To effectively pursue ethical action, the business community must recognize that the fundamental form of human association is not the "social contract" into which persons enter as atomic individuals, making partial commitments to each other for the purpose of gaining limited common ends or of satisfying certain laws. The fundamental form of human association is rather the face to face community in which ongoing commitments are the rule and in which aspects of every individual''s experience are conditioned by the continuing (...) membership. The following discussion initiates a preliminary phase in the consideration of what constitutes ethical issues associated with the business applications of expert systems. The focus is on knowledge based expert system applications in public accounting, specifically in the audit domain. Prior research on the development and use of expert systems in auditing has focused on a limited set of ethical issues. Niebuhr''s theory of the "the responsible self" is used here to broaden the scope of what constitutes an ethical issue and provides a framework for identifying responsible action. Within this framework, an action is responsible if it takes into consideration ongoing relationships among the stakeholder groups affected. Actions prior to the development of the system along with the potential consequences for the system must be considered. The discursive requirements that provide the context and conditions necessary for implementing the proposed theoretical framework are presented and an illustration of how the responsibility ethic can be implemented in the audit expert system domain is developed. (shrink)
This article traces the connection between expert systems used as consultants in medicine and their design for instructional purposes in education. It is suggested that there are important differences between these applications. Recognizing these differences leads to the view that the development of intelligent computer-assisted instructions (ICAI) should be guided by empirical research into social/psychological consequences and by ethical inquiries into the acceptability of those consequences. Three proposals are put forward: (1) that the pedagogical role of intelligent CAI be (...) clarified, (2) that forms of intelligent CAI be developed that aim primarily at refining rather than replacing human judgements, and (3) that ICAI research and development projects contain components which address ethical and social/psychological components and which are equitably-funded, integral parts of the overall development effort. (shrink)
Expert systems have had little impact as computing artifacts. In this paper we argue that the reason for this stems from the underlying assumption of most builders of expert systems that an expert system needs to acquire information and to control the interaction between the human user and itself. We show that this assumption has serious linguistic and usability flaws which diminish the likelihood of producing socially acceptable expert systems. We propose a reversal of this paradigm, for (...) the design of expert systems, by assuming that it is the human user who needs to acquire information and to control the interaction between themselves and the system. (shrink)
For quite some time, the research in artificial intelligence has focused on expert systems, because here are to be found practical applications at the experimental stage which may soon become widespread. This focus makes more pressing the need to link the debate about the fundamental efficiency of artificial intelligence with those activities that aim at the application of specialized expert systems. In this paper, I begin by considering the stages and the development of human expertise. As a frame (...) of reference I propose a polar dialectic model of the development of human acting and thinking that explicitly deals with the interplay of calculating rationality and intuition. This suggests the use of expert systems as decision aids particularly in the field of maintenance work on the shop-floor. With regard to this case, some theses concerning the human-centred shaping of technology and work are presented. (shrink)
By studying several cases of expert systems' use, a variety of difficulties were identified as directly depending on specific characteristics of experts and their tasks. This concerns more than the questions: “May experts be replaced by machines?” or “Is experts' knowledge explicable?”. The organisational structure of their work as well as the cyclic, non-plannable way of their task performing have further relevance. The paper introduces the concept of experts' systems to deal with diversities of their expertise and complexities (...) of their work. It draws a distinction between non-monotonic problem solving, exploration, medium and modification, and argues that these modes are not reducible to yet another improved input/output strategy or dialogue style but introduce additional functions supporting the human-computer interaction according to experts' needs. In the first few sections, the paper covers the theoretical and empirical results of our research, whereas Section 4 introduces our design suggestions for experts' systems. (shrink)
The search for “usable” expert systems is leading somemedical researchers to question the appropriate role of these programs. Most current systems assume a limited role for the human user, delegating situated “decision-control” to the machine. As expert systems are only able to replace a narrow range of human intellectual functions, this leaves the programs unable to cope with the “constructivist” nature of human knowledge-use. In returning practical control to the human doctor, some researchers are abandoning focusedproblem-solving in (...) favour of supportiveproblem-analysis. Using ONCOCIN and QMR as examples, this article contrasts these approaches and suggests that the latter avoids many of the difficulties currently facing medical expert systems. (shrink)
Expert systems have been concerned with applications dealing with medical diagnosis, mineral exploration, and computer configuration, with some efforts relatively successful in achieving results at least as good as human experts. Today, much is being written about these systems and managerial decision-making activities in organizations and the positive impact that they can have in these situations. However, it appears that expert systems could become somewhat of a panacea for some organizational ailments as research, development, and marketing of (...) them continues at a fast pace. What may be forgotten in this technological thrust is the individual decision maker and his/her unique style of decision making which could affect acceptance and use of these systems. Another important consideration is the attitude people have toward computers and computer systems, which along with decision-making styles could certainly affect expert system effectiveness and ultimate success in organizations. This paper provides a discussion of potential problems that could occur regarding individual decision making and attitudes and their relationships to these systems. (shrink)
Expert systems provide new languages and a new methodology for automating knowledge-intensive processes. Whilst the benefits expected are ubiquitously stated, probable negative impacts are seldom admitted by the dominant actors in the field. We deal with probable problematic impacts on employment as well as contents and structure of work both in production and the service and administration areas and make some suggestions concerning measures to be taken to account for these impacts assuming no radical change as to the prevailing (...) ideology of working organization. (shrink)
