Not all models are explanatory. Some models are data summaries. Some models sketch explanations but leave crucial details unspecified or hidden behind filler terms. Some models are used to conjecture a how-possibly explanation without regard to whether it is a how-actually explanation. I use the Hodgkin and Huxley model of the action potential to illustrate these ways that models can be useful without explaining. I then use the subsequent development of the explanation of the action potential to show what is (...) required of an adequate mechanistic model. Mechanistic models are explanatory. (shrink)

The question ‘what is life?’ has long been a source of philosophical debate and in recent years has taken on increasing scientific importance. The most popular approach among both philosophers and scientists for answering this question is to provide a “definition” of life. In this article I explore a variety of different definitional approaches, both traditional and non-traditional, that have been used to “define” life. I argue that all of them are deeply flawed. It is my contention that a scientifically (...) compelling understanding of the nature of life presupposes an empirically adequate scientific theory (vs. definition) of life; as I argue, scientific theories are not the sort of thing that can be encapsulated in definitions. Unfortunately, as I also discuss, scientists are currently in no position to formulate even a tentative version of such a theory. Recent discoveries in biology and biochemistry have revealed that familiar Earth life represents a single example that may not be representative of life. If this is the case, life on Earth today provides an empirically inadequate foundation for theorizing about life considered generally. I sketch a strategy for procuring the needed additional examples of life without the guidance of a definition or theory of life, and close with an application to NASA’s fledgling search for extraterrestrial life. (shrink)

Where does the mind stop and the rest of the world begin? The question invites two standard replies. Some accept the demarcations of skin and skull, and say that what is outside the body is outside the mind. Others are impressed by arguments suggesting that the meaning of our words "just ain't in the head", and hold that this externalism about meaning carries over into an externalism about mind. We propose to pursue a third position. We advocate a very different (...) sort of externalism: an _active externalism_, based on the active role of the environment in driving cognitive processes. (shrink)

In the movie, Memento, the hero, Leonard, suffers from a form of anterograde amnesia that results in an inability to lay down new memories. Nonetheless, he sets out on a quest to find his wife’s killer, aided by the use of notes, annotated polaroids, and (for the most important pieces of information obtained) body tattoos. Using these resources he attempts to build up a stock of new beliefs and to thus piece together the puzzle of his wife’s death. At one (...) point in the movie, a character exasperated by Leonard’s lack of biological recall, shouts. (shrink)

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. (shrink)

In a recent paper, Kaplan (Synthese 183:339–373, 2011) takes up the task of extending Craver’s (Explaining the brain, 2007) mechanistic account of explanation in neuroscience to the new territory of computational neuroscience. He presents the model to mechanism mapping (3M) criterion as a condition for a model’s explanatory adequacy. This mechanistic approach is intended to replace earlier accounts which posited a level of computational analysis conceived as distinct and autonomous from underlying mechanistic details. In this paper I discuss work in (...) computational neuroscience that creates difficulties for the mechanist project. Carandini and Heeger (Nat Rev Neurosci 13:51–62, 2012) propose that many neural response properties can be understood in terms of canonical neural computations. These are “standard computational modules that apply the same fundamental operations in a variety of contexts.” Importantly, these computations can have numerous biophysical realisations, and so straightforward examination of the mechanisms underlying these computations carries little explanatory weight. Through a comparison between this modelling approach and minimal models in other branches of science, I argue that computational neuroscience frequently employs a distinct explanatory style, namely, efficient coding explanation. Such explanations cannot be assimilated into the mechanistic framework but do bear interesting similarities with evolutionary and optimality explanations elsewhere in biology. (shrink)

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

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

Artificial intelligence research has foundered on the issue of representation. When intelligence is approached in an incremental manner, with strict reliance on interfacing to the real world through perception and action, reliance on representation disappears. In this paper we outline our approach to incrementally building complete intelligent Creatures. The fundamental decomposition of the intelligent system is not into independent information processing units which must interface with each other via representations. Instead, the intelligent system is decomposed into independent and parallel activity (...) producers which all interface directly to the world through perception and action, rather than interface to each other particularly much. The notions of central and peripheral systems evaporateeverything is both central and peripheral. Based on these principles we have built a very successful series of mobile robots which operate without supervision as Creatures in standard office environments. (shrink)

