A Philosophical Critique of Classical Cognitivism in Sport: From Information Processing to Bodily Background Knowledge

Transcription

1 ARTICLES Journal of the Philosophy of Sport, 2005, 32, Human Kinetics, Inc. A Philosophical Critique of Classical Cognitivism in Sport: From Information Processing to Bodily Background Knowledge Vegard Fusche Moe How can we understand intentional movements that make up sport? This is a core problem for sport research, and, over the years, several distinct answers have emerged. One of the most popular approaches to the problem for the last 30 years or so comes from an information-processing theory based on a computer model of the mind. This computer-inspired approach, that is, classical cognitivism (e.g., 7) or simply cognitivism (20), implies strong analogy between how computers and human intelligence work. The computer is a device that computes or processes information according to certain program or rule structures. The human mind, on this view, operates similarly. The computer model of the mind has been widely adopted for sport research at conceptual, empirical, and practical levels, and it has led to a reliance on notions such as information processing, motor programs, representations, traces, schemas, and the like. 1 Recently, however, classical cognitivism has been attacked from a variety of different perspectives. Strong critiques have emerged from philosophy, ecological psychology, and the dynamical-systems perspective. In particular, during the last decade or so the debate between a cognitive computer-inspired approach on the one hand and an ecological/dynamical approach on the other has been rich and lively in human movement science generally and sport psychology specifically. Both strengths and weaknesses of these two approaches have been thoroughly accounted for elsewhere (e.g., 1; 51; 53; 54). Although this debate is important, I do not take it up in this article. In this article I do, however, take a closer look at the critique of classical cognitivism that has come from the philosophical perspective. In particular, I examine the counterarguments that have been raised against the computer model of the mind from two renowned critics, Hubert Dreyfus and John Searle. Their critiques have barely, to my knowledge, been addressed in the sport literature before. Dreyfus and Searle have, from distinct philosophical perspectives, developed original arguments against classical cognitivism, and their critiques have been at the forefront in cognitive science for the last 30 years or so, something that has been emphasized by Clark: The author <vegard.fusche.moe@nih.no> is with the Norwegian School of Sport Sciences, PB 4014 Ullevaal Stadion 0806 Oslo, Norway. 155

2 156 Moe Classical cognitivism was not universally celebrated by philosophers. There was a slightly inchoate sense of mind being finessed by sleight of hand. With the work of Dreyfus... and later Searle..., the inchoate became flesh. (7: p. 25) In this article I use Dreyfus s and Searle s critical objections to classical cognitivism to show how and why it produces an incomplete or erroneous understanding of intentional movements in sport. My goal is not to provide a comprehensive defense of Dreyfus and Searle. It is, rather, to explore some interesting implications that their theories have for the way we understand intentional movements in sport. I have divided the article into three parts. In the first part, I review how classical cognitivism in sport emerged, what its basic assumptions are, what kinds of conceptual tools it has provided for sport research, and how the conceptual tools can be applied in the practical world of a coach to explain intentional movements in sport. The first part paints a powerful picture of cognitivism in sport. Generally speaking, it seems to provide an in-principle explanation of intentional movements in sport. In the second part of the article, I review the main arguments against classical cognitivism developed by Dreyfus and Searle. Contrary to the computer model of the mind, both Dreyfus and Searle focus more on the differences between the computer and the human than on their similarities. Dreyfus believes that cognitivism s manner of formalizing knowledge cannot grasp the richness and diversity of how human beings experience and cannot account for their practical and embodied coping with their surroundings. Searle, on the other hand, thinks that the formalistic aspects of cognitivism are unable to make sense of the concrete biological workings of the mind brain relationship. Because the philosophies of Dreyfus and Searle come from two different philosophical perspectives phenomenological and analytical ones, respectively their critiques of classical cognitivism, when combined, provide a strong attack on the information-processing approach, one that may (if it is found convincing) significantly reduce its attractiveness. This is the negative outcome of the article. On the positive side, both Dreyfus and Searle give us alternative approaches for understanding intentional movements in sport. In the third part of the article, I close with some optimistic remarks in this direction. What Is Classical Cognitivism in Sport? According to Gardner s history of the cognitive revolution, one might say that cognitive science has a very long past but a relatively short history (17: p. 9). Gardner traced the long tradition of cognitive science back to ancient times. The short history, on the other hand, goes only back to the second half of the preceding century. It was only then that cognitive science emerged as a recognized pursuit (17: p. 9). In the beginning of cognitive science, classical cognitivism was central. 2 Many factors influenced the emergence of classical cognitivism. According to its short history, two central elements deserve special attention. First of all, around World War II, major advances in the scientific and technological milieus were made, gains that were particularly evident in the fields of mathematics and computation, neuroscience, cybernetics, and information theory. Together with the development of the computer, these achievements provided the foundation for a new cognitive

