Pylyshyn's Definition and Approach

The second definition or approach within cognitive science has been defended by PYLYSHYN. He insists that mental images have no place in cognitive psychology, since this science should be a precise one, making no allusions to elements that we "intuitively" understand from the common-sense point of view. His view is that

IMAGES HAVE NO PLACE IN COGNITIVE PSYCHOLOGY.

His reasons for this view are based on one the goals of cognitive psychology: it is to provide a credible explanation of the mechanisms of cognition and thought, without recourse to indefinable, vague, intuited, or unanalysed terms. Among his objections to using the term "images" in explantions of human cognitive processes:
  • ONE CANNOT COMPUTE USING AN IMAGE (ONE CANNOT ADD, SUBTRACT, MULTIPLY, OR DIVIDE AN IMAGE)
  • IMAGES HAVE NO INTRISIC MEANING
  • IMAGES MUST "SEEN" TO BE IMAGES AND SEEING MUST BE BROKEN DOWN INTO CONCEPTUAL UNITS
  • IMAGES HAVE NO PLACE IN THOUGHT BECAUSE THINKING IS CONCEPT-BASED, NOT IMAGE-BASED.
  • Each of these points requires considerable elaboration and defense. There are some very strong general philosophic grounds for this view. In addition, there are other, more detailed, descriptivist arguments

    In one sense, Pylyshyn's approach is similar to that of traditional psychology. He accepts that "mental images" are just the "things" we are directly aquainted with in conscious states. This is precisely what we mean by the term mental images. But cognitive psychology has no real interest in these phenomena. Rather, it is concerned with the unconscious structures and processes that MUST underlie human information processing. Explaining consiciousness is really not a concern of cognitive science per se.

    IMPORTANT NOTE: Many have argued that computations do in fact "explain" consciousness. However, others (e.g., Pylyshyn and Jackendoff), while accepting that computationalism does NOT EXPLAIN the appearance of conscious states, have argued that this is essentially irrelevant to accepting cognitive science. This science is concerned with

    PROVIDING AN ADEQUATE MODEL OF HUMAN COGNITION.

    This view brings us to a complicated argument in the philosophy of science, since the relation between models and explanations needs to be clarified. Also, one must ask "what types of models are available to this science." There are some options here, but Pylyshyn, and many others of his school, have tried to model cognitive processes primarily on

    WELL-KNOWN PRINCIPLES OF COMPUTATION IN MACHINES

    Now, it may be that cognitive science is not limited to such models, but if it is, then, in my view, cognitive science can have no explanation of consciousness, and since it is not directely concerned with conscious "elements," such as mental images, the entire science is orthogonal to the study of mental images proper. That is not to say that some methods of investigation derived from cognitive science cannot discover significant facts relating to mental images -- indeed, the strongest proof that true eidetic images exist is owed to controlled experiment -- but the task of finding the nature of mental images belongs to philosophy and traditional psychology. The computational "explanations" (if that is what they are) of our mental capabilities, while interesting, do not directly address the phenomena of mental life with which we are directly acquainted. Hence, there is a sense in which computational models are uninteresting unless they also completely explain the entire mystery of consciousness and seamlessly incorporate every aspect of our lives.

    Let me put the matter another way: the difference between contemporary cognitive science and traditional psychology is that traditional psychology accepts human consciousness as a fact, a given (psychology = study of the psyche, the mind or soul), and cognitive science turns consciousness into a problem, something standing in need of explanation in physical, mechanistic, or computational terms. Thus, however well human cognitive processes might be modeled in terms of abstract functions, information flow, computational structures, or other other metaphors, an addtional step is needed to turn this description or model into an explanation.

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