Mind, Body, World

Michael R. W. Dawson

• Publisher: AU Press
• Year: 2013
• ISBN:
  9781927356197
• Topic: Psychology
• Subtopic: Cognitive Science
• Index: Psychology

Cognitive science arose in the 1950s when it became apparent that a number of disciplines, including psychology, computer science, linguistics, and philosophy, were fragmenting. Perhaps owing to the field's immediate origins in cybernetics, as well as to the foundational assumption that cognition is information processing, cognitive science initially seemed more unified than psychology. However, as a result of differing interpretations of the foundational assumption and dramatically divergent views of the meaning of the term information processing, three separate schools emerged: classical cognitive science, connectionist cognitive science, and embodied cognitive science.

Examples, cases, and research findings taken from the wide range of phenomena studied by cognitive scientists effectively explain and explore the relationship among the three perspectives. Intended to introduce both graduate and senior undergraduate students to the foundations of cognitive science, Mind, Body, World addresses a number of questions currently being asked by those practicing in the field: What are the core assumptions of the three different schools? What are the relationships between these different sets of core assumptions? Is there only one cognitive science, or are there many different cognitive sciences? Giving the schools equal treatment and displaying a broad and deep understanding of the field, Dawson highlights the fundamental tensions and lines of fragmentation that exist among the schools and provides a refreshing and unifying framework for students of cognitive science.

1

The Cognitive Sciences: One or Many?

1.0 Chapter Overview

When experimental psychology arose in the nineteenth century, it was a unified discipline. However, as the experimental method began to be applied to a larger and larger range of psychological phenomena, this new discipline fragmented, causing what became known in the 1920s as the “crisis in psychology,” a crisis that has persisted to the present day.

Cognitive science arose in the 1950s when it became apparent that a number of different disciplines, including psychology, computer science, linguistics and philosophy, were fragmenting. Some researchers responded to this situation by viewing cognition as a form of information processing. In the 1950s, the only plausible notion of information processing was the kind that was performed by a recent invention, the digital computer. This singular notion of information processing permitted cognitive science to emerge as a highly unified discipline.

A half century of research in cognitive science, though, has been informed by alternative conceptions of both information processing and cognition. As a result, the possibility has emerged that cognitive science itself is fragmenting. The purpose of this first chapter is to note the existence of three main approaches within the discipline: classical cognitive science, connectionist cognitive science, and embodied cognitive science. The existence of these different approaches leads to obvious questions: What are the core assumptions of these three different schools of thought? What are the relationships between these different sets of core assumptions? Is there only one cognitive science, or are there many different cognitive sciences? Chapter 1 sets the stage for asking such questions; the remainder of the book explores possible answers to them.

1.1 A Fragmented Psychology

Modern experimental psychology is rooted in two seminal publications from the second half of the nineteenth century (Schultz & Schultz, 2008), Fechner’s (1966) Elements of Psychophysics, originally published in 1860, and Wundt’s Principles of Physiological Psychology, originally published in 1873 (Wundt & Titchener, 1904). Of these two authors, it is Wundt who is viewed as the founder of psychology, because he established the first experimental psychology laboratory—his Institute of Experimental Psychology—in Leipzig in 1879, as well as the first journal devoted to experimental psychology, Philosophical Studies, in 1881 (Leahey, 1987).

Fechner’s and Wundt’s use of experimental methods to study psychological phenomena produced a broad, unified science.

This general significance of the experimental method is being more and more widely recognized in current psychological investigation; and the definition of experimental psychology has been correspondingly extended beyond its original limits. We now understand by ‘experimental psychology’ not simply those portions of psychology which are directly accessible to experimentation, but the whole of individual psychology. (Wundt & Titchner, 1904, p. 8)

However, not long after its birth, modern psychology began to fragment into competing schools of thought. The Würzberg school of psychology, founded in 1896 by Oswald Külpe, a former student of Wundt’s, challenged Wundt’s views on the scope of psychology (Schultz & Schultz, 2008). The writings of the functionalist school being established in North America were critical of Wundt’s structuralism (James, 1890a, 1890b). Soon, behaviourism arose as a reaction against both structuralism and functionalism (Watson, 1913).