3 A Critique of Cognitivism in Sport 157 paradigm (cf. 17: pp. 16ff.). Second, there was a strong dissatisfaction with the psychological research after World War II. Behaviorism, which attempted to turn psychology into a strictly defined science by means of its clear methodology and the measurement of behavior that was overtly observational, placed undue significance on stimuli (input) and responses (output) while simultaneously ignoring what was going on between these two stages. This strategy left a void a so-called black box between stimulus and response. Gradually it became clear that the simple stimulus response language of behaviorism was insufficient to grasp the real nature of the mind (cf. 18: pp ). Obviously, significant things transpired in the mind that behaviorism left out. As Ulric Neisser, the founding father of cognitive psychology, remarked, the basic reason for studying cognitive processes has become clear as the reason for studying anything else: because they are there. Our knowledge of the world must be somehow developed from the stimulus input (as quoted in 18: p. 16). It was the growing discontent with behaviorism in psychology that, together with scientific and technological inventions, made it possible for the cognitive paradigm to emerge and blossom in the second half of the 20th century. Quite simply, one needed an alternative to behaviorism that took the black box (the void between input and output) seriously. The Computer Analogy, Information Processing, and Mental Representation It is first and foremost through the computer analogy or the computer model of the mind that classical cognitivism revolutionized our understanding of the internal states of the mind. In short, it used computer imagery to fill in the void between input and output. If we look at computation from an etymological perspective, we will see that the word computer comes from the Latin word computare which means to calculate or reckon together (29: p. 129). What does the computer calculate? The most direct answer to this question is that a computer calculates, computes, or processes information (e.g., 35). The view that the computer is an information-processing device has a wide following. Processing can be broken into at least three different subheadings, including syntactic or quantitative versions, semantic versions, and historical or sociotechnical readings such as the notion that the information society exemplifies (49: p. 154). Generally speaking, the computer is a device that processes information according to hardware and software structures. The software structure namely, the programs is realized in the hardware of the computer. The computer, to put things simply, receives information from the environment, processes the incoming information according to one or more programs, and produces a certain output, as, for example, the written words on this page. To make the computer analogy even more explicit we can express it in a slogan. The mind is to the brain as the program is to the hardware (42: p. 200). The mind, in other words, is the program and the brain the hardware of a computational system (my emphasis, 42: p. 200). Lyons elaborates: Just as an operating computer behaves in accordance with a user s instructions which tap into a certain program or set of programs realised in and implemented by a computer s electronic hardware, so the human mind can be described as

4 158 Moe a particular set of, mainly cognitive, programs realised in and implemented by the brain s neural hardware. (29: p. 151) We are now in a position to make the analogy between the computer and the mind explicit. As for how the computer receives information, processes it according to specific programs, and, subsequently, presents a result or output, human information processing operates in a similar way. This is an important part of the background for why the study of cognition namely perception, memory, reasoning, learning, and action has turned into a study of how the mind processes information. These complex processes have been reduced to a three-part procedure: how we receive or gather information about our surroundings, how we process it according to distinct program or rule structures, and how we apply it in our interaction with the world (28: p. 9). The basics of classical cognitivism can also be traced in a more technical sense to the foundational work of Turing and his notion of the Turing machine and to the work of Simon and Newell and their physical symbol system hypothesis. Turing s major achievement was to define the notion of information processing or computation by means of his theoretical device, the Turing machine (7: p. 10). The Turing machine is a logical construct that consists of two parts: a finite set of operating rules, built somehow into the works and unchangeable during operation, and a tape of unlimited length, upon which changeable information can be stored (5: p. 44). Given enough time, the Turing machine is a conceptual way of saying that any well-defined function could be executed, step by step, according to simple if you are in state P and have input Q then do R rules (6: p. 155). By means of this simple construct Turing had developed a theoretical machine that in principle could carry out any possible conceivable computation (17: p. 17; 29: p. 149). This logical machine was one of the foundational developments that gradually prompted scientists of the mind to become more interested in the functional level of symbol manipulation than in behavior or the brain (e.g., 29; 33; 42). Later, in 1976, Newell and Simon presented a reformulation of a Turing computation through their physical symbol system hypothesis (27: p. 141). A physical symbol system has, according to Newell and Simon, the necessary and sufficient means for general intelligent action (as quoted in 14: p. 310). They elaborate: By necessary we mean that any system that exhibits general intelligence will prove upon analysis to be a physical symbol system. By sufficient we mean that any physical symbol system of sufficient size can be organized further to exhibit general intelligence. (As quoted in 14: p. 310) 3 In this seminal statement, according to Dreyfus and Dreyfus, Newell and Simon claim that the human brain and the digital computer, while totally different in structure and mechanism, had at a certain level of abstraction a common functional description. At this level both the human brain and the appropriately programmed digital computer could be seen as two different instantiations of a single species of device a device that generated intelligent behaviour by manipulating symbols by means of formal rules (14: p. 310).