Cognitive psychologists, like biologists, frequently describe mechanisms when explaining phenomena. Unlike biologists, who can often trace material transformations to identify operations, psychologists face a more daunting task in identifying operations that transform information. Behavior provides little guidance as to the nature of the operations involved. While not itself revealing the operations, identification of brain areas involved in psychological mechanisms can help constrain attempts to characterize the operations. In current memory research, evidence that the same brain areas are involved in what (...) are often taken to be different memory phenomena or in other cognitive phenomena is playing such a heuristic function. †To contact the author, please write to: Department of Philosophy, 0119, University of California, San Diego, La Jolla, CA 92093‐0119; e‐mail: [email protected]. (shrink)

The claim of the multiple realizability of mental states by brain states has been a major feature of the dominant philosophy of mind of the late 20th century. The claim is usually motivated by evidence that mental states are multiply realized, both within humans and between humans and other species. We challenge this contention by focusing on how neuroscientists differentiate brain areas. The fact that they rely centrally on psychological measures in mapping the brain and do so in a comparative (...) fashion undercuts the likelihood that, at least within organic life forms, we are likely to find cases of multiply realized psychological functions. (shrink)

Explanations in the life sciences frequently involve presenting a model of the mechanism taken to be responsible for a given phenomenon. Such explanations depart in numerous ways from nomological explanations commonly presented in philosophy of science. This paper focuses on three sorts of differences. First, scientists who develop mechanistic explanations are not limited to linguistic representations and logical inference; they frequently employ diagrams to characterize mechanisms and simulations to reason about them. Thus, the epistemic resources for presenting mechanistic explanations are (...) considerably richer than those suggested by a nomological framework. Second, the fact that mechanisms involve organized systems of component parts and operations provides direction to both the discovery and testing of mechanistic explanations. Finally, models of mechanisms are developed for specific exemplars and are not represented in terms of universally quantified statements. Generalization involves investigating both the similarity of new exemplars to those already studied and the variations between them. (shrink)

Should cognitive scientists be any more embarrassed about their lack of a discipline-fixing definition of cognition than biologists are about their inability to define “life”? My answer is “no”. Philosophers seeking a unique “mark of the cognitive” or less onerous but nevertheless categorical characterizations of cognition are working at a level of analysis upon which hangs nothing that either cognitive scientists or philosophers of cognitive science should care about. In contrast, I advocate a pluralistic stance towards uses of the term (...) ‘cognition’ that eschews the urge to treat cognition as a metaphysically well-defined “natural” kind. (shrink)

The present century has seen renewed interest in characterizing cognition, the object of inquiry of the cognitive sciences. In this paper, I describe the problem of cognition—the absence of a positive characterization of cognition despite a felt need for one. It is widely recognized that the problem is motivated by decades of controversy among cognitive scientists over foundational questions, such as whether non-neural parts of the body or environment can realize cognitive processes, or whether plants and microbes have cognitive processes. (...) The dominant strategy for addressing the problem of cognition is to seek a dichotomous criterion that vindicates some set of controversial claims. However, I argue that the problem of cognition is also motivated by ongoing conceptual development in cognitive science, and I describe four benefits that a characterization of cognition could confer. Given these benefits, I recommend an alternative criterion of success, ecumenical extensional adequacy, on which the aim is to describe the variation in expert judgments rather than to correct this variation by taking sides in sectarian disputes. I argue that if we had an ecumenical solution to the problem of cognition, we would have achieved much of what we should want from a “mark of the cognitive”. (shrink)

An important question in the debate over embodied, enactive, and extended cognition has been what has been meant by “cognition”. What is this cognition that is supposed to be embodied, enactive, or extended? Rather than undertake a frontal assault on this question, however, this paper will take a different approach. In particular, we may ask how cognition is supposed to be related to behavior. First, we could ask whether cognition is supposed to be behavior. Second, we could ask whether we (...) should attempt to understand cognitive processes in terms of antecedently understood cognitive behaviors. This paper will survey some of the answers that have been given in the embodied, enactive, and extended cognition literature, then suggest reasons to believe that we should answer both questions in the negative. (shrink)

It is easy to give a list of cognitive processes. They are things like learning, memory, concept formation, reasoning, maybe emotion, and so on. It is not easy to say, of these things that are called cognitive, what makes them so? Knowing the answer is one very important reason to be interested in the mark of the cognitive. In this paper, consider some answers that we think do not work and then offer one of our own which ties cognition to (...) actions explained via the having of reasons. (shrink)

