We are victims of one common superstitionthe superstition that we understand the changes that are daily taking place in the world because we read about them and know what they are. The anthropological stories and the concept of memes were brought to my attention several years ago by Lynn Conway Much of the vision and some of the material was drawn from a paper that we worked on together but never published. The important distinction between process and product, was made crisp for me by John Seely Brown, who also has encouraged and made possible projects like Trillium, which I watched with interest, and like Colab, in which I participated. Joshua Lederberg kindled my interest in biological issues and a respect for knowledge processes and their partial automation that has not faded Dan Bobrow listened to my ramblings on several runs, agonized over my confusions, helped to get the kinks out of the arguments, and suggested the title for the article Sanjay Mittal and I have spent many hours speculating together on the issues in building community knowledge bases and knowledge servers and in understanding the principles of knowledge competitions Austin Henderson helped me to understand the Trillium story and to report it accurately. Austin and Sanjay hounded me to say, more precisely, what a knowledge medium is Agustin Araya and Mark Miller participated in a Colab session in which we tried to jointly lay out these ideas, and together asked me to make the prescriptions clearer Ed Feigenbaum persuaded me to be more precise in the discussion of the limits of today's expert systems technology Thanks to Agustin Araya, Dan Bobrow, John Seely Brown, Lynn Conway, Bob Engelmore, Ed Feigenbaum, Felix Frayman, Gregg Foster, Austin Henderson, Ken Kahn, Mark Miller, Sanjay Mittal, Julian Orr, Allen Sears, Lucy Suchman, and Paul Wallich for reading early drafts of this paper and for helping to clarify the ideas and improve the article's readability Stephen Cross triggered the writing of this article when he invited me to give the keynote address at the Aerospace Applications of Artificial Intelligence Conference in Dayton, Ohio, in September 1985.

Hence, at a coarse-grained level of abstraction, KB-Ss can be characterized in terms of two components: (1) a knowledge base, encoding the knowledge embodied by the system, and (2) a reasoning engine, which is able to query the knowledge base, infer or acquire knowledge from external sources, and add new knowledge to the knowledge base. A knowledge-level account of a KBS (that is, a competencecentered, implementation-independent description of a system), such as Clancey's (1985) analysis of first-generation rule-based systems, focuses on the task-centered competence of the system; that is, it addresses issues such as what kind of problems the KBS is designed to tackle, what reasoning methods it uses, and what knowledge it requires. In contrast with task-centered analyses, Levesque and Lakemeyer focus on the competence of the knowledge base rather than that of the whole system. Hence, their notion of competence is a task-independent one: It is the "abstract state of knowledge" (p. This is an interesting assumption, which the "proceduralists" in the AI community might object to: According to the procedural viewpoint of knowledge representation, the knowledge modeled in an application, its representation, and the associated knowledge-retrieval mechanisms have to be engineered as As a result, they would argue, it is not possible to discuss the knowledge of a system independently of the task context in which the system is meant to operate.

The project is large and has a number of components that have been documented at length. These components have never been drawn together in one document; thus, this article describes the project and gives a taste of the individual subprojects that have kept the project members so busy for so long. A large number of publications have emerged from the project, so a full bibliography of the work appears for the reader who wants to follow up on any intriguing topics. AAP straddles a number of research areas and, thus, does not fall easily into any one sphere of interest. A certain amount of work has been done on the parallelizing of expert systems, most notably by Gupta (1986).

The annual conference of the American Association for Artificial Intelligence (AAAI) is the premier U.S. gathering for artificial intelligence (AI) theoreticians and practitioners. Regardless of the exact figure, I believe that the majority of large U.S. organizations are currently preparing to put AI technology into operation or have already done so. IBM Unveils Its Al Plans As if to testify that AI is now legitimate technology in corporate America, IBM chose AAAI-86 to unfurl its dedication to AI. In the keynote address, Herb Schorr, IBM's AI czar, presented IBM's recently organized program for AI activities. Schorr leads IBM's AI Project Office, a new type of IBM organization that will permeate all IBM activities and organizations related to AI. Schorr's organization currently consists of 12 people with full responsibility within IBM for (1) developing AI products for internal and external use, (2) marketing AI products outside IBM, and (3) applying AI tools and technology within IBM.

"It was good to see the number of student attendees up," noted American Association for Artificial Intelligence (AAAI) President Tom Mitchell, "and that our attendance was so high despite the economic downturn. I think the meeting was even more stimulating because of the co-location of AAAI with so many other conferences in Edmonton at the same time." This article provides a few snapshots of the vast and varied content of the 2002 conferences. Proceedings of AAAI-02 and IAAI-02 are available from AAAI Press (www.aaaipress.org). AAAI is grateful for the outstanding work of the conference committee members as well the support of the following organizations for this year's conference: Association of Computing Machinery SIGART, Alberta Informatics Circle of Research Excellence (iCORE), Defense Advanced Research Projects Agency (DARPA), NASA Ames Research Center, the National Science Foundation's Directorate for Computer and Information Science and Engineering (CISE), and the Naval Research Laboratory.

This article is a summary of the Workshop on Explanation held during the 1988 National Conference on Artificial Intelligence in St. Paul, Minnesota. The purpose of the workshop was to identify key research issues in the rapidly emerging area of expert system explanation. Expert system explanation is the study of how to give an expert system the ability to provide an explanation of its actions and conclusions to a variety of users (including the domain expert, knowledge engineer, and end user). The 1988 AAAI Workshop on Explanation brought together many of the world's experts on expert system explanation in an attempt to highlight key research areas and questions that should be the focus of subsequent work. The one-day workshop was organized into five sessions of short presentations, each followed by panelled open discussion among the 35 workshop participants.

"Over the last decade a new technology has begun to take hold in... business, one so new that its significance is still difficult to evaluate. While many aspects of this technology are uncertain, it seems clear that it will move into the managerial scene rapidly, with definite and far reaching impact on managerial 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.

In reviewing a book of this kind, it is necessary to answer three questions: (1) how important is the workshop topic, (2) how valuable are the included papers, and (3) how coherent is the volume as a whole? I address each question in turn. In the last decade, knowledgebased systems (KBSs) emerged from being a research subfield within AI to become an application software technology. Although many specific aspects of knowledge acquisition, representation, and reasoning remained active research topics, the methods and tools required to build useful and powerful KBS applications had become sufficiently well understood to facilitate the development and delivery of systems in many diverse domains. However, as organizations began to use the technology, concerns arose about the reliability of KBSs.

Johanna Moore's work in the area of computer-generated explanation has been highly influential. Her thesis work, as well as the subsequent work of her and her students, has helped to change the way we think about the problem of generating explanations. The crux of the explanation problem, according to Moore, is not how to present information as such but how to impart an understanding on the user. The explanation system should be flexible enough that if an initial explanation fails to convey the understanding, it can try explaining the concept in a different way. The system should be aware of what it previously said to the user and what its communicative goals were at the time.

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. The set is the result of a call for papers to support the first American Association for Artificial Intelligence Knowledge Acquisition for Knowledge-Based Systems Workshop, held 3-7 November 1986 in Banff, Canada. Although the conference was held three years ago, these volumes are still timely and sorely needed. Few books dedicated to knowledge acquisition exist. The first volume, Knowledge Acquisition for Knowledge-Based Systems, begins with a paper whose title sounds appropriate: "An Overview of Knowledge Acquisition and Transfer" by the editor B. R. Gaines.