For many years, the very idea of artificial intelligence has been provocative and exciting. However, with a continually increasing focus on specialized subareas and somewhat narrow technical problems (both of which are inevitable and in many ways healthy), we may be torpedoing our core research agenda: the creation of a true synthetic intelligence. I reflect briefly on the essential interdependencies of the components of intelligence, the important roles of architecture and integration, and the need to get back to thinking about the very idea of AI. AAAI's role in the field has evolved over the years, but after a quarter-century as an organization, and a half-century as a field, it seems like AAAI is in an ideal situation to bring AI as a whole back to its roots. In 1985, the philosopher John Haugeland wrote a thoughtprovoking treatise on AI that he titled Artificial Intelligence: The Very Idea.

The Workshop on Future Directions in NLP was held at Bolt Beranek and Newman, Inc. (BBN), in Cambridge, Massachusetts, from 29 November to 1 December 1989. The workshop was organized and hosted by Madeleine Bates and Ralph Weischedel of the BBN Speech and Natural Language Department and sponsored by BBN's Science Development Program. Thirty-six leading researchers and government representatives gathered to discuss the direction of the field of natural language processing (NLP) over the next 5 to 10 years. The intent of the symposium was "to make the conference and resulting volume an intellectual landmark for the field of NLP." This brief article summarizes the invited papers and strategic planning discussions of the workshop.

The Full-Sized Knowledge-Based Systems Research Workshop was held May 7-8, 1990 in Washington, D.C., as part of the AI Systems in Government Conference sponsored by IEEE Computer Society, Mitre Corporation and George Washington University in cooperation with AAAI. The goal of the workshop was to convene an international group of researchers and practitioners to share insights into the problems of building and deploying Full-Sized Knowledge Based Systems (FSKBSs). The term "full-sized" was chosen to encourage discussion of questions not only of largeness but also of breadth, depth, maturity, and deployment scale. For example, a 1000-rule expert system facilitating knowledge sharing and collaboration between several thousand users was felt to be as interesting to the workshop as a 100,000-rule system with only a few users. That notwithstanding, the underlying question was how to overcome the brittleness and narrowness of the first generation of expert systems, and how to use a variety of new ideas and technologies to increase the scale, intelligence, and capability of the systems currently able to be fielded.

Originally founded in 1987 as a conference to promote and advance AI within the state of Florida, over the years, FLAIRS has attracted national and international participation--56 percent of this year's papers had international authors. After a period of eight years, the Fifteenth International Conference of the Florida Artificial Intelligence Research Society (FLAIRS 2002) returned to the emerald coast of Pensacola Beach, Florida. John Kolen (UWF-IHMC) was the conference general chair, and Susan Haller (University of Wisconsin at Parkside) and Gene Simmons (University of South Alabama) were the program cochairs. FLAIRS is a general conference for reporting AI research, and the 104 papers presented at FLAIRS-2002 covered a broad spectrum of research areas. The conference consisted of 3 parallel sessions of 21 tracks, including 14 special tracks highlighting specific themes.

A key data source available to FINCEN is reports of large cash transactions made to the Treasury according to terms of the Bank Secrecy Act. FAIS's unique analytic power arises primarily The most common motivation for criminal behavior is profit. The larger the criminal organization is, the greater the profit. By disrupting the ability to profit, law enforcement can focus on a vulnerable aspect of large criminal organizations. Money laundering is a complex process of placing the profit, usually cash, from illicit activity into the legitimate financial system, with the intent of obscuring the source, ownership, or use of the funds.

During the past year, a prototype expert system for tactical data fusion has been under development This compute1 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 rule 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 useI interactions IN THE MODERN MILITARY ENVIRONMENT, Multiple sensor inputs need to be interpreted in a timely manner to assess developing battlefield conditions. The high volume of data from such sensor systems, as well as their high rate of data transfer, make this timely interpretation difficult and very demanding of human resources. THE AI MAGAZINE Summer 1984 37 is inherently probabilistic as well as time varying and nonmonotonic. The fusion process can also require numerical analysis to be done on the raw sensor data. This "number crunching" analysis is best done (and is currently being done) with languages such as This form of representation is very general, offering good future growth potential for the system.

Editors' Note: In this provocative article Doyle suggests that I thank Jaime Carbonell, John McDermott, Joseph Schatz, and Derek Sleeman for helpful discussions and comments This research was supported by the Defense Advanced Research Projects Agency (DOD), ARPA Order No. 3597, monitored by the Air Force Avionics Laboratory under Contract F33615-81-K-1539. The views and conclusions contained in this document are those of the author, and should not be interpreted as representing the official policies, either expressed or implied, of the Defense Advanced Research Projects Agency or the Government of the United States of America Abstract, Knowledge engineers qualified to build expert systems are currently in short supply The production of useful and trustworthy cxpcrt systems can he significantly increased by pursuing the idea of nrCiculate ayprentzce.ship This revolution is very important. We now actively seek out tasks for automation that would never have been considered previously. It seems clear that the work of our society and industry includes many economically important (if often mundane) tasks whose automation may be possible with the new techniques.

Artificial Intelligence is solving more and more real world problems, but penetration into the complexities of government administration has been minimal. The author suggests that combining expert system technology with conventional procedural computer systems can lead to substantial efficiencies. Business rules can be removed from business-oriented computer systems and stored in a separate but integrated knowledge base, where maintenance will be centralized. Fourteen specific practical applications are suggested. Traditionally, these systems have been used to automate the accounting function, automate labor-intensive activities, manage and control vast financial and physical assets, process payrolls for hundreds of thousands of employees, and merge and summarize information about a wide set of activities in support of management decision making.

Human error is an increasingly important and addressable concern in modernday high-technology accidents. Avoidable human errors led to many famous accidents, including Bhopal, the space shuttle Challenger, Chernobyl, the Exxon Valdez, and Three Mile Island. Many hundreds of thousands of nonfamous accidents occur each year that are equally or more avoidable. Dramatic examples make the local headlines, such as car crashes, train and plane wrecks, and military-related operations mishaps. Less dramatic consequences happen even more frequently because of millions of mundane errors that appear daily in the products we use (for example, poorly designed cars), the processes we are affected by (for example, banking or healthcare institutions), and the automation that surrounds us (for example, unfriendly computers that expect us to adapt to their interfaces).

As in past years, papers were solicited in two categories: (1) deployed applications and (2) emerging applications and technologies. Deployed applications are systems that have been in use for at least several months by individuals or organizations other than their developers, have measurable benefits, and incorporate AI technologies. Emerging applications are technologies and systems that are close to deployment and clearly show an innovative implementation of AI technologies. All these case studies are of value not only to other application developers looking for guidance in applying various techniques to their own applications but also to researchers who need to understand the myriad of technical challenges provided by real-world problems. At IAAI-2001, five deployed applications and seven emerging application papers were presented.