An alarming number of philosophers and cognitive scientists have argued that mind extends beyond the brain and body. This book evaluates these arguments and suggests that, typically, it does not. A timely and relevant study that exposes the need to develop a more sophisticated theory of cognition, while pointing to a bold new direction in exploring the nature of cognition Articulates and defends the “mark of the cognitive”, a common sense theory used to distinguish between cognitive and non-cognitive processes Challenges (...) the current popularity of extended cognition theory through critical analysis and by pointing out fallacies and shortcoming in the literature Stimulates discussions that will advance debate about the nature of cognition in the cognitive sciences. (shrink)

According to F. Adams [this journal, vol. 68, 2018] cognition cannot be realized in plants or bacteria. In his view, plants and bacteria respond to the here-and-now in a hardwired, inflexible manner, and are therefore incapable of cognitive activity. This article takes issue with the pursuit of plant cognition from the perspective of an empirically informed philosophy of plant neurobiology. As we argue, empirical evidence shows, contra Adams, that plant behavior is in many ways analogous to animal behavior. This renders (...) plants suitable to be described as cognitive agents in a non-metaphorical way. Sections two to four review the arguments offered by Adams in light of scientific evidence on plant adaptive behavior, decision-making, anticipation, as well as learning and memory. Section five introduces the ‘phyto-nervous’ system of plants. To conclude, section six resituates the quest for plant cognition into a broader approach in cognitive science, as represented by enactive and ecological schools of thought. Overall, we aim to motivate the idea that plants may be considered genuine cognitive agents. Our hope is to help propel public awareness and discussion of plant intelligence once appropriately stripped of anthropocentric preconceptions of the sort that Adams' position appears to exemplify. (shrink)

What psychological and philosophical significance should we attach to recent efforts at computer simulations of human cognitive capacities? In answering this question, I find it useful to distinguish what I will call "strong" AI from "weak" or "cautious" AI. According to weak AI, the principal value of the computer in the study of the mind is that it gives us a very powerful tool. For example, it enables us to formulate and test hypotheses in a more rigorous and precise fashion. (...) But according to strong AI, the computer is not merely a tool in the study of the mind; rather, the appropriately programmed computer really is a mind, in the sense that computers given the right programs can be literally said to. (shrink)

In the beginning, there was the DN (Deductive Nomological) model of explanation, articulated by Hempel and Oppenheim (1948). According to DN, scientific explanation is subsumption under natural law. Individual events are explained by deducing them from laws together with initial conditions (or boundary conditions), and laws are explained by deriving them from other more fundamental laws, as, for example, the simple pendulum law is derived from Newton's laws of motion.

This paper attempts to elucidate three characteristics of causal relationships that are important in biological contexts. Stability has to do with whether a causal relationship continues to hold under changes in background conditions. Proportionality has to do with whether changes in the state of the cause “line up” in the right way with changes in the state of the effect and with whether the cause and effect are characterized in a way that contains irrelevant detail. Specificity is connected both to (...) David Lewis’ notion of “influence” and also with the extent to which a causal relation approximates to the ideal of one cause–one effect. Interrelations among these notions and their possible biological significance are also discussed. (shrink)

Mechanistic explanation has an impressive track record of advancing our understanding of complex, hierarchically organized physical systems, particularly biological and neural systems. But not every complex system can be understood mechanistically. Psychological capacities are often understood by providing cognitive models of the systems that underlie them. I argue that these models, while superficially similar to mechanistic models, in fact have a substantially more complex relation to the real underlying system. They are typically constructed using a range of techniques for abstracting (...) the functional properties of the system, which may not coincide with its mechanistic organization. I describe these techniques and show that despite being non-mechanistic, these cognitive models can satisfy the normative constraints on good explanations. (shrink)

According to the dominant computational approach in cognitive science, cognitive agents are digital computers; according to the alternative approach, they are dynamical systems. This target article attempts to articulate and support the dynamical hypothesis. The dynamical hypothesis has two major components: the nature hypothesis (cognitive agents are dynamical systems) and the knowledge hypothesis (cognitive agents can be understood dynamically). A wide range of objections to this hypothesis can be rebutted. The conclusion is that cognitive systems may well be dynamical systems, (...) and only sustained empirical research in cognitive science will determine the extent to which that is true. (shrink)

