A New Life for AI Artifacts
Deepak Kumar
Department of Mathematics & Computer Science
Bryn Mawr College Bryn Mawr, PA 19010

Curriculum Descant
From ACM Intelligence Magazine
Volume 10, Number 2, Summer 1999
ACM Press


We live in times when funding for basic research, especially research on artificial intelligence (AI). also includes an evaluation or deliverable component. This is especially true for funding that supports AI research. In most cases, the deliverable is a demonstration, a proof of concept, or an implementation of a prototype. Generally relegated to use within research labs/groups and reporting of results in various symposia, such artifacts tend to live a minimal existence. Some artifacts barely make it to the final demo. Several artifacts are being constantly used and serve as platforms for further research. Some of them have been in existence now for several years and have undergone enhancements, rewrites, and even complete re-implementations.

I want to bring to your attention the artifacts that you or your colleagues may have created and are used in your research labs. I would like to appeal to you to bring these artifacts into your classrooms. Incorporate them into your lab assignments and have your AI students get some experience with them.

AI artifacts that exist in research labs can serve as excellent tools to help bring research into the classroom. They can be used in various ways: as demos that show off the state of the art, as working artifacts of theories discussed in texts, as laboratory exercises where students learn to use them, as case studies for studying concepts, as platforms for developing other AI artifacts. All together, a rich set of pedagogical devices can be available to enhance students' experience with AI.

My proposal is not necessarily novel. Most instructors use some AI artifacts in one way or another. My appeal here is to focus energies into extending the boundaries of use of these artifacts. If you or your research group has produced an AI artifact, it would be worthwhile examining its use in the classroom. For example, is it something you can share with undergraduate students? With graduate students? In what form? Can you give a demo during a lecture? Would a short video clip suffice? Could the students operate it themselves? What types of lab assignment would highlight the main features of the artifact? Could it be used for students to do development work?

The use of Ai artifacts in the classroom requires planning and effort at different levels. The primary responsibility rests with the creators. First, they have to try to answer some of the preceding questions in order to help create appropriate pedagigical materials. Next, the materials can be tested in their own courses and then to disseminated for others to use.

Currently, most of the burden of developing such materials rests on authors of AI texts. Authors feel obliged to provide artifacts specifically designed for use with their texts. This works, at times, but it essentially eliminates the in situ nature of artifacts that emerge from research labs. The emphasis should also be on "doing AI" as done by others in the field. Besides, using artifacts also creates a fertile pipeline of well-trained individuals who will be able to contribute to the field in the future.

At a recent AAAI symposium, researchers lamented their own lack of training in certain new areas into which their research was leading. Some people complained about not having sufficiently trained students who could participate in some of their research projects. An audience survey revealed that a very small percentage of them were using any of their research tools or artifacts in their classes and agreed that incorporating more of tools and artifacts would certainly alleviate some of the concerns about student preparedness.

I would like to invite readers to send me short descriptions of AI artifacts that have been successfully used as teaching materials in AI courses. Entries submitted should be such that others will also be able to use the artifacts in their own courses. I will collect and present them as a resource in a future issue of this magazine. If you are willing to write a longer, more detailed tutorial or presentation, please contact me to discuss the details.


Fall 1997
Inaugural Installment of the new column.
(Deepak Kumar)

Summer 1998
Teaching about Embedded Agents
Using small robots in AI Courses
(Deepak Kumar)

Fall 1998
Robot Competitions as Class Projects
A report of the 1998 AAAI Robot Competition and how robot competitions have been successfully incorporated in the curriculum at Swarthmore College and The University of Arkansas
Lisa Meeden & Doug Blank)

Winter 1998
Nilsson's New Synthesis
A review of Nils Nilsson's new AI textbook
(Deepak Kumar)

Spring 1999
Pedagogical Dimensions of Game Playing
The role of a game playing programming exercise in an AI course
(Deepak Kumar)

Summer 1999
A New Life for AI Artifacts
A call for the use of AI research software in AI courses
(Deepak Kumar)

Fall 1999
Beyond Introductory AI
The possibility of advanced AI courses in the undergraduate curriculum
(Deepak Kumar)

January 2000
The AI Education Repository
A look back at AAAI's Fall 1994 Symposium on Improving the Instruction of Introductory AI and the resulting educational repository
(Deepak Kumar)

Spring 2000
Interdisciplinary AI
A challenge to AI instructors for designing a truly interdisciplinary AI course
(Richard Wyatt)

Summer 2000
Teaching "New AI"
Authors of a new text (and a new take) on AI present their case
(Rolf Pfeifer)

Fall 2000
Ethical and Social Implications of AI: Stories and Plays
Descriptions of thought provoking stories and plays that raise ethical and social issues concerning the use of AI
(Richard Epstein)

January 2001
How much programming? What kind?
A discussion on the kinds of programming exercises in AI courses
(Deepak Kumar)

Spring 2001
Predisciplinary AI
A follow-up to Richard Wyatt's column (above) and a proposal for a freshman-level course on AI
(Deepak Kumar)

Spring 2001
Machine Learning for the Masses
Machine Learning comes of age in undergraduate AI courses
(Clare Congdon)

About Curriculum Descant
Curriculum Descant has been a regular column in ACM's Intelligence magazine (formerly published as ACM SIGART's Bulletin). The column is edited by Deepak Kumar. The column features short essays on any topic relating to the teaching of AI from any one willing to contribute. If you would like to contribute an essay, please contact Deepak Kumar.