Syllabus: Seminar on Artificial Intelligence and Law
August 29, 2002

Time and Place: Fall Semester, 2002: Thursdays & Fridays, 10:00 - 11:30 AM, Law Bldg 121

Professor: Kevin D. Ashley

Law Bldg, 3900 Forbes Ave., Room 525, 648-1495
Learning Research and Development Center, 3939 O'Hara St., Room 519, 624-7496

ashley@pitt.edu

Materials: One volume of readings available through KopyKat.

Evaluation and Requirements:

The two major requirements are a seminar paper and classroom participation.
Seminar papers:  A nonexhaustive listing of possible paper topics may be found at http://www.lrdc.pitt.edu/ashley/sampletopics.htm. Students should contact Prof. Ashley early in the term to discuss appropriate paper topics. This is especially true for those who intend the paper to satisfy their law school writing requirement. A typical paper topic for a law student might involve the student’s attempting to model how a lawyer reasons about an interesting legal issue or task using one or more of the AI techniques discussed in the seminar. Such a paper would identify the information necessary to reason about the issue or perform the task, describe a scheme for representing the information and a mechanism for applying it to solve problems, work through examples manually illustrating how the mechanism works, and discuss the difficulties encountered and assumptions made. Graduate students are invited to propose paper topics connecting the seminar material to their own interests in AI.

For students planning to take the Practicum in Artificial Intelligence and Law in spring, 2003, the seminar paper may serve as a preparation for the student's project.

Classroom Participation: Students will also be evaluated on the basis of class participation. In order to stimulate classroom discussion and foster understanding of the readings, students also will be asked to participate in a “rotisserie” program, a kind of software-supported peer feedback, in which the program distributes assignments to students to prepare short (1 page) critiques of readings, and then, after everyone has submitted her answer, randomly distributes these answers to different classmates for comment (and sometimes to participating authors of the readings). Prof. Ashley may assign individual students responsibility for being prepared to discuss individual readings.

Rotisserie Program: http://kingston.cs.pitt.edu:8080/Rotisserie


Schedule of Topics and Readings:

I. Introduction to AI & Law

Date: August 29, 30
Take-home exercise.

Read: "The Semantic Web", Tim Berners-Lee, et al., Scientific American, May 17, 2001

II. Overview of AI and Law Research
Date: September 5, 6

Powerpoint presentation by Prof. Ashley

III. What is Legal Reasoning? What is AI?
Date: September 12, 13
IV. Legal Production Rule Systems and Logical Representations of Statutes
Date: September 19, 20
V. Problems with Logical Representations of Statutes
Date: September 26, 27
VI. Identifying Legal Issues
Dates: October 3, 4
VII. Representing Legal Concepts
Dates: October 10, 11
VIII. Arguing with Cases and Hypotheticals
Dates: October 17, 18
IX. Structured Legal Analogies
Date: October 24, 25
X. Integrating Cases, Statutes, and Rules
Date: October 31, November 1
XI. Teleology; Case Interpretation & Intelligent Tutoring with Cases
Date: November 7, 8
XII. Text Retrieval
Dates: November 14, 15
X. Helping Judges: Document Drafting, Decision Making, Sentencing
Dates: November 21, 22
XIII. Hybrids, Hypertext and Beyond
Dates: December 5, 6