Recent extensions of mechanistic explanation into psychology suggest that cognitive models are only explanatory insofar as they map neatly onto, and serve as scaffolding for more detailed neural models. Filling in those neural details is what these accounts take the integration of cognitive psychology and neuroscience to mean, and they take this process to be seamless. Critics of this view have given up on cognitive models possibly explaining mechanistically in the course of arguing for cognitive models having explanatory value independent (...) of how well they align with neural mechanisms. We can have things both ways, however. The problem with seamless integration accounts is their seamlessness, not that they take cognitive models to be mechanistic. A non-componential view of mechanisms allows for cognitive and neural models that cross cut one another, and for cognitive models that don’t decompose into parts. I illustrate the inadequacy of seamless accounts of integration by contrasting how “filter” models of attention in psychology and of sodium channels in neuroscience developed; by questioning whether the mappings generated by neuroimaging subtraction studies achieve integration; and by reinterpreting the evidence for cognitive models of memory having been successfully integrated with neural models. I argue that the integrations we can realistically expect are more partial, patchy, and full of loose threads than the mosaic unity Craver describes. (shrink)

Andy Clark and David Chalmers claim that cognitive processes can and do extend outside the head.1 Call this the “hypothesis of extended cognition” (HEC). HEC has been strongly criticised by Fred Adams, Ken Aizawa and Robert Rupert.2 In this paper I argue for two claims. First, HEC is a harder target than Rupert, Adams and Aizawa have supposed. A widely-held view about the nature of the mind, functionalism—a view to which Rupert, Adams and Aizawa appear to subscribe— entails HEC. Either (...) HEC is true, or functionalism is false. The relationship between functionalism and HEC goes beyond support for the relatively uncontroversial claim that it is logically or nomologically possible for cognition to extend (the “can” part of HEC); functionalism entails that cognitive processes do extend in the actual world. Second, I argue that the version of HEC entailed by functionalism is more radical than the version that Clark and Chalmers suggest. I argue that it is so radical as to form a counterexample to functionalism. If functionalism is modified to prevent these consequences, then HEC falls victim to Rupert, Adams and Aizawa’s original criticism. An advocate of HEC has two choices: (1) accept functionalism and radical HEC; (2) give up HEC entirely. Clark and Chalmers’ intermediate position of a modest form of HEC is unsustainable. The argument of this paper, although initially appearing to support Clark and Chalmers, ultimately argues against their position. The price of HEC is rampant expansion of the mind into the world, and the implausibility of such expansion is indicative of deep-seated problems with functionalism. The argument of this paper consequently speaks to wider issues than just the status of HEC. The reasons for.. (shrink)

Several articles have recently appeared arguing that there really are no viable alternatives to mechanistic explanation in the biological sciences (Kaplan and Bechtel; Kaplan and Craver). We argue that mechanistic explanation is defined by localization and decomposition. We argue further that systems neuroscience contains explanations that violate both localization and decomposition. We conclude that the mechanistic model of explanation needs to either stretch to now include explanations wherein localization or decomposition fail or acknowledge that there are counterexamples to mechanistic explanation (...) in the biological sciences. (shrink)

Many who advocate dynamical systems approaches to cognitive science believe themselves committed to the thesis of extended cognition and to the rejection of representation. I argue that this belief is false. In part, this misapprehension rests on a warrantless re-conception of cognition as intelligent behavior. In part also, it rests on thinking that conceptual issues can be resolved empirically. Once these issues are sorted out, the way is cleared for a dynamical systems approach to cognition that is free to retain (...) the standard conception of cognition as taking place in the head, and over representations. (shrink)

According to the thesis of the extended mind (EM) , at least some token cognitive processes extend into the cognizing subject's environment in the sense that they are (partly) composed of manipulative, exploitative, and transformative operations performed by that subject on suitable environmental structures. EM has attracted four ostensibly distinct types of objection. This paper has two goals. First, it argues that these objections all reduce to one basic sort: all the objections can be resolved by the provision of an (...) adequate and properly motivated criterion—or mark—of the cognitive. Second, it provides such a criterion—one made up of four conditions that are sufficient for a process to count as cognitive. (shrink)

Kaplan and Craver claim that all explanations in neuroscience appeal to mechanisms. They extend this view to the use of mathematical models in neuroscience and propose a constraint such models must meet in order to be explanatory. I analyze a mathematical model used to provide explanations in dynamical systems neuroscience and indicate how this explanation cannot be accommodated by the mechanist framework. I argue that this explanation is well characterized by Batterman’s account of minimal model explanations and that it demonstrates (...) how relationships between explanatory models in neuroscience and the systems they represent is more complex than has been appreciated. (shrink)

