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3.6. USER INTERFACE MANAGEMENT SYSTEMS FOR EXPERT SYSTEMS

User Interface Management Systems (UIMS) is a method that helps interface designers to cope with the ever-increasing demands on their systems. UIMS systems provide various tools to facilitate interface design and evaluation, such as action logging mechanisms, automatic code generation, maintaining consistent interface design, and supporting the complete life cycle from prototype to final application. This is accomplished by maintaining consistency within and across applications and making it easier to rapidly iterate through the implement-and-test cycle.

For expert systems, an interface designer's productivity can be greatly increased by using UIMS systems in which interface design language closely matches the expert system languages used.

3.7. WWW INTERFACES

The WWW has been a revolution on the computing scene since the early 1990s. Expert system developers realize the value to be gained by connecting their knowledge bases to the WWW interface. Such an interface improves the likelihood that the expert system can have wide accessibility.

At the simple end, an expert system simply uses text-based WWW interfaces to replace a text-based interface that would be delivered in some other more proprietary way. For instance, a lymph node expert system was developed in a class project and is accessible on the WWW (Cheng et al., 1996). At the other end, researchers are develoing virtual reality interfaces on top of the WWW that allow the user to be immersed in the environment about which the expert system is giving advice. For instance, in ship emergency handling with expert system support, a virtual reality interface supported on the WWW can be particularly valuable (Wilkins, 1996).

4. RESEARCH ISSUES

The central issue of user interfaces to expert systems arises from the fact that an expert system may play a diverse range of roles in its practical use and maintenance. At present, expert systems technology is used opportunistically by organizations mainly on an individual application basis. As a result, assimilation of this technology can be slow as there is no proper coordination. With increasing awareness of its value and benefits, more organizations are venturing into this technology; but to maximize its potential, a systemic approach must be adopted. Research in expert systems reveals that besides technical issues, there are numerous human behavioral variables pertinent to the construction of the master plan. The culture of a corporation and its present level of computerization are significant factors related to the psychological readiness of its staff members to tap into expert system technology on a more massive scale.

4.1. ACCEPTANCE

One of the key issues an expert system designer must address is the ultimate acceptance of the system by intended users. The acceptance may be affected by many factors. One reason may be simply the natural scepticism about artificial intelligence that is still seen in many application domains. For some groups of users, such as doctors, lawyers, physicists, and managers, who are traditionally recognized as experts in their own field, it is essential for them to be convinced that the underlying reasoning is valid and the knowledge has been correctly encoded. An expert system therefore must be able to explain its behavior and show the reasoning process.

The designer must take ecological issues into account, including where and when users access an expert system and how the user interface of the expert system is compatible with other interfaces in the same working environment. These factors are often overlooked.

This need for pragmatic knowledge about the environment in which the expert system will be used is repeatedly emphasized by studies on the reasons for successes or failures of expert systems in practice. For instance, in one such recent study, the main conclusion was that management needs to be convinced that the expert system will affect company productivity and individual users need to see the benefits to their job performance (Duchessi and O'Keefe, 1995). These and other similar factors are most important in determining whether or not an expert system will be accepted in the work environment.

One popular new approach to expert systems development is to incorporate intelligent agents that support collaborative work. The expert system includes a model of the collaborative work situation of those who will use the system. Where the human activity can be performed by the computer, the agent detects the opportunity and assists the people (Bose, 1996).

4.2. EFFECTIVE MEANS OF EXPLANATION

Providing explanations for recommended actions is deemed one of the most important capabilities of expert systems. There is little empirical evidence, however, that explanation facilities indeed influence user confidence in, and acceptance of, decisions and recommendations made by expert systems. Some empirical studies recently investigated the impact of explanations provided by expert systems on changes in user beliefs toward conclusions generated by expert systems.

Based on a theoretical model of argument, three alternative types of explanations, (1) trace, (2) justification, and (3) strategy, were provided in a simulated diagnostic expert system performing auditing tasks. Twenty practicing auditors evaluated the outputs of the system in a laboratory setting. The results indicate that explanation facilities can make advice from expert systems more acceptable to users and that justification is the most effective type of explanation to bring about changes in user attitudes toward the system.


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