group together physically heterogenous mechanisms, and that the constructs of folk psychology may fulfil such a grouping function even if they fail to pick out discrete states of individual processing. More speculatively, the paper goes on to suggest that the virtues which recommend such constructs from a theorist’s third person perspective may nonetheless have close analogues in individual processing. Various difficulties for what I term a pure distributed connectionism may be solved by systems which utilise both distributed and classical symbolic representations-the latter exhibiting the discreteness and semantic interpretability which the eliminativist requires to vindicate common-sense psychology. If human beings turned out to be such mixed systems, then the eliminativist claim would be doubly misguided. It would be false as a conditional since even if pure distributed connectionism were a complete and accurate formal model of individual processing, it would not follow that the other, higher level constructs were not accurate and essential tools for a different kind of explanation. And it would involve a false antecedent since in a mixed system the symbolic descriptions may indeed be incarnate in the system’s own individual processing. The paper is in four main sections. Section 1 attempts to systematise a certain received picture of the relative status and accuracy of various levels of description of a connectionist system. Section 2 then introduces a general model of explanations which aim to group systems into equivalence classes defined for various purposes. Each grouping requires a special vocabulary and the constructs of any given vocabulary are legitimate just insofar as the grouping is interesting and useful. Section 3 goes on to show that, relative to such a model of explanation, the constructs of both symbolic AI and commonsense psychology may have a legitimate role to play in giving psychological explanations. This role is not just that of a useful approximation. The paper ends with a speculative section in which the argument for the theoretical usefulness of such symbolic constructs is extended, in a very natural way, to the domain of individual processing. Here the cognizer, in the process of regulating, debugging and understanding her own representations, creates symbols to stand for sets of distributed activity patterns. The section points out some difficulties for a pure distributed approach which may be eased by the addition of such symbolic constructs and relates the speculations to the current debate over the ’correct’architecture of cognition. If the speculations are on target, this whole debate turns out to be fundamentally illposed.