to assume that the only way to solve problems is to build more programs. These biases can be self-serving, of course. Psychologists. generate more experiments; computer scientists generate more compilers. But when the disciplines dovetail, as they do in "cognitive science," the research can seem especially self-serving. The clearest example of this is the bounty (to put it mildly) of reports on problem solving by computer programmers. (Will we see computer models of the knowledge of expert computer programmers?) I do not really mean to denigrate that particular research topic; it is important. But surely there are other things in the world to study. It is clear that all of us, psychologist and computer scientist, need to expand our conceptual horizons . . . and our capabilities. It also seems clear that, for topics in expertise, it helps to work together. It is hoped that this volume contributes to the spirit of interdisciplinary research, both basic and applied.
Expert systems technology may or may not evolve significantly beyond rule-based operations and their brittleness problems ( Keyes, 1989). But imagine an empirically based "knowledge elicitation methods palette" that enables one to specify the methods needed to capture the knowledge and skills of experts in a given domain. Imagine the benefits to society of an advanced technology for representing and disseminating the knowledge and skills of the best corporate managers, the most seasoned pilots, or the most renowned medical diagnosticians! It is hoped that this volume contributes in some way to that enterprise.
This volume should be of interest to cognitive psychologists and computer scientists, and to those who are out in the trenches developing expert systems. It should be of interest to anyone who is pondering the nature of expertise and the question of how it can be studied scientifically.
Long Island, NY Robert R. Hoffman
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