Psychology’s fragmentation soon began to be discussed in the literature, starting with Bühler’s 1927 “crisis in psychology” (Stam, 2004), and continuing to the present day (Bower, 1993; Driver-Linn, 2003; Gilbert, 2002; Koch, 1959, 1969, 1976, 1981, 1993; Lee, 1994; Stam, 2004; Valsiner, 2006; Walsh-Bowers, 2009). For one prominent critic of psychology’s claim to scientific status,

psychology is misconceived when seen as a coherent science or as any kind of coherent discipline devoted to the empirical study of human beings. Psychology, in my view, is not a single discipline but a collection of studies of varied cast, some few of which may qualify as science, whereas most do not. (Koch, 1993, p. 902)

The fragmentation of psychology is only made more apparent by repeated attempts to find new approaches to unify the field, or by rebuttals against claims of disunity (Drob, 2003; Goertzen, 2008; Henriques, 2004; Katzko, 2002; Richardson, 2000; Smythe & McKenzie, 2010; Teo, 2010; Valsiner, 2006; Walsh-Bowers, 2009; Watanabe, 2010; Zittoun, Gillespie, & Cornish, 2009).

The breadth of topics being studied by any single psychology department is staggering; psychology correspondingly uses an incredible diversity of methodologies. It is not surprising that Leahey (1987, p. 3) called psychology a “large, sprawling, confusing human undertaking.” Because of its diversity, it is likely that psychology is fated to be enormously fragmented, at best existing as a pluralistic discipline (Teo, 2010; Watanabe, 2010).

If this is true of psychology, then what can be expected of a more recent discipline, cognitive science? Cognitive science would seem likely to be even more fragmented than psychology, because it involves not only psychology but also many other disciplines. For instance, the website of the Cognitive Science Society states that the Society,

brings together researchers from many fields that hold a common goal: understanding the nature of the human mind. The Society promotes scientific interchange among researchers in disciplines comprising the field of Cognitive Science, including Artificial Intelligence, Linguistics, Anthropology, Psychology, Neuroscience, Philosophy, and Education. (Cognitive Science Society, 2013)

The names of all of these disciplines are proudly placed around the perimeter of the Society’s logo.

When cognitive science appeared in the late 1950s, it seemed to be far more unified than psychology. Given that cognitive science draws from so many different disciplines, how is this possible?

1.2 A Unified Cognitive Science

When psychology originated, the promise of a new, unified science was fuelled by the view that a coherent object of enquiry (conscious experience) could be studied using a cohesive paradigm (the experimental method). Wundt defined psychological inquiry as “the investigation of conscious processes in the modes of connexion peculiar to them” (Wundt & Titchner, 1904, p. 2). His belief was that using the experimental method would “accomplish a reform in psychological investigation comparable with the revolution brought about in the natural sciences.” As experimental psychology evolved the content areas that it studied became markedly differentiated, leading to a proliferation of methodologies. The fragmentation of psychology was a natural consequence.

Cognitive science arose as a discipline in the mid-twentieth century (Boden, 2006; Gardner, 1984; Miller, 2003), and at the outset seemed more unified than psychology. In spite of the diversity of talks presented at the “Special Interest Group in Information Theory” at MIT in 1956, cognitive psychologist George Miller,

left the symposium with a conviction, more intuitive than rational, that experimental psychology, theoretical linguistics, and the computer simulation of cognitive processes were all pieces from a larger whole and that the future would see a progressive elaboration and coordination of their shared concerns. (Miller, 2003, p. 143)

The cohesiveness of cognitive science was, perhaps, a natural consequence of its intellectual antecedents. A key inspiration to cognitive science was the digital computer; we see in Chapter 2 that the invention of the computer was the result of the unification of ideas from the diverse fields of philosophy, mathematics, and electrical engineering.

Similarly, the immediate parent of cognitive science was the field known as cybernetics (Ashby, 1956; de Latil, 1956; Wiener, 1948). Cybernetics aimed to study adaptive behaviour of intelligent agents by employing the notions of feedback and information theory. Its pioneers were polymaths. Not only did cyberneticist William Grey Walter pioneer the use of EEG in neurology (Cooper, 1977), he also invented the world’s first autonomous robots (Bladin, 2006; Hayward, 2001; Holland, 2003a; Sharkey & Sharkey, 2009). Cybernetics creator Norbert Wiener organized the Macy Conferences (Conway & Siegelman, 2005), which were gatherings of mathematicians, computer scientists, psychologists, psychiatrists, anthropologists, and neuroscientists, who together aimed to determine the general workings of the human mind. The Macy Conferences were the forerunners of the interdisciplinary symposia that inspired cognitive scientists such as George Miller.

