The Psychology of Expertise and Knowledge Acquisition: Comments on the Chapters in This Volume
The following commentaries on the chapters in this volume start with a few humble premises. The realization is inescapable that the enterprise of psychology is vast, has a long history, and is deeply divided into often noncommunicating subfields. The enterprise of artificial intelligence (AI) is much younger than psychology and yet is also divided into areas that barely communicate with each other. The divisions in AI often parallel those in psychology and often seem to be motivated by similar theoretical and methodological concerns. In addition, the enterprise of expert system construction, and in particular knowledge acquisition (KA), is but one tiny corner of AI, yet the activities focused on expertise are expanding beyond the narrow confines of computer science. It is as if a new field concerning itself with expertise, knowledge, and expert system construction -- a field as yet unnamed -- is trying to be born. It is an event exciting to witness, but it leaves the poor commentator with no fixed or generally agreed-upon platform -- no firm Newtonian coordinate system from which to survey and summarize multidisciplinary research.
And yet, some framework has to be used. So I propose to make use of the basic model of the KA process that was described in the second chapter of this volume, and I would like to refer the reader to the figures, especially Figure 2.3. I will be referring to that basic model as I discuss the contributions to this volume, in order. For each chapter, I try to mention its key concerns and contributions, and I also point to lingering issues and problems.
The chapter by Cooke (chap. 3) directly addresses the issue of the nature of expertise. Much of the material in chapter 3 would be new to the typical implementor or researcher in the expert systems field. This seems paradoxical. Surely, if one is eager to build expert systems, first one would try to find out about expertise. Hence, a chapter outlining current work in the psychology of expertise should not be especially informative to the AI practitioner. Yet, because of the historical development of the AI field, or because psychology of the past had little to offer to those studying knowledge, or because psychology traditionally focused on process rather than content, the cultural gulf between AI and psychology is deep. Although one often has to read between the lines to see it, psychology is often construed as being partly, if not largely, irrelevant to AI (cf. Newell, 1983). For instance,
It is by no means evident just what the intelligence of people and the intelligence of computers have in common beyond their ability to perform certain tasks. ( Simon & Kaplan, 1989, p. 4)
Indeed, I have heard it expressed by some members of one particular school of thought in