5 A Critique of Cognitivism in Sport 159 A symbol, within this framework, is regarded to be a piece of matter that carries information about some states of affairs (33: p. 66). A symbol is, in other words, a representational device. This representational device carries information, and when this information is being manipulated, intelligent behavior is generated. Thus, a symbol carries information, and it causes things to happen (33: p. 66). Through the notion of a symbol or a symbol manipulation, we have entered the level of representation in cognitivism, that is, to be precise, the level of mental representation. When we refer to the level of mental representation, we zero in on the core of classical cognitivism. According to Gardner s (17: p. 40) analysis, the level of representation constitutes, together with the computer, two of the basic assumptions of traditional cognitive science. The computer served as an existence proof for cognitivism. To quote Gardner, if a man-made machine can be said to reason, have goals, revise its behavior, transform information, and the like, human beings certainly deserve to be characterized in the same way (17: p. 40). In addition, the level of representation constituted a necessary and separate level of analysis. Gardner described the level of representation in the following way: When working at this level, a scientist traffics in such representational entities as symbols, rules, images the stuff of representation which is found between input and output and in addition, explores the ways in which these representational entities are joined, transformed, or contrasted with one another. (17: p. 38) Although it is not always clear what entities the level of representation contains, this level is, for the cognitivist, necessary in order to explain the variety of human behavior, action, and thought (17: p. 38). By means of the two core assumptions of traditional cognitive science we have, in this section, seen how classical cognitivism in general, through computer imagery at the level of mental representation, established a conceptual framework for filling in the void between input and output that behaviorism had left behind. In the next section we shall look at how this framework has been adopted in the sport sciences. Information Processing and Motor Programs Textbooks and journal articles from sport psychology and the field of motor control and learning have widely adopted the general framework of classical cognitivism that has been elaborated here. This is, for example, clearly demonstrated in the classical work of Schmidt and colleagues. In an opening paragraph of a basic chapter in their book Motor Learning and Control, Schmidt and Lee (36) state, Human functioning in the environment can be conceptualized and studied in many ways; one of the most popular is based on the fundamental notion that humans are processors of information. It is assumed that information is available in the environment, that the individual accepts the information into various storage systems called memory, and that the information is processed. The term processed means that the information is coded, that its code may be changed from one form to another, that the information may be combined with other information, and so on. (36: p. 42)

6 160 Moe With a background in the fundamental notion that humans are processors of information, Schmidt and colleagues develop a conceptual framework that accounts for how athletes process information, learn, and control motor skills (cf. 36; 37). Schmidt and colleagues argue that a central, higher ranking executive level organizes the lower ranking effector level to produce desired movements (36; 37). The basic assumption of their conceptual framework is that the information processed at the executive level goes through three distinct stages before it initiates the effector level that is, the motor program(s) and the peripheral motor system. Executive-level processing includes an early or first stimuli-identification stage, an intermediary or second stimuli-response stage, and a final stimuli-programming stage. The logic of this tripartite division suggests that a stimulus first needs to be recognized or identified before an athlete can, at the second stage, decide what kind of response to make. And finally, after the athlete has decided what to do, the third, stimuli-programming, stage is used to organize the motor system to produce the desired movements (cf. 36; 37). From the information processes carried on at the executive level, decisions about what to do are sent further to an effector level including motor programs, the spinal cord, and the muscles. The idea of a motor program is crucial to sport science in general and to the framework offered by Schmidt and colleagues in particular. Basically, the idea of a motor program is a set of motor commands that is prestructured at the executive level and that defines the essential details of a skilled action (37: p. 124). In short, it is an abstract representation that, when initiated, results in the production of a coordinated movement sequence (36: p. 416). Hence, stored within the motor programme are all the movement commands required for controlling the action (53: p. 49). In other words, as soon as the motor program starts or is initiated, the information that is stored in the motor program is sent to the muscles through the spinal cord, and the result of this information processing is seen in the shape of an output, namely, a motor response. In this sense one can claim that a motor program includes rules, commands, or plans of action that specify distinct bodily movements. Thus, motor programs are clearly analogous to the programs one finds in a computer. This relationship is made explicit in the description that follows. Most motor program theorists assume that a movement is organized in advance by a program that sets up some kind of neural mechanism, or network, containing time and event information a movement script, if you will, that specifies certain essential details of the movement as it runs off over time. Some scientists even speak of performers running a motor program, which is clearly analogous to the processes involved in running a computer program (37: p. 132). 4 By means of a basic idea inherited from classical cognitivism, namely that humans are information-processing or computational devices, we have now seen that information processing by athlete goes through distinct stages and that motor programs contain abstract representations, that is, rules, commands, or plans of action, that guide or govern bodily movements as soon as they become initiated. How can the basics of the information-processing approach be applied in the practical world of a coach?

