Those of us engaged in artificial intelligence research have the historically unique privilege of asking and answering the most profound scientific and engineering questions that people have ever set for themselves--questions about the nature of those processes that separate us humans from the rest of the universe--namely intelligence, reason, perception, self-awareness, and language. It is clear--to most of us in AI, at least--that our field, perhaps together with molecular genetics, will be society's predominant scientific endeavor for the rest of this century and well into the next...

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.

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.

This article provides a personal perspective, in three stories, on the origins of AAAI. In the first story, I explain the reasons justifying AAAI's existence. In the second story. In the second story, I recount some of the controvery over the name artificial intelligence, and explain why it was chosen as the new society's moniker. In the third story, I note that AI has not suffered from the applied versus research scism that has affected other societies. Finally, in the fourth story, I mention some of the early issues of finance.

Fortunate to be one of the cofounders of AAAI, the author describes how the association was founded, how the first AAAI conference was planned, and how the first tutorial program was organized. I had been hired by Raj and Allen Newell to play a lead role on the Hearsay-II speech understanding project in 1976. After that, I moved to Rand Corporation and, shortly thereafter, took over the leadership of the research program in information processing systems, where the focus was on AI tools and applications and cognitive science. It was in that context that Raj spoke to me about his conviction that it was time for AI to become a recognized scientific profession, much as the AAAS and IEEE had done for natural science and engineering, respectively. This conversation was an example of Raj's modus operandi, the gap between vision and current state translated simply into gap-reducing actions.

This article reprints a section of the January 1980 "Chairman's Message" of the SIGART Newsletter (No. 69). SIGART is the Special Interest Group on Artificial Intelligence, of the Association for Computing Machinery. At the time of AAAI's formation, SIGART, with its 3,800 members, was the principal AI organization in the United States, and its primary activity was publishing the "Newsletter.

This article provides a historical background on the origins of AAAI, recounting some of the issues discussed and requirements to be fulfilled by the new society. It provides a personal reminiscence of some of the persons who founded the association, including Raj Reddy, Donald Walker, and Woody Bledsoe, and also recounts some of my experiences as secretarytreasurer and later president of AAAI. In 1979 he was the general chair for IJCAI-79, and I was the program chair, so we were already working closely together and thinking about organization. We were not alone in being frustrated by the phoenix-like nature of IJCAI--springing to life before every biannual conference, then dying, with little continuity. Also, it was obvious that volunteers from academe and industry had numerous distractions and other obligations besides IJCAI, so important deadlines could easily be missed.

It highlights the many voices contributing to AAAI by featuring personal remembrances and visions from many people, including founders of AAAI, presidents who guided the society's development, and others spurring on AI research and applications. While a single issue can only scratch the surface, this special issue clearly illustrates the spirit, accomplishment, and optimism that will drive the next 25 years. It is fitting for AI Magazine to present such a commemoration: 2005 is the twenty-fifth anniversary of the magazine as well. From the beginning, AI Magazine has brought the AI community together to share ideas and advances and to introduce newcomers to the challenges and accomplishments of the field. With circulation that is roughly one quarter international, the magazine serves a worldwide audience.

By the early 1960s there were several active research groups in AI, including those at Carnegie Mellon University (CMU), the Massachusetts Institute of Technology (MIT), Stanford University, Stanford Research Institute (later SRI International), and a little later the University of Southern California Information Sciences Institute (USC-ISI). My own involvement in AI began in 1963, when I joined Stanford as a graduate student working with John McCarthy. After completing my Ph.D. in 1966, I joined the faculty at Stanford as an assistant professor and stayed there until 1969 when I left to join Allen Newell and Herb Simon at Carnegie Mellon University

Just as email traffic has increased over the years since its in ception, so has the proportion that is unsolicited; some estimations have plac ed the proportion as high as 60%, and the average cost of this to business at arou nd $2000 per year, per employee (see [29] for a range of numbers and statis tics on spam). Unsolicited emails - commonly know as spam - have thereby become a daily feature of every email user's inbox; and regardless of advan ces in email filtering, spam continues to be a problem in a similar way to comp uter viruses which constantly reemerge in new guises. This leaves the res earch community with the task of continually investigating new approac hes to sorting the welcome emails (known as ham) from the unwelcome spam. W e present just such an approach to email classification and fi ltering based on a well studied data structure, the suffix tree (see [1 6] for a brief introduction). The approach is similar to many existing one s, in that it uses training examples to construct a model or profile of the class and its features, then uses this to make decisions as to the class of new example s; but it differs in the depth and extent of the anaysis. For a good overview of a number of text classification methods, see [26, 1, 31]. Using a suffix tree, we are able to compare not only single word s, as in most current approaches, but substrings of an arbitrary len gth.