In an earlier issue of this column, (Interdisciplinary AI, ACM Intelligence, Volume 11, Number 1, 2000) Richard Wyatt wrote:

Artificial intelligence, as a course offered within computer science programmes, should be an interdisciplinary course. Stated more carefully, the correct design for an undergraduate artificial intelligence course for a computer science department is such that it should be able to be taken by any student possessing good analytic skills but lacking programming skills. The interdisciplinary nature of a well-designed artificial intelligence course is not itself a goal of the preferred course design, but is a consequence of it.

Computer science programs are not the ideal training grounds for artificial intelligence. There are of course exceptions, but in general, computer science students lack an understanding of philosophical issues, ...

In short, artificial intelligence should be an interdisciplinary course and we, as instructors, should consciously conceive of it as such. ...

If we ourselves view our undergraduate artificial intelligence courses as interdisciplinary, it will mould our course design to benefit not only our own computer science students, but also students in our colleges in general. Artificial Intelligence needs as many smart people as we can get, from computer science and elsewhere.

Furthering these ideas, and not taking away anything from his proposals about the design of an undergraduate-level AI course, in this installment, I want to propose the idea of a pre-disciplinary course on AI for the freshman class. The proposal is based on a recent trend at most colleges of requiring the freshman class to enroll in one or more courses that emphasize writing and critical thinking skills. For instance, at Bryn Mawr college, we require all our incoming students to take two such courses, designated as College Seminars. I quote from the college's prospectus about a description of these courses:

The College Seminars are discussion-oriented, reading- and writing-intensive courses for first- and second-year students. Topics (of these courses) vary from year to year, but all seminars are designed and taught by faculty from several different fields and are intended to engage broad, fundamental issues and questions. These courses have a predisciplinary rather than an interdisciplinary intent: their aim is to revisit and revitalize questions that tend to be taken as settled by existing disciplines. Course materials include books and essays but also films, material objects, social practices, scientific observations and experiments.

For more information on this program, and specific course descriptions, visit the College Seminars website.

Inspired by sentiments expressed in the two pieces above, I would like to propose the creation of a pre-disciplinary writing intensive course that centers around the issues of artificial intelligence and philosophy of mind. Such a course can use a combination of materials taken from a selection of classic papers, videos of AI systems, movies (AI documentaries as well as Hollywood-style productions), and articles on AI as reported in the popular press. When team-taught by faculty from other disciplines, one quickly discovers an exciting array of readings that could be used to formulate the course content. I am also thinking of the book, HAL's Legacy: 2001's computer as dream and reality, Edited by David Stork, MIT Press 1997. Coupled with the movie, and additional related readings, I can see a fruitful freshman course on AI.

Without necessarily providing an introduction to computers and algorithms (if one wishes one can certainly do so), a pre-disciplinary course could engage students in lively discussions of what it means to be intelligent, the notions of machine intelligence, whether language has anything to do with thought, etc. Of course, it would be a challenge from getting bogged down with technical details and at the same time not fall prey to being considered "fluffy". Remember it is a pre-disciplinary freshman-level course. As AI researchers and educators we should all be up for such a task.

A pre-disciplinary course in AI can address several concerns expressed in Richard Wyatt's article, without necessarily taking anything away from the design of the upper-level introductory AI course. It also serves a nice challenge to us, who are mostly content 'staying within the discipline' for most of our academic teaching lives. Such a course is bound to create a better awareness about the discipline and perhaps even help attract students into computer science and AI. Regardless, the very process of engaging students into discussions on AI-related issues and having them write essays and critiques could make for an exciting course.