Law
The Mind at AI: Horseless Carriage to Clock
Commentators on AI converge on two goals they believe define the field: (1) to better understand the mind by specifying computational models and (2) to construct computer systems that perform actions traditionally regarded as mental. We should recognize that AI has a third, hidden, more basic aim; that the first two goals are special cases of the third; and that the actual technical substance of AI concerns only this more basic aim. This third aim is to establish new computation-based representational media, media in which human intellect can come to express itself with different clarity and force. This article articulates this proposal by showing how the intellectual activity we label AI can be likened in revealing ways to each of five familiar technologies.
Expert Systems in Government Administration
Artificial Intelligence is solving more and more real world problems, but penetration into the complexities of government administration has been minimal. The author suggests that combining expert system technology with conventional procedural computer systems can lead to substantial efficiencies. Business rules can be removed from business-oriented computer systems and stored in a separate but integrated knowledge base, where maintenance will be centralized. Fourteen specific practical applications are suggested.
Contributors
James Peters, coauthor of "A Knowledge-Based Model of Audit Risk," is an assistant professor in the Department of Accounting, College of Business Administration, University of Oregon. Glenn D. Rennels coauthor of "Prose Generation from Expert Systems: An Applied Computational Linguistics Thomas Arcidiacono, the author of the review of An Artificial Intelligence Approach, " is a research affiliate in Approach to Legal Reasoning, is affiliated with the Artificial Intelligence Laboratory, the Medical Information Sciences Program, the New York Institute of Technology, Sunburst Center 203, Central Edwina L. Rissland, author of "Artificial Intelligence and Legal Reasoning: R. Peter Bonasso, author of "An Hermann Kaindl, author of "Minimaxing: A Discussion of the Field and Assessment of What AI Can Do for Theory and Practice", is a Gardner's Book," is an associate professor Battle Management--A Report of the software engineer in the position of of Computer and Information First AAAI Workshop on AI Applications "Gruppenleiter" at Siemens AG Science at the University of Massachusetts to Battle Management" is the osterreich, Program and System Engineering at Amherst and lecturer on department head of the Artificial Since 1984, he has been a lecturer law at the Harvard Law School. Operations division, 7525 Colshire research interests include planning Drive, Mclean, VA 22102. Vasant Dhar, coauthor of "A Knowledge-Based Model of Audit Risk," is Model of Audit Risk," is Peat Marwick Professor of Accounting, Kenneth D. Forbus is an assistant professor Perry Miller, coauthor of "Prose Generation of computer science at the University from Expert Systems: An Call toU-free 800-521-3044 Or mail inquiry to: University Microfilms International. Forbus's research interests Program, Yale University include qualitative reasoning, inference School of Medicine, 333 Cedar Street, engine design, analogical reasoning P.O.
Artificial Intelligence and Legal Reasoning: A Discussion of the Field and Gardner's Book
In this article, I discuss the emerging field of artificial intelligence and legal reasoning and review the new book by Anne v.d.L. Gardner, An Artificial Intelligence Approach to Legal Reasoning, published by Bradford/MIT Press (1987, 225 pp., $22.50) as the first book in its new series on the subject.
What AI Pratitioners Should Know about the Law Part Two
This is Part 2 of a two-part article and discusses issues of tort liability and the use of computers in the courtroom. Part 1 of this article, which appeared in the Spring 1988 issue of AI Magazine, discussed steps that developers of AI systems can take to protect their efforts, and the attendant legal ambiguities that must eventually be addressed in order to clarify the scope of such protection. Part 2 explores the prospect of AI systems as subjects of litigation.
What AI Pratitioners Should Know about the Law Part Two
This is Part 2 of a two-part article and discusses issues of tort liability and the use of computers in the courtroom. [The legal dimensions of topics covered in this part are given comprehensive attention by the author in Tort Adjudication and the Emergence of Artificial Intelligence Software, 21 Suffolk University Law Review 623 (1987)]. Part 1 of this article, which appeared in the Spring 1988 issue of AI Magazine, discussed steps that developers of AI systems can take to protect their efforts, and the attendant legal ambiguities that must eventually be addressed in order to clarify the scope of such protection. Part 2 explores the prospect of AI systems as subjects of litigation.
Contributors
Knowledge-Based Backtracking," is a principal researcher for the Advanced Technology Center, Boeing Computer Services, P.O. Jackson Y. Read, coauthor of "Real-Time Knowledge-Based Systems," is a senior analyst and associate investigator of the independent research project on real-time knowledge-based Jack Breese, who reviewed The Principles and Applications of Decision Analysis, systems at Lockheed Artificial Intelligence is with Rockwell, 444 High Street, Palo Alto, California 94301. Preston A. Cox, coauthor of "Real-Time Knowledge-Based Systems," is a scientific programmer specialist for Lockheed's Space System Division in Sunnyvale, Patrick Saint-Dizier is chairman of California. James L. Schmidt, coauthor of "Real- " is a research computer scientist Bryan M. Kramer, author of the Time Knowledge-Based Systems," is a in the Department of Computer review of Expert Systems, is affiliated scientific programmer and associate Science, Carnegie-Mellon University, with Xerox Canada, Inc., 5650 Yonge investigator of the independent Pittsburgh, Pennsylvania 15213 Street, North York, Ontario M2M research project on real-time knowledge-based 4G7, Canada. Intelligence Center, 2710 Sand Practitioners Should Know about the Thomas J. Laffey, coauthor of "Real-Hill Road, Menlo Park, California Law," is an attorney practicing with Time Knowledge-Based Systems," is a 94025. Nutter, McClennen & Fish, One research scientist and the principal International Place, Boston, Massachusetts investigator of the independent Jeffrey Stout is on the research staff of 02210-2699. She coedited the research Victor Lesser, coauthor of "Approximate in progress, "New Mexico State University's Processing in Real-Time Problem Yorick Wilks is the director of the Computing Research Laboratory."
What AI Practitioners Should Know about the Law Part One
This is Part 1 of a two-part article. Part 2 covers tort liability and computers as expert witnesses. It will appear in the Summer 1988 issue of AI Magazine. Technological developments that remove ever-increasing numbers of cognitive tasks from human control will alter the assumptions on which current legal rules are based. These rules will have a growing impact on AI researchers and entrepreneurs as their work reaches a growing audience of beneficiaries. In order to accommodate the needs of practitioners and their recipients, courts and lawmakers will be forced to reevaluate principles whose foundations were developed well before the implications of advanced technology could have been predicted. This article attempts to identify areas of law in which the need for accommodation will be greatest and provide some insight into the process and the direction of change.