Andy Clark

Markets, companies and various forms of business organizations may all (we have argued) be usefully viewed through the lens of CAS -- the theory of complex adaptive systems. In this chapter, I address one fundamental issue that confronts both the theoretician and the business manager: the nature and opportunities for control and intervention in complex adaptive regimes. The problem is obvious enough. A complex adaptive system, as we have defined it, is soft assembled and largely self-organizing. This means that it is the emergent product of multiple, and often very heterogeneous, interacting factors and forces, and that the crucial interactions are not controlled and orchestrated by an overseeing executive, detailed program, or any other source of strict hierarchical control. There is thus a pressing problem -- are such systems strictly out of control and beyond the reach of useful governance? I shall argue that they are not. Such systems, though initially unfamiliar, can nonetheless be led, influenced and enabled in a variety of ways.

Like those famous nations divided by a single tongue, my paper (this volume) and Professor P.M. Churchland's deep and engaging reply offer different spins on a common heritage. The common heritage is, of course, a connectionist vision of the inner neural economy- a vision which depicts that economy in terms of supra-sentential state spaces, vector-to-vector transformations, and the kinds of skillful pattern-recognition routine we share with the bulk of terrestrial intelligent life-forms. That which divides us is, as ever, much harder to isolate and name. Clearly, it has something to do with the role of moral talk and exchange, and something to do with the conception of morality itself (and, correlatively, with the conception of moral progress). Most of this Reply will be devoted to clarifying the nature of the disputed territory. First, though (as a prophylactic against misunderstanding) I shall rehearse some points of agreement concerning moral talk and progress.

The meta-problem of consciousness (Chalmers, 2018) is the problem of explaining the behaviours and verbal reports that we associate with the so-called 'hard problem of consciousness'. These may include reports of puzzlement, of the attractiveness of dualism, of explanatory gaps, and the like. We present and defend a solution to the meta-problem. Our solution takes as its starting point the emerging picture of the brain as a hierarchical inference engine. We show why such a device, operating under familiar forms of adaptive pressure, may come to represent some of its mid-level inferences as especially certain. These mid-level states confidently re-code raw sensory stimulation in ways that (they are able to realize) fall short of fully determining how properties and states of affairs are arranged in the distal world. This drives a wedge between experience and the world. Advanced agents then represent these mid-level inferences as irreducibly special, becoming increasingly puzzled as a result.

How do questions concerning consciousness and phenomenal experience relate to, or interface with, questions concerning plans, knowledge and intentions? At least in the case of visual experience the relation, we shall argue, is tight. Visual perceptual experience, we shall argue, is fixed by an agent’s direct unmediated knowledge concerning her poise (or apparent poise) over a currently enabled action space. An action space, in this specific sense, is to be understood not as a fine-grained matrix of possibilities for bodily movement, but as a matrix of possibilities for pursuing and accomplishing one’s intentional actions, goals and projects. If this is correct, the links between planning, intention and perceptual experience are tight, while (contrary to some recent accounts invoking the notion of ‘sensorimotor expectations’) the links between embodied activity and perceptual experience, though real, are indirect. What matters is not bodily activity itself, but our practical knowledge (which need not be verbalized or in any way explicit) of our own possibilities for action. Such knowledge, selected, shaped and filtered by the grid of plans, goals, and intentions, plays, we argue, a constitutive role in explaining the content and character of visual perceptual experience.

Summarizes and illuminates two decades of research Gathering important papers by both philosophers and scientists, this collection illuminates the central themes that have arisen during the last two decades of work on the conceptual foundations of artificial intelligence and cognitive science. Each volume begins with a comprehensive introduction that places the coverage in a broader perspective and links it with material in the companion volumes. The collection is of interest in many disciplines including computer science, linguistics, biology, information science, psychology, neuroscience, iconography, and philosophy. Examines initial efforts and the latest controversies The topics covered range from the bedrock assumptions of the computational approach to understanding the mind, to the more recent debates concerning cognitive architectures, all the way to the latest developments in robotics, artificial life, and dynamical systems theory. The collection first examines the lineageof major research programs, beginning with the basic idea of machine intelligence itself, then focuses on specific aspects of thought and intelligence, highlighting the much-discussed issue of consciousness, the equally important, but less densely researched issue of emotional response, and the more traditionally philosophical topic of language and meaning. Provides a gamut of perspectives The editors have included several articles that challenge crucial elements of the familiar research program of cognitive science, as well as important writings whose previous circulation has been limited. Within each volume the papers are organized to reflect a variety of research programs and issues. The substantive introductions that accompany each volume further organize the material and provide readers with a working sense of the issues and the connection between articles.

This is the first of two volumes of essays in commemoration of Alan Turing, whose pioneering work in the theory of artificial intelligence and computer science continues to be widely discussed today. A group of prominent academics from a wide range of disciplines focus on three questions famously raised by Turing: What, if any, are the limits on machine `thinking'? Could a machine be genuinely intelligent? Might we ourselves be biological machines, whose thought consists essentially in nothing more than the interaction of neurons according to strictly determined rules? The discussion of these fascinating issues is accessible to non-specialists and stimulating for all readers.

