Design has long been an area of particular interest for AI researchers. Herbert Simon's 1968 Karl Taylor Compton lectures on the sciences of the artificial included substantial material on design. However, only recently have design researchers embraced paradigms from AI and AI researchers chosen design as a domain to study.

Contrary to many prevailing approaches to knowledge acquisition, Laps, our expert-interviewing software, begins by soliciting cases from the expert, but it does not end there. Laps begins with a case in the form of a sample solution path elicited from the domain expert. This sample solution path is refined by a process called dechunking, which facilitates finding a model of the expert's reasoning process. Once these tables have been set up, the expert is able to produce row after row on his own until a complete rule base is built.

The system, Hoist, performs fault diagnosis without the use of a repair expert or shallow rules. Its knowledge is coded directly from a structural specification of the Mark 45 lower hoist. In a mechanism like the lower hoist, the functional model must reason about forces, fluid pressures, and mechanical linkages; that is, it must reason about qualitative physics. Hypothetical reasoning, the process embodied in Hoist, has general utility in qualitative physics and reason maintenance.

This article examines the near-term impact of expert system technology on work and the organization. From this analysis, a framework is constructed for viewing the impact of these technologies -- and technologies in general -- as a function of the technology itself; market realities; and personal, organizational, and societal values and policy choices. Two scenarios are proposed with respect to the application of this framework to expert systems. The second scenario posits that expert system diffusion will be pulled by, and will be a contributing factor toward, the evolution of the lean, flexible, knowledge-intensive, postindustrial organization.

This article examines the near-term impact of expert system technology on work and the organization. First, an approach is taken for forecasting the likely extent of the diffusion, or success, of the technology. Next, the case of advanced manufacturing technologies and their effects is considered. From this analysis, a framework is constructed for viewing the impact of these technologies -- and technologies in general -- as a function of the technology itself; market realities; and personal, organizational, and societal values and policy choices. Two scenarios are proposed with respect to the application of this framework to expert systems. The first concludes that expert systems will have little impact on the nature of work and the organization. The second scenario posits that expert system diffusion will be pulled by, and will be a contributing factor toward, the evolution of the lean, flexible, knowledge-intensive, postindustrial organization.

The two-volume set entitled "Knowledge-Based Systems (Volume 1, Knowledge Acquisition for Knowledge-Based Systems, 355 pp., and Volume 2, "Knowledge Acquisition Tools for Expert Systems, 343 pp., Academic Press, San Diego, California, 1988), edited by B. R. Gaines and J. H. Boose, is an excellent collection of papers useful to both commercial practitioners of knowledge-based-systems development and research-oriented scientists at specialized centers or academic institutions.

Letters to the Editor.

Nevertheless, significant aspects of behavior and user expectation are peculiar to expert systems and their users. These considerations are discussed here with examples from an actual system. Guidelines for the behavior of expert systems and the responsibility of designers to their users are proposed.