AI and AAAI are coevolving. As AI matures, its focus is shifting from inward-looking to outwardlooking. Some of the new concerns of the field are social awareness, networking, cross-disciplinarity, globalization, and open access. AAAI must reflect and support those concerns. AI is now a mature discipline.

I systems, the importance of controlling the had previously worked in cybernetics, data acquisition, and introduced an new control theory, and pattern recognition, paradigm: active perception. We stated that where we modeled intelligence, perception, we not just see but we also look, and we and action as signal processing.

The emerging Semantic Web focuses on bringing knowledge representationlike capabilities to Web applications in a Web-friendly way. The ability to put knowledge on the Web, share it, and reuse it through standard Web mechanisms provides new and interesting challenges to artificial intelligence. In this paper, I explore the similarities and differences between the Semantic Web and traditional AI knowledge representation systems, and see if I can validate the analogy "The Semantic Web is to KR as the Web is to hypertext."

What Do We Know about Knowledge? In this article, I will examine the first of these questions. AI has been slow to embrace this principle. Programs demonstrating research ideas in AI are often too large and not well enough documented to allow replication or sharing. What I would like to in diverse conditions. I wish to clarify the knowledge example, it was pretty clearly articulated in Biblical principle and try to increase our understanding times: "A man of knowledge increaseth of what programmers and program strength" (Proverbs 24: 5). Greek philosophers based their lives on acquiring The "knowledge is power" principle is most and transferring knowledge. In the course closely associated with Francis Bacon, from his of teaching, they sought to understand the 1597 tract on heresies: "Nam et ipsa scientia nature of knowledge and how we can establish potestas est." ("In and of itself, knowledge is knowledge of the natural world. B," along with quantification, "All A's are B's," Euclid's geometry firmly established the concept In the intervening several centuries before Plato, Socrates's pupil and Aristotle's mentor, was the first to pose the question in writing of the Middle Ages and the rise of modern science what we mean when we say that a person in the West, He was distinguishing empirical knowledge, church to make new knowledge fit with established lacking complete certainty, from the certain dogma.

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.

For more information on the BS in CS program, see Philip Flora, 1981 Rina Dechter, 2002 http://www.csd.cs.cmu.edu/education/bscs/index.html.

In this first message to the members of AAAI, AAAI President Allen Newell answers the questions "what are we?" "why did we come into existence?" "how will AAAI conduct itself?" and ends with a few thoughts on the name "artificial intelligence." According shock to come from the womb to the world. The birth we give witness to here is that of a new society, the American Association for Artificial Intelligence--AAAI. It has not seemed to me traumatic, but rather almost wholly benign. In a world where not much is benign at the moment, such an event is devoutly to be cherished.

The 1993-95 period presented various "identity challenges" to the field of AI and to AAAI as a leading scientific society for the field. The euphoric days of the mid-1980s AI boom were over, various expectations of those times had not been met, and there was continuing concern about an AI "winter." The major challenge of these years was to chart a path for AI, designed and endorsed by the broadest spectrum of AI researchers, that built on past progress, explained AI's capacity for addressing fundamentally important intellectual problems and realistically predicted its potential to contribute to technological challenges of the coming decade. This reflection piece considers these challenges and the ways in which AAAI helped the field to move forward. Adolescence, the twenties, and the forties each bring particular "developmental" challenges to people, and, though surely coincidentally, elements of those life stages seem also to characterize the period of my presidency.

The long-term goal of AI is human-level AI. This is still not directly definable, although we still know of human abilities that even the the best present programs on the fastest computers have not been able to emulate, such as playing master-level go and learning science from the Internet. Basic researchers in AI should measure their work as to the extent to which it advances this goal.

AAAI has seen great ups and downs, based largely on the perceived success of AI in business applications. Great early success allowed AAAI to weather the "AI winter" to enjoy the current "thaw." Other challenges to AAAI have resulted from its success in spinning out international conferences, thereby effectively removing several key AI areas from the AAAI National Conference. AAAI leadership continues to look for ways to deal with these challenges. AAI began life intending to be completely societies (such as ACM).