7 A Critique of Cognitivism in Sport 161 From Novice to Expertise and the Development of Automaticity To better appreciate the strengths of the information-processing approach, I now return to the early and pretheoretical days of our coaching careers. I assume that most coaches had a direct approach to movements of sport. Simply by means of an observational approach, we were often able to grasp an athlete s level of competence. With the naked eye we saw, for example, that athletes early in the process of learning were much slower and less efficient in solving different motor problems than their proficient counterparts were. Novice athletes were even quite clumsy. They often fumbled and stumbled and were never quite sure of what to do. On the other hand, the really proficient performers, the experts, were highly confident and efficient. Usually, they were at the right place at the right time doing the right thing in a more or less reliable and effortless manner. The best players simply did what the situations required of them nothing more, nothing less. 5 This direct approach to movements in sport seemed at first sight to be very helpful. Basically, it provided the necessary knowledge of what was required for a beginning athlete to progress to higher levels of proficiency. Later, however, there seemed to be more to athletic agency than met the eye. The differences we saw in athletic behavior had to have some important underlying causes. If expert behavior was fluent and fast, it seemed reasonable to believe that the underlying causes had to have some fluency and fastness associated with them. Even though behavior was an important first step, on reflection it only seemed to be a surface manifestation of something deeper of some underlying processes and conditions that preceded and initiated the overt performance. 6 To enhance our understanding of intentional movements, we needed to understand these underlying processes. The problem was, of course, to gain access to this underlying level of competence. Classical cognitivism came to our rescue. As we have already seen, cognitivism in sport is built on two basic assumptions. First, it claims that athletes are processors of information. Second, it claims that intentional movements are set up in advance by a rule or command structure that has been labeled a motor program. Findings from empirical research seemed to support these notions. Literature on anticipation and decision making in sport, two well-known concepts of cognitivism, showed that experts, in comparison with novices, are known to (a) be faster and more accurate in recognising patterns of play; (b) be able to quickly and accurately detect and locate objects of relevance in the visual field; (c) be superior in anticipating the actions of their opponents based on advance visual cues; (d) have superior knowledge of situational probabilities; (e) make more appropriate tactical decisions; (f) possess deeper and more structured knowledge of both factual and procedural matters; and (h) [sic] possess superior self-monitoring skills. (53: p. 138) Another review that focused directly on differences in information-processing capabilities between athletes who were early and late in the learning process suggested that the elite performer might excel because she/he (a) recognizes the stimulus sooner (perceptual processing), (b) has a variety of appropriate responses

8 162 Moe ready for execution (decision processing), and/or (c) issues movement commands more rapidly (effector processing) (58: p. 7). On the basis of a variety of studies done from an information-processing perspective, we were now able to distinguish athletes at distinct levels of competence in a much more systematic and fine-grained framework than ever before. With comforting scientific precision, we could, for example, coach athletes in terms of early, intermediary, or final stages of information processing. The cognitive paradigm also made us realize that there is much more to the workings of the mind than we had ever been aware of. There is, as Freud had made perfectly clear before cognitivism, a more subtle part of the mind than consciousness. Freud called it the unconscious (22: p. 598). The cognitive paradigm, in turn, labeled it the cognitive unconscious (25). The argument from both a psychoanalytic and a cognitive perspective is that there are truly unconscious mental phenomena in the mind that have a considerable impact on our conscious lives, phenomena such as our desires, beliefs, and intentions (25). Within the cognitive paradigm this argument is supported by contemporary research on the automaticity of perceptual-cognitive and motor skills, subliminal perception, implicit memory, and hypnosis (25). The introduction of the cognitive unconscious has made a whole generation of scientists and practitioners eager to disclose and learn more about the differences between the conscious and unconscious workings of the mind. According to Baars s (3: pp. 74ff.) contrastive analysis of the capabilities of conscious and unconscious processes, conscious processes are known to be computationally inefficient, that is, they have high number of errors, low speed, and mutual interference between conscious computations (p. 75). On the other hand, unconscious processes are known to be highly efficient in their own tasks, that is, they have low number of errors, high speed, and little mutual interference (p. 75). 7 In sport psychology, conscious processes are referred to as controlled processing, and sub- or unconscious processes are referred to as automatic processing (53: p. 43). According to the supporters of the distinction between controlled and automatic processing (38; 47), controlled processing is slow and deliberate, requires attention, and is serial and volitional so that it can be easily altered and applied to changing circumstances. Automatic processing is, on the contrary, fast and effortless, not attention demanding, parallel, and nonvolitional so that it is difficult to modify it once it has been learned (cf. 2: p. 65; 36: p. 68; 53: p. 43). This division of the mind, taken together with the previous differences between athletes at distinct levels of competence, disclosed a new world to a lot of sport scientists and coaches. No wonder expert behavior was fluent and fast. Through a lot of practice it had became automatic and, thus, rendered unconscious (25: p. 1445). The next challenge was to fully understand how movements became automatic. This was where the notion of a motor program entered into the picture. Previously we defined a motor program as an abstract representation that initiated and governed intentional movements. The information-processing approach to intentional movements suggests that practice leads to the development of motor programs (36; 37; 51; 53). Hence, to consider how the abstract representations of motor programs are developed, it might be helpful to consider how we learn a new skill by means of abstract representations. When we start learning a new skill, we often take some rules or instructions into account. In the process of learning the inside pass in soccer, for example, athletes