Recent work in cognitive and computational neuroscience depicts the human cortex as a multi-level prediction engine. This ‘predictive processing’ framework shows great promise as a means of both understanding and integrating the core information processing strategies underlying perception, reasoning, and action. But how, if at all, do emotions and sub-cortical contributions fit into this emerging picture? The fit, we shall argue, is both profound and potentially transformative. In the picture we develop, online cognitive function cannot be assigned to either the cortical or the sub-cortical component, but instead emerges from their tight co-ordination. This tight co-ordination involves processes of continuous reciprocal causation that weave together bodily information and ‘top-down’ predictions, generating a unified sense of what’s out there and why it matters. The upshot is a more truly ‘embodied’ vision of the predictive brain in action.

Sensory substitution devices are a type of sensory prosthesis that (typically) convert visual stimuli transduced by a camera into tactile or auditory stimulation. They are designed to be used by people with impaired vision so that they can recover some of the functions normally subserved by vision. In this chapter we will consider what philosophers might learn about the nature of the senses from the neuroscience of sensory substitution. We will show how sensory substitution devices work by exploiting the cross-modal plasticity of sensory cortex: the ability of sensory cortex to pick up some types of information about the external environment irrespective of the nature of the sensory inputs it is processing. We explore the implications of cross-modal plasticity for theories of the senses that attempt to make distinctions between the senses on the basis of neurobiology.

After offering a brief account of how we understand the shared circuits model (SCM), we divide our response into four sections. First, in section R1, we assess to what extent SCM is committed to an account of the ontogeny and phylogeny of shared circuits. In section R2, we examine doubts raised by several commentators as to whether SCM might be expanded so as to accommodate the mirroring of emotions, sensations, and intransitive actions more generally. Section R3 responds to various criticisms that relate to the account of social-learning Hurley proposes in the target article. We conclude in section R4 by responding to a number of commentators who argued for the limitation of control theory as a framework for studying social cognition

How to build a theory in cognitive science. Valerie Gray Hardcastle. Albany: State University of New York. Press, 1996Language, thought, and consciousness. Peter Carruthers. Cambridge: Cambridge University. Press, 1996. ISBN 0–521–48158–9 (hc)Young children's knowledge about thinking. John H. Flavell, Frances L. Green & Eleanor R. Flavell with Commentary by Paul L. Harris & Janet Wilde Astington. Monographs of the Society for Research in Child Development, 1995, 60 (1, Serial No, 243) Chicago: The University of Chicago PressValuing emotions. Michael Stocker with Elizabeth Hegeman. Cambridge: Cambridge University Press, 1996Explaining attitudes: a practical approach to the mind. Lynne Rudder Baker. Cambridge: Cambridge University Press, 1995. ISBN 0–521–42053–9 $59.95The prehistory of the mind: a search for the origins of art, religion and science. Steven Mithen. London: Thames and Hudson, 1996The discovery of spoken language Peter Jusczyk. Cambridge, MA: MIT Press/Bradford Books, 1997. ISBN 0–262–10058–4 $32.50Noam Chomsky: a life of dissent. Robert F. Barksky Cambridge, MA: MIT Press ISBN 0–262–02418–7 $27.50.

The key question in this three way debate is the role of the collectivity and of agency. Collins and Shrager debate whether cognitive psychology has, like the sociology of knowledge, always taken the mind to extend beyond the individual. They agree that irrespective of the history, socialization is key to understanding the mind and that this is compatible with Clark’s position; the novelty in Clark’s “extended mind” position appears to be the role of the material rather than the role of other minds. Collins and Clark debate the relationship between self, agency, and the human collectivity. Collins argues that the Clark’s extended mind fails to stress the asymmetry of the relationship between the self and its material “scaffolding.” Clark accepts that there is asymmetry but that an asymmetrical ensemble is sufficient to explain the self. Collins says that we know too little about the material world to pursue such a model to the exclusion of other approaches including that both the collectivity and language have agency. The collectivity must be kept in mind! (Though what follows is a robust exchange of views it is also a cooperative effort, authors communicating “backstage” with each other to try to make the disagreements as clear and to the point as possible.).

