Here,onelineof the literature proposes to train a binary classifier using the human-written texts and LGTs [20,6].

By virtue of their medical training, doctors have a wealth of knowledge, experience, wisdom and judgment. Yet even the greatest of human brains can't remember or interpret a tiny fraction of the information now available on human health and disease. Just a few years ago, most medical decisions were based entirely on the knowledge in the head of the doctor at the time the decision was made. Today that is beginning to change, thanks to the rapid development of artificial intelligence.

This article is a review of Thinking about Android Epistemology by Kenneth Ford, Patrick Hayes, and Clark Glymour. The result of colliding beams of gold traveling near the speed of light ("minibangs") allows physicists to observe the liberation of quarks and gluons from protons and neutrons, revealing conditions that existed at the earliest moments of creation of the universe, thus validating current theories of how the original mix of quarks and gluons phase-transitioned into the mundane soup of protons and neutrons that forms the building blocks of everything. Theoretical and experimental breakthroughs since the 1970s, as well as technological advances in the art of colliding and detecting particles, have made it possible to observe a new "energy frontier," with a wealth of results that will allow a refinement of our theories. The question of the validity of the results obtained is a completely empirical matter. No one would seriously entertain the claim that the results obtained from RHIC are invalid because the results were obtained in an artificially induced laboratory setting rather than as the result of direct observation of nature.

IAAI seeks out applications of artificial intelligence that either demonstrate new technology or use previously known technology in innovative ways. IAAI particularly seeks out examples of deployments of AI technology that tackle the problems of demonstrating value and planning for long-term deployment. The five articles we have selected for this special issue are extended versions of papers that appeared in the conference. Two of the articles are deployed applications that have already demonstrated practical value. The remaining three articles are particularly innovative emerging applications.

It was written not by a human being, but by my computer program EWI (an acronym for "experiments in writing intelligence"). EWI was fed the texts of two of Hofstadter's books--namely, Gödel, Escher, Bach (winner of the Pulitzer Prize for General Nonfiction in 1980) and Metamagical Themas--and then, following its code, EWI carefully analyzed these two books for their uniquely Hofstadterian stylistic elements and features, after which it recombined these stylistic elements in new fashions. EWI thereby came up with some 25 new and highly diverse "Hofstadter articles," one of which is given below, and the article is followed by a brief commentary about EWI and its output by Hofstadter himself. Actually, I should state up front that the wonderful sparkling dialogues of GEB, which are a substantial part of that book, were not used by EWI in generating any of the articles, because EWI is unfortunately not yet able to work with inputs that belong to different genres, such as chapters and dialogues. To combine stylistic aspects of two or more different genres of writing represents a very thorny challenge indeed.

In this article, we describe a deployed educational technology application: the Criterion Online Essay Evaluation Service, a web-based system that provides automated scoring and evaluation of student essays. Criterion has two complementary applications: (1) Critique Writing Analysis Tools, a suite of programs that detect errors in grammar, usage, and mechanics, that identify discourse elements in the essay, and that recognize potentially undesirable elements of style, and (2) e-rater version 2.0, an automated essay scoring system. Critique and e-rater provide students with feedback that is specific to their writing in order to help them improve their writing skills and is intended to be used under the instruction of a classroom teacher. Both applications employ natural language processing and machine learning techniques. All of these capabilities outperform baseline algorithms, and some of the tools agree with human judges in their evaluations as often as two judges agree with each other. Unfortunately, this puts an enormous load on the classroom teacher, who is faced with reading and providing feedback for perhaps 30 essays or more every time a topic is assigned. As a result, teachers are not able to give writing assignments as often as they would wish. With this in mind, researchers have sought to develop applications that automate essay scoring and evaluation. Work in automated essay scoring began in the early 1960s and has been extremely productive (Page 1966; Burstein et al. 1998; Foltz, Kintsch, and Landauer 1998; Larkey 1998; Rudner 2002; Elliott 2003). Detailed descriptions of most of these systems appear in Shermis and Burstein (2003). Pioneering work in the related area of automated feedback was initiated in the 1980s with the Writer's Workbench (MacDonald et al. 1982). The Criterion Online Essay Evaluation Service combines automated essay scoring and diagnostic feedback. The feedback is specific to the student's essay and is based on the kinds of evaluations that teachers typically provide when grading a student's writing. Criterion is intended to be an aid, not a replacement, for classroom instruction. Its purpose is to ease the instructor's load, thereby enabling the instructor to give students more practice writing essays. Criterion contains two complementary applications that are based on natural language processing (NLP) methods. Critique is an application that is comprised of a suite of programs that evaluate and provide feedback for errors in grammar, usage, and mechanics, that identify the essay's discourse structure, and that recognize potentially undesirable stylistic features. The companion scoring application, e-rater version 2.0, extracts linguistically-based features from an essay and uses a statistical model of how these features are related to overall writing quality to assign a holistic score to the essay. Figure 1 shows Criterion's interface for submit-

The question of whether a computer can think like a person is once again a hot topic. Somewhat to my surprise, this philosophical question seems to have direct practical implications for AI, especially language understanding. The following analysis has been helpful to me and might be of some value to others. When we use words such as think, understand, and wish, we typically refer to the human experience of these activities. When I want to emphasize this point, I use the notation x/h for human.

"Nearly 10 years ago, the Department of Commerce issued a technology assessment of the U.S. artificial intelligence (AI) market.... The report estimated the 1993 global AI market - including technologies such as expert systems, neural networks, fuzzy logic, robotics, speech recognition, search, etc. - at about $900 million.... What a difference a decade makes…. In April, Business Communication Company (BCC) will release a thorough new study of the worldwide artificial intelligence market, which it predicts will reach more than $21 billion by 2007 with an average annual growth rate from 2002 to 2007 of 12.2%. In 2002 alone, BCC calculates the worldwide market was $11.9 billion…." Fledgling Robot Industry Aims to Fly High.