9 A Critique of Cognitivism in Sport 163 are usually instructed to follow rules such as turn the passing foot outward so that it points 90 on the passing movement, lock up the joint of both the knee and the ankle, and hit the ball at the center with the middle of the inside part of the ankle. In the beginning athletes reflect on the content of these rules and how their behavior will improve if only they follow them carefully. Obviously, their behaviors are guided by the representational content of the rules in a highly conscious and deliberate manner. Later, however, after a lot of practice, their behavior changes. It becomes fluent, fast, and automatic. But what has really happened at an underlying level? How can the transition from conscious and controlled processing to automatic and unconscious processing be explained? 8 According to classical cognitivism, athletes develop more sophisticated and comprehensive motor programs. With practice these programs become more elaborate, controlling longer and longer strings of behavior, and perhaps even modulating various reflexive activities that support the overall movement goal (37: p. 127). Two factors stand out as important. First, we have already seen that stored within the motor programme are all the movement commands required for controlling the action (53: p. 49). Hence, the more sophisticated and comprehensive the program, the more skilled the athlete becomes. Second, movement execution by means of a motor program is carried out in the absence of a direct conscious control (37: p. 127). Automaticity is, in other words, consistent with motor programs (52: p. 44). Hence, automaticity implies that the motor programme becomes increasingly responsible for a greater number of the sequential parts of movement (53: p. 49). At the underlying level, then, athletes develop motor programs that can govern their intentional movements in a highly automatic and unconscious way. 9 Classical cognitivism, in sum, seems to provide sound explanations for many of our coaching experiences. The mechanisms of information processing coupled with different levels of motor programs provide a rationale for the advance and increased automaticity of motor behavior. Nevertheless, we may also encounter problems with cognitivism. A Philosophical Critique of Classical Cognitivism in Sport It is possible that many theorists in our field adopted the conceptual framework of classical cognitivism without thinking through what it entails. Two particular questions need to be asked. These are Do athletes, in fact, process information? and Are the intentional movements of athletes governed by motor programs, that is, by abstract representations in the form of internalized rules or muscle commands? We saw previously how classical cognitivism in sport provided affirmative answers to both of these basic questions, but what answers do the critics of cognitivism offer, and are they able to shake the foundation on which cognitivism rests? It is here that the critiques from Dreyfus and Searle need to be considered. Dreyfus criticizes cognitive theory from his phenomenological viewpoint, whereas the critique from Searle is based on a logical analysis. Despite their distinct perspectives, it is interesting to note that both Dreyfus and Searle are in agreement that classical cognitivism is on the wrong track. I hope the debate between cognitivism, on the one hand, and the critique from philosophy, on the other, will throw new light on our understanding of intentional movements in sport. In this part of the