In various contexts and for various reasons, writers often define cognitive processes and architectures as those involving representational states and structures. Similarly, cognitive theories are also often delineated as those that invoke representations. In this paper, I present several reasons for rejecting this way of demarcating the cognitive. Some of the reasons against defining cognition in representational terms are that doing so needlessly restricts our theorizing, it undermines the empirical status of the representational theory of mind, and it encourages wildly (...) deflationary and explanatorily vacuous conceptions of representation. After criticizing this outlook, I sketch alternative ways we might try to capture what is distinctive about cognition and cognitive theorizing. (shrink)

In 1967, American biologist Adrian Wenner (1928-) launched an extensive challenge to Karl von Frisch's (1886-1982) theory that bees communicate to each other the direction and distance of food sources by a symbolic dance language. Wenner and various collaborators argued that bees locate foods solely by odors. Although the dispute had largely run its course by 1973 -- von Frisch was awarded a Nobel Prize, while Wenner withdrew from active bee research -- it offers us a rare window into mid-twentieth (...) century discussions about animals, language, and cognition. Historians, sociologists, and scientists have commented on the debate and its outcome, but none has seriously questioned why von Frisch and Wenner pursued such different explanations of the bees' dances. In this paper, I explore von Frisch and Wenner's differing visions of animals and their behaviors and show how these contributed to their respective positions. Von Frisch's early-twentieth-century training in experimental physiology disposed him to focus on individual animals, their abilities, and their behaviors' evolutionary significance. Wenner, by contrast, was trained in mathematics and statistics and the Schneirla school of behavior. He viewed the bees' behaviors probabilistically with an eye toward the entire hive and its surroundings and ultimately explained them in terms of simple stimulus--response conditioning. Finally, while the debate was resolved in von Frisch's favor, he neither waged nor won the battle by himself. Instead, I show that practitioners, whose agendas ranged from the nascent fields of sociobiology to cognitive ethology, took up the cause of the communicating bees. (shrink)

In several disciplines within science—evolutionary biology, molecular biology, astrobiology, synthetic biology, artificial life—and outside science—primarily ethics—efforts to define life have recently multiplied. However, no consensus has emerged. In this article, I argue that this is no accident. I propose a dilemma showing that the project of defining life is either impossible or pointless. The notion of life at stake in this project is either the folk concept of life or a scientific concept. In the former case, empirical evidence shows that (...) life cannot be defined. In the latter case, I argue that, although defining life may be possible, it is pointless. I conclude that scientists, philosophers, and ethicists should discard the project of defining life. (shrink)

The concept of mechanism is analyzed in terms of entities and activities, organized such that they are productive of regular changes. Examples show how mechanisms work in neurobiology and molecular biology. Thinking in terms of mechanisms provides a new framework for addressing many traditional philosophical issues: causality, laws, explanation, reduction, and scientific change.

In this paper, I argue that looking at the concept of neural function through the lens of cognition alone risks cognitive myopia: it leads neuroscientists to focus only on mechanisms with cognitive functions that process behaviorally relevant information when conceptualizing “neural function”. Cognitive myopia tempts researchers to neglect neural mechanisms with noncognitive functions which do not process behaviorally relevant information but maintain and repair neural and other systems of the body. Cognitive myopia similarly affects philosophy of neuroscience because scholars overlook (...) noncognitive functions when analyzing issues surrounding e.g., functional decomposition or the multifunctionality of neural structures. I argue that we can overcome cognitive myopia by adopting a patchwork approach that articulates cognitive and noncognitive “patches” of the concept of neural function. Cognitive patches describe mechanisms with causally specific effects on cognition and behavior which are likely operative in transforming sensory or other inputs into motor outputs. Noncognitive patches describe mechanisms that lack such specific effects; these mechanisms are enabling conditions for cognitive functions to occur. I use these distinctions to characterize two noncognitive functions at the mesoscale of neural circuits: subsistence functions like breathing are implemented by central pattern generators and are necessary to maintain the life of the organism. Infrastructural functions like gain control are implemented by canonical microcircuits and prevent neural system damage while cognitive processing occurs. By adding conceptual patches that describe these functions, a patchwork approach can overcome cognitive myopia and help us explain how the brain’s capacities as an information processing device are constrained by its ability to maintain and repair itself as a physiological apparatus. (shrink)

A critique of the hypothesis of extended cognition.