What possible glue could unite the diversity of individuals involved first in cybernetics, and later in cognitive science? One answer is that cognitive scientists are united in sharing a key foundational assumption that cognition is information processing (Dawson, 1998). As a result, a critical feature of cognition involves representation or symbolism (Craik, 1943). The early cognitive scientists,

realized that the integration of parts of several disciplines was possible and desirable, because each of these disciplines had research problems that could be addressed by designing ‘symbolisms.’ Cognitive science is the result of striving towards this integration. (Dawson, 1998, p. 5)

Assuming that cognition is information processing provides a unifying principle, but also demands methodological pluralism. Cognitive science accounts for human cognition by invoking an information processing explanation. However, information processors themselves require explanatory accounts framed at very different levels of analysis (Marr, 1982; Pylyshyn, 1984). Each level of analysis involves asking qualitatively different kinds of questions, and also involves using dramatically different methodologies to answer them.

Marr (1982) proposed that information processors require explanations at the computational, algorithmic, and implementational levels. At the computational level, formal proofs are used to determine what information processing problem is being solved. At the algorithmic level, experimental observations and computer simulations are used to determine the particular information processing steps that are being used to solve the information processing problem. At the implementational level, biological or physical methods are used to determine the mechanistic principles that actually instantiate the information processing steps. In addition, a complete explanation of an information processor requires establishing links between these different levels of analysis.

An approach like Marr’s is a mandatory consequence of assuming that cognition is information processing (Dawson, 1998). It also makes cognitive science particularly alluring. This is because cognitive scientists are aware not only that a variety of methodologies are required to explain information processing, but also that researchers from a diversity of areas can be united by the goal of seeking such an explanation.

As a result, definitions of cognitive science usually emphasize co-operation across disciplines (Simon, 1980). Cognitive science is “a recognition of a fundamental set of common concerns shared by the disciplines of psychology, computer science, linguistics, economics, epistemology, and the social sciences generally” (Simon, 1980, p. 33). Interviews with eminent cognitive scientists reinforce this theme of interdisciplinary harmony and unity (Baumgartner & Payr, 1995). Indeed, it would appear that cognitive scientists deem it essential to acquire methodologies from more than one discipline.

For instance, philosopher Patricia Churchland learned about neuroscience at the University of Manitoba Medical School by “doing experiments and dissections and observing human patients with brain damage in neurology rounds” (Baumgartner & Payr, 1995, p. 22). Philosopher Daniel Dennett improved his computer literacy by participating in a year-long working group that included two philosophers and four AI researchers. AI researcher Terry Winograd studied linguistics in London before he went to MIT to study computer science. Psychologist David Rumelhart observed that cognitive science has “a collection of methods that have been developed, some uniquely in cognitive science, but some in related disciplines. … It is clear that we have to learn to appreciate one another’s approaches and understand where our own are weak” (Baumgartner & Payr, 1995, p. 196).

At the same time, as it has matured since its birth in the late 1950s, concerns about cognitive science’s unity have also arisen. Philosopher John Searle stated, “I am not sure whether there is such a thing as cognitive science” (Baumgartner & Payr, 1995, p. 203). Philosopher John Haugeland claimed that “philosophy belongs in cognitive science only because the ‘cognitive sciences’ have not got their act together yet” (p. 103). AI pioneer Herbert Simon described cognitive science as a label “for the fact that there is a lot of conversation across disciplines” (p. 234). For Simon, “cognitive science is the place where they meet. It does not matter whether it is a discipline. It is not really a discipline—yet.”

In modern cognitive science there exist intense disagreements about what the assumption “cognition is information processing” really means. From one perspective, modern cognitive science is fragmenting into different schools of thought—classical, connectionist, embodied—that have dramatically different views about what the term information processing means. Classical cognitive science interprets this term as meaning rule-governed symbol manipulations of the same type performed by a digital computer. The putative fragmentation of cognitive science begins when this assumption is challenged. John Searle declared, “I think that cognitive science suffers from its obsession with the computer metaphor” (Baumgartner & Payr, 1995, p. 204). Philosopher Paul Churchland declared, “we need to get away from the idea that we are going to achieve Artificial Intelligence by writing clever programs” (p. 37).

Different interpretations of information processing produce variations of cognitive science that give the strong sense of being mutually incompatible. One purpose of this book is to explore the notion of information processing at the foundation of each of these varieties. A second is to examine whether these notions can be unified.

1.3 Cognitive Science or the Cognitive Sciences?

One reason that Wilhelm Wundt is seen as the founder of psychology is because he established its first academic foothold at the University of Leipzig. Wundt created the first experimental psychology laboratory there in 1879. Psychology was officially part of the university calendar by 1885. Today, hundreds of psychology departments exist at universities around the world.