10 164 Moe article, four arguments against classical cognitivism are examined two from each philosopher. 10 We will begin with the phenomenological perspective. Information Processing Is Without Phenomenological Support The first argument against classical cognitivism in sport is probably the easiest to understand. When Dreyfus tests out the basic assumption of cognitivism that humans are processors of information he turns toward phenomenology for evidence and, consequently, to our experiences. Taken literally, phenomenology is the study of phenomena, that is, how anything appears or shows itself to consciousness. Another way to define phenomenology is to say that it is the study of structures of consciousness as experienced from the first-person point of view (50: p. 1). In this regard, phenomenology involves the description of things as one experiences them, or of one s experiences of things (19: p. 1). Phenomenology is a descriptive endeavor and not, for example, an explanatory one. Kelly notes that phenomenology is essentially descriptive. Its goal is completely and accurately to describe the phenomena of human experience without the interference of metaphysical presuppositions inherited from psychological, scientific, historical, sociological, or other theoretical frameworks (24: p. 162). Understood broadly enough, descriptive phenomenology can be elaborated as a neutral, close and thorough account of phenomena (31: p. 2). Dreyfus was inspired by the phenomenology of Heidegger and Merleau-Ponty. From Heidegger, Dreyfus has, basically, borrowed a phenomenological description that deepens our understanding of what it means for something (things, people, abstractions, language, etc.) to be (8: p. 1). We are, according to Heidegger (21), thrown into a world that is immediately experienced. Moreover, this immediate experience is, according to Merleau-Ponty (30), an embodied encounter. It is primarily from this existential phenomenological tradition that Dreyfus argues against cognitivism. Like Heidegger, Dreyfus is most of all concerned with the phenomena that are closest to us. How we use tools and equipment in our everyday coping with the environment and how we learn skills are questions that Dreyfus entertains. His answers to these questions show, if he is right, that cognitivism provides an inadequate description of intentional activity. First of all, according to Wrathall, Dreyfus points out that the cognitive description of our encountering the world as a set of meaningless, atomistic elements is phenomenologically unsupported (55: p. 95). Dreyfus stresses that things are not encountered as isolated occurrent entities to which we attach isolated function predicates.... [N]othing is intelligible to us unless it first shows up as already integrated into our world, fitting into our coping practices (Dreyfus as quoted in 55: p. 95). Dreyfus supports this claim by referring to the phenomenological experiences of normal living. According to Dreyfus, there is nothing in our everyday consciousness that indicates that human beings process atomistic bits of information. If we go directly to the phenomena we know the best, such as the carpenter s grasp of the hammer or the soccer player s touch of the ball, neither the hammer nor the ball become meaningful objects until after the carpenter or the soccer player have processed the different bits of matter that constitute the hammer or the ball. The carpenter and the soccer player experience immediately what the hammer and the ball are and how they can be used, because these objects are, to quote Heidegger, always

11 A Critique of Cognitivism in Sport 165 already an integrated part of their background. They are natural entities as being meaningfully integrated into our world by a background of coping practices (55: p. 95). This seems to present a strong objection to cognitivism. If everyone were to go directly to the phenomena of our everyday life zu den Sachen selbst! to follow Husserl s methodological advice and carry out a careful description of the activities with which we are familiar, such as opening doors, walking and talking, and driving cars, it would be clear that we are not processing meaningless bits of information in our coping with these activities over time. We simply seem to open doors, walk and talk, and drive cars, period! Dreyfus has shown that classical cognitivism in sport cannot be supported at the level of phenomenological description. But even if cognitivism s basic assumptions about information processing do not find support on the basis of lived experience, we must not ignore the possibility that it may gain support on another level. Let us therefore go to the basis of our phenomenology, namely, to our biology. We need to see if the brain can be explained as an information-processing device. Does the Brain Process Information? To investigate the question of whether the brain is an information-processing device or not, Searle reminds us first of an important distinction. He states that it is absolutely essential to our understanding of the world to be able to distinguish between those features of the world that exist independently of our attitudes and purposes, and those that exist only relative to us (46: p. 62). Searle calls the features or properties that are independent of human attitudes and purposes intrinsic or observer-independent, and features or properties that only exist relative to us are labeled observer-dependent or observer-relative. To illustrate the distinction between observer independence and observer dependence, Searle gives us some examples. Features like force, mass, gravitational attraction, photosynthesis, tectonic plates, molecules, and planets are all examples of observer-independent things (46: p. 62). Searle explains: If we all cease to exist tomorrow, these would go on existing, and indeed, if we had never existed, these would still have existed (46: p. 62). On the other hand, things like houses, cars, money, marriage, and organized sport are all examples of observer-dependent phenomena. These phenomena have special properties by virtue of human agents that ascribe them these special properties. To follow one of Searle s own examples we might say that the piece of paper or metal that we call money is only used as a means of payment because we ascribe special value to money. We can simply buy things with money. 11 The distinction between observer independence and observer dependence is basic to our whole scientific worldview, and we must therefore, according to Searle, take it into account when we study cognitive phenomena. The correspondence theory of the truth seems to be at the core of Searle s worldview. He emphasizes that our claims, if true... have to correspond to facts in the world (46: p. 61). Thus, We have to suppose that there exists a reality totally independent of our representations of it (in a healthier intellectual era it would not be necessary to say that), and we have to suppose that the elements of that reality that we cite in our explanations genuinely functions causally. (45: p. 106).

