GROWTH OF COGNITIVE SCIENCE
Questions about the nature of mentality have been asked throughout human existence. How are ideas represented in the mind? Are different kinds of concepts stored in different parts of the brain? Is the capacity for language innate or learned? How are language, perception, and thought interrelated? For a long while these and other such questions remained in the province of philosophy. The empirical study of cognition did not really become established as a field until the 19th century. Perhaps paradoxically, however, the first stage in the development of this science was a divisive one. Around the beginning of the 20th century, the study of cognition in terms of psychology, linguistics, neuroscience, and so on each developed into a distinct and separate area of inquiry. A general hiatus in cognitive science as a whole then followed, during the period when behaviorism came to dominate psychologyÑroughly, from 1920 to 1950.
During this period, nonetheless, certain events and ideas interacted to form the foundations on which modern cognitive science is built. One of these was the growth of computer science, along with the development of information theory by Claude Shannon and of cybernetics by Norbert Wiener and John von Neumann. Another contributing idea was the central concept set out by Alan Turing: that a finite machine can carry out any conceivable calculation if it goes through a sufficient number of steps. Turing also proposed what is now called the Turing test to judge whether a computer can be said to think. If a human interviewer is allowed to question the computer at will and cannot then distinguish it from a human on the basis of the answers, the computer has passed the Turing test.
The field of artificial intelligence developed from these roots, with scientists such as John McCarthy, Marvin Minsky, Allen Newell, and Herbert Simon as its early leaders. The importance of artificial intelligence to cognitive science lay not only in the idea that machines could conceivably be programmed to think like humans, but also in the equally bold idea that by explicitly describing the processes of thinking, those processes could be made available to empirical study.
Cognitive psychology emerged as a subfield of psychology in the late 1960s. It operated on the concept that human thinking can be modeled as a program, in a symbolic language, to be carried out on a computational device.
The linguist Noam Chomsky, applying this concept in his own field, demonstrated that models that might have been compatible with behaviorism's chains of stimulus-response could not account for the generative nature of human language. Psychologists such as George Armitage Miller and Ulric Neisser also applied these insights to their descriptions of cognition. While linguistics and psychology and other disciplines continued for some time to progress along separate tracks in these efforts, the feeling was growing among many researchers that no single discipline was adequate to the problemÑthat understanding the complexity of the human mind required a combination of different methods of study.
Cognitive science was the result. It is by now well-established internationally as a field of its own, with societies and centers scattered around the world. While most researchers do not consider cognitive science as a whole to be a replacement for its subdisciplines, the cognitive-science approach of interdisciplinary collaboration is leading to fruitful interpenetrations among those disciplines. Cognitive science also has applications in education and in the workplace. In education, researchers such as Jerome Bruner have stressed the social construction of cognitive models and have proposed methods for making classrooms more effective in promoting optimal ways of thinking about the world. In the workplace, the field of engineering psychology draws on research in cognitive science to identify people's typical mental models of vices and processes. It has been found that people can learn to use a new device more quickly and with fewer errors if it fits the causal pattern they expect, and cognitive scientists such as Donald Norman have set forth design principles that fit people's normal cognitive models.