Psychology is clearly healthy as an academic discipline. However, its status as a science is less clear. Sigmund Koch, a noted critic of psychology (Koch, 1959, 1969, 1976, 1981, 1993), argued in favor of replacing the term psychology with the psychological studies because of his view that it was impossible for psychology to exist as a coherent discipline.

Although it is much younger than psychology, cognitive science has certainly matured into a viable academic discipline. In the fall of 2010, the website for the Cognitive Science Society listed 77 universities around the world that offered cognitive science as a program of study. Recent developments in cognitive science, though, have raised questions about its scientific coherence. To parallel Koch, should we examine “cognitive science,” or is it more appropriate to inquire about “the cognitive sciences”? Investigating this issue is one theme of the current book.

According to psychologist George Miller (2003), cognitive science was born on September 11, 1956. At this early stage, the unity of cognitive science was not really an issue. Digital computers were a relatively recent invention (Goldstine, 1993; Lavington, 1980; Williams, 1997; Zuse, 1993). At the time, they presented a unified notion of information processing to be adopted by cognitive science. Digital computers were automatic symbol manipulators (Haugeland, 1985): they were machines that manipulated symbolic representations by applying well-defined rules; they brought symbolic logic to mechanized life. Even though some researchers had already noted that the brain may not work exactly like a computer, the brain was still assumed to be digital, because the all-or-none generation of an action potential was interpreted as being equivalent to assigning a truth value in a Boolean logic (McCulloch & Pitts, 1943; von Neumann, 1958).

Classical cognitive science, which is the topic of Chapter 3, was the first school of thought in cognitive science and continues to dominate the field to this day. It exploited the technology of the day by interpreting “information processing” as meaning “rule-governed manipulation of symbol” (Feigenbaum & Feldman, 1995). This version of the information processing hypothesis bore early fruit, producing major advances in the understanding of language (Chomsky, 1957, 1959b, 1965) and of human problem solving (Newell, Shaw, & Simon, 1958; Newell & Simon, 1961, 1972). Later successes with this approach led to the proliferation of “thinking artifacts”: computer programs called expert systems (Feigenbaum & McCorduck, 1983; Kurzweil, 1990). Some researchers have claimed that the classical approach is capable of providing a unified theory of thought (Anderson, 1983; Anderson et al., 2004; Newell, 1990).

The successes of the classical approach were in the realm of well-posed problems, such problems being those with unambiguously defined states of knowledge and goal states, not to mention explicitly defined operations for converting one state of knowledge into another. If a problem is well posed, then its solution can be described as a search through a problem space, and a computer can be programmed to perform this search (Newell & Simon, 1972). However, this emphasis led to growing criticisms of the classical approach. One general issue was whether human cognition went far beyond what could be captured just in terms of solving well-posed problems (Dreyfus, 1992; Searle, 1980; Weizenbaum, 1976).

Indeed, the classical approach was adept at producing computer simulations of game playing and problem solving, but was not achieving tremendous success in such fields as speech recognition, language translation, or computer vision. “An overall pattern had begun to take shape…. an early, dramatic success based on the easy performance of simple tasks, or low-quality work on complex tasks, and then diminishing returns, disenchantment, and, in some cases, pessimism” (Dreyfus, 1992, p. 99).

Many abilities that humans are expert at without training, such as speaking, seeing, and walking, seemed to be beyond the grasp of classical cognitive science. These abilities involve dealing with ill-posed problems. An ill-posed problem is deeply ambiguous, has poorly defined knowledge states and goal states, and involves poorly defined operations for manipulating knowledge. As a result, it is not well suited to classical analysis, because a problem space cannot be defined for an ill-posed problem. This suggests that the digital computer provides a poor definition of the kind of information processing performed by humans. “In our view people are smarter than today’s computers because the brain employs a basic computational architecture that is more suited to deal with a central aspect of the natural information processing tasks that people are so good at” (Rumelhart & McClelland, 1986c, p. 3).

Connectionist cognitive science reacted against classical cognitive science by proposing a cognitive architecture that is qualitatively different from that inspired by the digital computer metaphor (Bechtel & Abrahamsen, 2002; Churchland, Koch, & Sejnowski, 1990; Churchland & Sejnowski, 1992; Clark, 1989, 1993; Horgan & Tienson, 1996; Quinlan, 1991). Conn...