12 166 Moe This makes up Searle s causal reality constraint. He claims that in explaining cognition we have to cite real features of the world which functions causally (45: p. 107). One of Searle s aims is to defend the claim that some, though of course not all, of the explanatory models in cognitive science fail to meet the causal reality constraint (45: p. 107). We are now in a position to return to the problem in the heading of this section and ask, Does the brain process information? Another way of formulating this question is to ask whether information processing is a real feature of the world that functions causally; that is, does information processing in the brain face up to the causal reality constraint? In other words, we have to, by means of the distinction between observer independence and observer dependence, settle a factual issue about the brain and information processing. What we want to know is whether information processing is an intrinsic feature of the brain or just something that can be ascribed to the brain. If the former alternative is true, then the causal reality constraint is satisfied and we have established a genuine explanation of cognition that functions causally. If the latter alternative is true, then the causal reality constraint remains unsatisfied and we do not have a genuine or intrinsic explanation of cognition. Now, does the brain process information? Because there is no universal agreement, according to Searle, on how to define a computational process, we have to go back to the sources. In Searle s opinion, that is back to the original definitions given by Turing. Previously we accounted for the notion of a Turing machine. This is how Searle explains it: According to Turing, a Turing machine can carry out certain elementary operations: It can rewrite a 0 on its tape as a 1, it can rewrite a 1 on its tape as a 0, it can shift the tape 1 square to the left, or it can shift the tape 1 square to the right. It is controlled by a program of instructions and each instruction specifies a condition and an action to be carried out if the condition is satisfied. (42: p. 205) According to Searle, this is the standard definition of computation. Taken literally, it is, however, at least a bit misleading (42: p. 206). Searle elaborates: If you open up your home computer, you are most unlikely to find any 0 s and 1 s or even a tape. But this does not really matter for the definition. To find out if an object is really a digital computer, it turns out that we do not actually have to look for 0 s and 1 s, etc.; rather we just have to look for something that we could treat as or count as or that could be used to function as a 0 s and 1 s. (42: p. 206) What are the consequences of this scenario? Searle believes the consequences are puzzling, because this machine could be made out of just about anything (42: p. 206). To exemplify, Searle says, the window in front of me is a very simple computer. Window open = 1, window closed = 0 (44: p. 16). This idea can easily be ascribed to how the brain works. We could, for example, say neuron fires = 1, neuron does not fire = 0. The point, according to Searle, is that the definition of computation is in the eyes of the beholder (and can thus be ascribed to a variety of cases). Searle elaborates:

13 A Critique of Cognitivism in Sport 167 The thesis is that there are a whole lot of symbols being manipulated in the brain, 0 s and 1 s flashing through the brain at lightning speed and invisible not only to the naked eye but even to the most powerful electron microscope, and it is these that cause cognition. But the difficulty is that the 0 s and 1 s as such have no causal powers because they do not even exist except in the eyes of the beholder. (42: p. 215) Searle sees notions such as the computer, computation, information processing, and the like as humanly created abstractions. Thus, they are observerdependent features. Something is a computer because we assign that status to it. We discover out in the world that something is a computer only after it has been called or used as a computer by someone (15: p. 164). Now, if we go back to the starting point, We wanted to know if there was not some sense in which brains were intrinsically... [information processing devices] in a way that green leaves intrinsically perform photosynthesis or hearts intrinsically pump blood.... We were looking for some facts of the matter that would make brain processes computational; but [says Searle] given the way we have defined computation, there never could be any such facts of the matter. (42: pp ) This is because [a] physical state of a system is a computational state only relative to the assignment to that state of some computational role, function, or interpretation... Computational states are not discovered within the physics, they are assigned to the physics (42: p. 210). If Searle is right about computation or information processing namely, that they only are observer-dependent phenomena, he has demonstrated that the causal reality constraint remains unsatisfied in terms of information processing in the brain, and, consequently, we do not have a genuine or intrinsic explanation of cognition. Thus, the brain does not intrinsically process information. What, then, is Searle s alternative approach? Biological naturalism is what makes up Searle s philosophy of mind. Biological naturalism is the view that mental phenomena are caused by neurophysiological processes in the brain and are themselves features of the brain (42: p. 1). In biological naturalism mental events and processes are as much part of our biological natural history as digestion, mitosis, meiosis, or enzyme secretion (42: p. 1). So, contrary to the cognitivist who believes that the brain is carrying out computations or information processing, Searle thinks these processes are on much too high a level of abstraction to be able to grasp the concrete biological basis of consciousness and intentionality, namely, the brain (42: p. 224). He elaborates: The brain, as far as its intrinsic operations are concerned, does no information processing. It is a specific biological organ and its specific neurobiological processes cause specific forms of intentionality. In the brain, intrinsically, there are neurobiological processes and sometimes they cause consciousness. But that is the end of the story. All other mental attributions are either dispositional, as when we ascribe unconscious states to the agent, or they are observer relative, as when we assign a computational interpretation to his brain processes. (42: p. 226)

