This article surveys a portion of the field of natural language processing. The main areas considered are those dealing with representation schemes, particularly work on physical object representation, and generalization processes driven by natural language understanding. The emphasis of this article is on conceptual representation of objects based on the semantic interpretation of natural language input. Six programs serve as case studies for guiding the course of the article. Within the framework of describing each of these programs, several other programs, ideas, and theories that are relevant to the program in focus are presented.

Subjects include AI's impact on employment, the AAAI conference, a response to McCarthy's Presidential Message, AI going public, and computerless expert systems.

It may be argued that this, in principle, is a more realistic approach because it addresses, rather than finesses, the problem of incomplete information in the knowledge base. On the other hand, the Dempster-Shafer theory provides a basis-at least at present-for only a small subset of the rules of combination which are needed for inferencing in expert systems. In particular, the theory does not address the issue of chaining, nor does it come to grips with the fuzziness of probabilities and certainty factors. Thus, although the theory is certainly a step in the right direction, for it provides a framework for dealing with granular data, it does require a great deal of further development to become a broadly useful tool for the management of uncertainty in expert systems. Although not easy to understand, Shafer's book contains a wealth of significant results, and is a must for anyone who wants to do serious research on problems relating to the rules of combination of evidence in expert systems. Indeed, there is no doubt that, in the years to come, the Dempster-Shafer theory and its extensions will become an integral part of the theory of such systems and will certainly occupy an important place in knowledge engineering and related fields.

In the past fifteen years artificial intelligence has changed from being the preoccupation of a handful of scientists to a thriving enterprise that has captured the imagination of world leaders and ordinary citizens alike. While corporate and government officials organize new projects whose potential impact is widespread, to date few people have been more affected by the transition than those already in the field. I review here some aspects of this transition, and pose some issues that it raises for AI researchers, developers, and leaders.

During the past year, a prototype expert system for tactical data fusion has been under development,. This computer program combines various messages concerning electronic intelligence (ELINT) to aid in decision making concerning enemy actions and intentions. The prototype system is written in Prolog, a language that has proved to be very powerful and easy to use for problem /rule development. The resulting prototype system (called EXPRS-Expert Prolog System) uses English-like rule constructs of Prolog code. This approach enables the system to generate answers automatically to "why" a ruled fired, and "how" that rule fired. In addition, a rule clause construct is provided which allows direct access to Prolog code routines. This paper describes the structure of the rules used and provides typical user interactions.

Artificial intelligence (AI) will have profound societal effects. It promises potential benefits (and may also pose risks) in education, defense, business, law and science. In this article we explore how AI is likely to affect employment and the distribution of income. We argue that AI will indeed reduce drastically the need of human toil. We also note that some people fear the automation of work by machines and the resulting of unemployment. Yet, since the majority of us probably would rather use our time for activities other than our present jobs, we ought thus to greet the work-eliminating consequences of AI enthusiastically. The paper discusses two reasons, one economic and one psychological, for this paradoxical apprehension. We conclude with discussion of problems of moving toward the kind of economy that will be enabled by developments in AI.

Most work in automatic programming has focused primarily on the roles of deduction and programming knowledge. However, the role played by knowledge of the task domain seems to be at least as important, both for the usability of an automatic programming system and for the feasibility of building one which works on non-trivial problems. This perspective has evolved during the course of a variety of studies over the last several years, including detailed examination of existing software for a particular domain (quantitative interpretation of oil well logs) and the implementation of an experimental automatic programming system for that domain. The importance of domain knowledge has two important implications: a primary goal of automatic programming research should be to characterize the programming process for specific domains; and a crucial issue to be addressed in these characterizations is the interaction of domain and programming knowledge during program synthesis.

The second example is of another distinguished scholar who, in a passionate contribution to the debate, stated that ... May I also take this opportunity to praise the staff Western governments, were thereby displaying a full sense of I look forward to the continuing success of the Association social responsibility, and anybody who disagreed with this in all its activities. On the surface this appears Yours sincerely, to be at least logical, until one reflects that it would not Marten E. Bennett be particularly difficult with this kind of argument to prove Gzllingham, Kent, UK that Hitler displayed a sense of social responsiblity, since one has no reason to believe that he was not sincere in believing that Jews, communists, Western capitalists and others would destroy his country if not checked. There is really not much excuse these days for anyone The background to it is the "Marietta affair." University of Cambridge, "Defended to Death," edited by movement protested on the conference site, and after some Gwyn Prins and published by Penguin Books). I came away from the meeting wondering why apparently comments.

Charles A. Rosen came to SRI in 1957. I arrived in 1961. Between these dates, Charlie organized an Applied Physics Laboratory and became interested in "learning machines" and "self-organizing systems." That interest launched a group that ultimately grew into a major world center of artificial intelligence research - a center that has endured twenty-five years of boom and bust in fashion, has "graduated" over a hundred AI research professionals, and has generated ideas and programs resulting in new products and companies as well as scientific articles, books, and this particular collection itself.

John McCarthy will prepare a proposal for A A AI to provide an online abstract service Election. Marvin Minsky announced that Woody Bledsoe for its membership. is the President-Elect for 1984-85. Mark Stefik, Stanley Rosenschein, Eugene Charniak, and Randall Davis will serve Transfer of the Presidency. Nilsson ended his term as on the Council for 1983-86.