Lawrence L. Schkade

Complex document search for decision making

Abstract Professionals are often faced with ill-structured and complex decision situations, and they must make choices on the basis of limited information and problem clarity. These decisions are especially difficult when extensive document search is required. Thus, decision makers often satisfice rather than select an optimal alternative. The research reported here applies a cascading index, logical views, hypertext, notation capability, and case-based reasoning to a conceptual design and the prototyping of an electronic retrieval document system (ERDS) that may serve as a valuable tool for decision makers faced with an ill-structured problem and the task of extensive searching. The ERDS prototype was applied to the problem domain of public accounting professional conduct. It was developed using a portion of the AICPA Professional Standards , which served as the electronic document text. The text was linked by hypertext to real and prototypical cases. A panel of industry experts validated the prototype. The results of analysis and evaluation produced ideas for the extension and wider application of the system.

Designing artificial intelligence applications in law: A systemic view

Artificial intelligence applications development in law has historically focused on formal legal reasoning. Most of the systems are rule-based and none has yet become a fully functional prototype or commercially viable. The attempts to build large-scale systems without examining the intrinsic systemic nature of the legal process has resulted in limited operational success. The legal function, another area of legal activity, has emerged rapidly offering potential for artificial intelligence-based applications. This paper discusses the systemic differences between legal reasoning and legal function and suggests that different design methodologies be used in the two domains. Legal reasoning requires a holistic approach such as the blackboard model incorporating the properties of softness, openness, complexity, flexibility, and generality of legal systems, while traditional rule-based approaches are sufficient for legal function applications.

Legal Expert Systems Design: The Blackboard Model

Expert systems applications development in legal decision making has traditionally focused on the use of rule-based models. None of the systems has yet become a fully functional prototype or commercially viable. The attempts to design legal decision making systems without examining the intrinsic complex nature of the legal process has resulted in limited operational success. This paper discusses legal decision making, legal function and the differences between rulebased blackboard models. It is recommended that the blackboard model be used in the design of legal decision making systems while the rule-based will continue to be appropriate for the legal function applications. The use of more sophisticated models such as the blackboard will enable the scaling up of expert systems technology to more encompassing domains.

INFORMATION AUTOMATION, HUMAN SERVICE DELIVERY, AND QUALITY OF LIFE

ABSTRACT Analysis of historical trends in human service delivery and information automation technology are combined to project future patterns of delivery and suggest ways to maximize quality of life. Changes in the human service delivery system and its environment that will impact quality of life are increases in elaboration and differentiation, definition and specification, and accountability and responsibility. Recommended actions for insuring that these changes improve quality of life include: reduce conflict caused by service demands that exceed resources; develop a policy decision infrastructure to increase use of system information; integrate information technology throughout the organization; develop decision support systems for direct service workers; and expand consumer monitoring of service delivery.