14 168 Moe Interplay The Real Power of Classical Cognitivism in Sport If one is convinced by Dreyfus s phenomenology or Searle s logical analysis, one must answer negatively the first question I asked. Neither a phenomenological description of how we experience everyday life nor a logical analysis of information processing related to the biological brain has supported the basic assumption of cognitivism that athletes are processors of information. But the cognitivist can now argue that the strength of cognitivism lies neither at the phenomenological level that Dreyfus is concerned with (i.e., experience) nor at the biological level that Searle is arguing at (i.e., the brain). Rather, the strength of cognitivism lies somewhere in between these two levels. Between the phenomenology and the biology there is a third intermediate level, namely, the level of mental representation. It is first and foremost at this level that one will discover the rule-governed or program-based information processing of motor programs. And, as we have also seen, motor programs are consistent with automaticity and unconscious processes. Therefore, at this level, the information processing is going on unconsciously. 12 The cognitivist can now argue that neither Dreyfus s phenomenology nor Searle s biological naturalism has disproved the strength of this intermediate cognitive picture. The Regress of Rules of Classical Cognitivism in Sport Against Dreyfus, the cognitivist can argue that it is obvious that we experience things as immediately meaningful, but this happens only after the different bits of information have been processed via a set of rules or programs at a sub-, pre-, or unconscious level. Dreyfus s phenomenology seems to overlook this important insight from the cognitive perspective, because what we experience as meaningful must be experienced through our consciousness, and because the information processing takes place at an unconscious level, Dreyfus s phenomenology will fail to see this level of analysis (55: p. 96). As Wrathall emphasizes, of course we experience the world as already meaningful, the cognitivist might say, but this is only possible because our minds have made it meaningful (55: p. 96). The cognitivist seems to argue that Dreyfus s phenomenological account depends on a cognitive analysis of information processing that is taking place at an unconscious level. According to the cognitivist something has to be processed in order for meaning to arise. It is unconscious processing of the information that is stored within mental representations that causes our experiences of the world as meaningful. But to show that this picture also must be false, Dreyfus refers to his arguments from holism and skills (55: p. 96). Here is the argument from skills: If the human being is a system that processes bits of information in relation to program or rule structures, as the thesis of classical cognitivism goes, this picture will end in an infinite regress of rules even if it proceeds at an unconscious level. Dreyfus describes the regress problem in relation to language skills. He states, To have a complete theory of what speakers are able to do, one must not only have grammatical and semantic rules but further rules which would enable a person or a machine to recognize the context in which the rules must be applied. Thus there must be rules for recognizing the situation, the intentions of the speakers, and so forth. But if the theory then requires further rules in order to explain how these rules are applied, as the pure intellectualist viewpoint would

15 A Critique of Cognitivism in Sport 169 suggest, we are in an infinite regress. Since we do manage to use language, this regress cannot be a problem for human beings. (9: pp ) Naturally, we can exchange the skills of language with the skills of soccer and reach the same end result as Dreyfus has done. The argument will then go like this: If we are to establish a full-blown theory of the skills of a soccer player, we not only must have rules for how the player shall kick and run, but we also need a specification of the rules that makes the player able to recognize the contexts of where the rules are applied. And with the constant changes of the game, we are talking about many rules. The cognitivist must therefore be able to specify an enormous number of rules that make sure that the soccer player is capable of recognizing the different situations and so on. But if the theory then requires even more rules to be able to explain how the former rules are applied, as the pure cognitivist must do according to Dreyfus, then we are in an infinite regress of rules required for applying rules. But because we are indeed capable of playing soccer, the regress of rules does not seem to cause any problems for athletes. Dreyfus is following Wittgenstein s famous insight, that rules cannot determine their own applications (48: p. 858). The point of Dreyfus s argument against the cognitivist is that the application of rules itself depends on skills for applying rules. If we try to capture those skills in terms of the application of further rules, then (55: pp ) we are trapped in the regress-of-rules dilemma. How can the regress be stopped? Dreyfus stops the regress in classical cognitivism by means of situating our skills in a practice and coping background that cannot be rule governed (8; 9; 55). Dreyfus elaborates: In explaining our actions we must always sooner or later fall back on our everyday practices and simply say this is what we do or that s what it is to be a human being. Thus, in the last analysis, all intelligibility and all intelligent behavior must be traced back to our sense of what we are, which is, according to this argument, necessarily, on pain of regress, something we can never explicitly know. (as quoted in 55: p. 94) Contrary to the cognitivist, who argues that meaningless bits of information first become meaningful after unconscious information processing, Dreyfus argues that we experience different phenomena as immediately meaningful simply because they are a part of a bodily and practical background, that is, a bodily background knowledge, that cannot be expressed through facts and rules (55: pp ). Unconscious Rules and the Homunculus Problem Against Searle, the cognitivist can argue that if the information processes, as they are described in classical cognitivism, are on too high a level of abstraction for the concrete biological brain, the details of the biological brain are definitely on too low a level of abstraction to explain higher ranking cognitive phenomena such as intentionality and consciousness. Really, to be able to grasp these higher ranking phenomena, we need the level of representation at which rule-governed information processing is carried out through unconscious processes. It is only by means of a specification of these processes that we are able to explain human agency. In fact, if we are able to specify these processes completely, we do not