What is the role of conscious visual experience in the control and guidance of human behaviour? According to some recent treatments, the role is surprisingly indirect. Conscious visual experience, on these accounts, serves the formation of plans and the selection of action types and targets, while the control of 'online' visually guided action proceeds via a quasi-independent non-conscious route. In response to such claims, critics such as (Wallhagen [2007], pp. 539-61) have suggested that the notions of control and guidance invoked are unacceptably vague, and that that the image of 'zombie systems' guiding action fails to take account of the possibility that there is genuine but unconceptualized, unnoticed, and/or unreportable experience taking place and guiding or controlling the actions. I address both sets of concerns. I try to show that refining and clarifying the key notions of control and guidance leaves the original argument intact, as does the appeal to unconceptualized, unnoticed, or unreportable experiences. The exercise serves, however, to highlight an important complex of considerations concerning the relations between control, agency, and experience. Better understanding these relations is, I suggest, an important source of insights concerning the nature of phenomenal experience

  Recent work in biology and cognitive science depicts a variety of target phenomena as the products of a tangled web of causal influences. Such influences may include both internal and external factors as well as complex patterns of reciprocal causal interaction. Such twisted tales are sometimes seen as a threat to explanatory strategies that invoke notions such as inner programs, genes for and sometimes even internal representations. But the threat, I shall argue, is more apparent than real. Complex causal influence, in and of itself, provides no good reason to reject these familiar explanatory notions. To believe otherwise, I suggest, is generally to commit (at least) one of two seductive errors. The first error is to think that the general notion of a state x coding for an outcome y involves the state's constituting a full description of y. This is what I call the myth of the self-contained code. The second error is to think that the practice of treating certain factors as special (e.g., seeing genes as coding for outcomes in a way environmental factors do not) depends on the (often mistaken) belief that the singled out factor is somehow doing the most real work. Where the amounts of causal influence are evenly spread, it is assumed there can be no reason to treat one factor in a special way. This is what I term the Myth of Explanatory Equality. Avoiding these errors involves reminding ourselves of (1) the rich context-dependence of even standard, unproblematic uses of the notions of code, program and information content (all three make sense only relative to an assumed ecological backdrop) and (2) the difference between explaining why an event occurred and displaying the full workings of a complex causal system

Some regularities enjoy only an attenuated existence in a body of training data. These are regularities whose statistical visibility depends on some systematic recoding of the data. The space of possible recodings is, however, infinitely large type-2 problems. they are standardly solved! This presents a puzzle. How, given the statistical intractability of these type-2 cases, does nature turn the trick? One answer, which we do not pursue, is to suppose that evolution gifts us with exactly the right set of recoding biases so as to reduce specific type-2 problems to (tractable) type-1 mappings. Such a heavy-duty nativism is no doubt sometimes plausible. But we believe there are other, more general mechanisms also at work. Such mechanisms provide general (not task-specific) strategies for managing problems of type-2 complexity. Several such mechanisms are investigated. At the heart of each is a fundamental ploy representational redescription language and culture – may themselves be viewed as adaptations enabling this representation/computation trade-off to be pursued on an even grander scale

Some regularities enjoy only an attenuated existence in a body of training data. These are regularities whose statistical visibility depends on some systematic recoding of the data. The space of possible recodings is, however, infinitely large – it is the space of applicable Turing machines. As a result, mappings that pivot on such attenuated regularities cannot, in general, be found by brute-force search. The class of problems that present such mappings we call the class of “type-2 problems.” Type-1 problems, by contrast, present tractable problems of search insofar as the relevant regularities can be found by sampling the input data as originally coded. Type-2 problems, we suggest, present neither rare nor pathological cases. They are rife in biologically realistic settings and in domains ranging from simple animat behaviors to language acquisition. Not only are such problems rife – they are standardly solved! This presents a puzzle. How, given the statistical intractability of these type-2 cases, does nature turn the trick? One answer, which we do not pursue, is to suppose that evolution gifts us with exactly the right set of recoding biases so as to reduce specific type-2 problems to type-1 mappings. Such a heavy-duty nativism is no doubt sometimes plausible. But we believe there are other, more general mechanisms also at work. Such mechanisms provide general strategies for managing problems of type-2 complexity. Several such mechanisms are investigated. At the heart of each is a fundamental ploy – namely, the maximal exploitation of states of representation already achieved by prior, simpler learning so as to reduce the amount of subsequent computational search. Such exploitation both characterizes and helps make unitary sense of a diverse range of mechanisms. These include simple incremental learning, modular connectionism, and the developmental hypothesis of “representational redescription”. In addition, the most distinctive features of human cognition – language and culture – may themselves be viewed as adaptations enabling this representation/computation trade-off to be pursued on an even grander scale.

Abstract Cognitive Science, it is argued, comprises two distinct projects. One is an Engineering project whose goal is understanding the in?the?head computational activities which ground intelligent behaviour. The other is a Descriptive project whose goal is the mapping of relations between thoughts as ascribed using the (sentential) apparatus of the propositional attitudes. Some theorists (e.g. Fodor, 1987) insist that the two projects are (in a sense to be explained) deeply related. This view is contested, and the consequences of its abandonment examined. Such consequences are seen to include (i) the irrelevance of scientific arguments for Eliminative Materialism, (ii) a view concerning the proper roles of classical and connectionist work in Artificial Intelligence and (iii) the failure of an allegedly damning argument against connectionism (the so?called systematicity argument)