Three case studies were conducted on the implications of the use of expert systems for the work of clerks and operators in Britain. An expert system had been introduced in a process control application. The operators' work was deskilled. The second case was a fault diagnosis application. An operator was very happy with his new work. In the third case, insurance clerks received training to operate an expert system which extended the scope of their work. In conclusion, it is (...) suggested that expert systems extend the range of work which can be automated, but may not have unique impacts. (shrink)
In this paper the difficulties arising out of a necessary examination of expert systems as to the ‘correctness’ of functioning are outlined. The argumentation is based on the problematic use of the knowledge term in expert system development and the design perspectives connected with the cognitivistic knowledge concept. It becomes obvious that fundamental problems in system development will involve negative consequences for utilization. The perspective developed from this analysis is assuming that these problems have to be taken into account (...) in development and have to be elucidated for utilization. (shrink)
Expert Systems (ES) are as yet imperfectly defined. Their two consistently cited characteristics are domain knowledge and expert-level performance. We propose that current structural definitions are inadequate and suggest a view of ES as communication channels. We proceed to explore the factors influencing applicability of ES technology to an enterprise and the impacts that could be expected. A consequence of this view is the idea of incremental information loss on the path from the expert to the ES user. Strategies (...) for minimizing this loss derive naturally from our perspective and are evident in successful ES. (shrink)
The conventional approach to developing expert systems views the domain of application as being “formally defined”. This view often leads to practical problems when expert systems are built using this approach. This paper examines the implications and problems of the formal approach to expert system design and proposes an alternative approach based on the concept of semi-formal domains. This approach, which draws on the work of socio-technical information systems, provides guidelines which can be used for the design (...) of successful expert systems. (shrink)
This paper looks beyond the mostly technical and business issues that currently inform the design of knowledge-based systems (e.g., expert systems) to point out that there is also a social and organisational (a socio-organisational) dimension to the issues affecting the design decisions of expert systems and other information technologies. It argues that whilst technical and business issues are considered before the design of Expert Systems, that socio-organisational issues determine the acceptance and long-run utility of the technology (...) after it has been implemented. It shows how four issues within the organisation can affect the design or the after-effects of the design and implementation of the technology. It also shows how the four issues can be considered within the structured phases of expert system development. (shrink)
Often, knowledge engineers become so involved in the development process of the expert system that they fail to look further down the road toward the expert system's institutionalization within the organization. Institutionalization is an important component of the expert system planning process. More specifically, the legal issues associated with expert systems development and deployment are critical institutionalization factors. This paper looks at some expert system institutionalization guidelines, and then focuses on legal considerations.
This paper examines some of the possible legal implications of the production, marketing and use of expert systems. The relevance of a legally useful definition of expert systems, comprising systems designed for use both by laymen and professionals, is related to the distinctions inherent in the legal doctrine underlying provision of goods and provision of services. The liability of the sellers and users of, and contributors to, expert systems are examined in terms of professional malpractice as (...) well as product liability. A recurring theme indicates that legislators may be inclined to restrict possibilities of liability suits in order to avoid disincentives to the creation of expert systems. (shrink)
Computer ethicists have for some years been troubled by the issue of how to assign moral responsibility for disastrous events involving erroneous information generated by expert information systems. Recently, Jeroen van den Hoven has argued that agents working with expert information systems satisfy the conditions for what he calls epistemic enslavement. Epistemically enslaved agents do not, he argues, have moral responsibility for accidents for which they bear causal responsibility. In this article, I develop two objections to van den (...) Hoven’s argument for epistemic enslavement of agents working with expert information systems. (shrink)
My goal is to emphasize the way we generally use the word âlogicâ and the sort of problems related to the definition of logic and the sort of problems related to the definition of logic. I also wish to underline the differences between human intelligence and artificial intelligence.
After the setbacks suffered in the 1970s as a result of the ‘Lighthill Report’ (Lighthill, 1973), the science of Artificial Intelligence (AI) has undergone a dramatic revival of fortunes in the 1980s. But despite the obvious enormity and complexity of the problems tackled by AI, it still remains rather parochial in relation to the import of alternative though potentially fruitful ideas from other disciplines. With this in mind, the aim of the present paper is to utilise ideas from the sociology (...) of science in order to explore some current issues in AI and, in particular, the branch of expert systems.It is argued that the sociology of sciences shares a common focus of enquiry along with AI — namely, the nature of knowledge — and has a role to play in the understanding, design and future development of expert systems. (shrink)
There is a disparity between the multitude of apparently successful expert system prototypes and the scarcity of expert systems in real everyday use. Modern tools make it deceptively easy to make reasonable prototypes, but these prototypes are seldom made subject to serious evaluation. Instead the development team confronts their product with a set of cases, and the primary evaluation criterion is the percentage of correct answers: we are faced with a “95% syndrome”. Other aspects related to the use of (...) the system are almost ignored. There is still a long way to go from a promising prototype to a final system.It is maintained in the article that a useful test must be performed by future users in a situation that is as realistic as possible. If this is not done claims of usefulness cannot be justified. It is also stated that prototyping does not make “traditional” analysis and design obsolete, although the contents of these activities will change.In order to discuss the effects of using the systems a distinction between expert systems as media, tools and experts is proposed. (shrink)
Expert systems are being developed in a multitude of domains worldwide. The usage of expert systems within organizations is growing; however, many expert systems projects still fail due to poor ‘institutionalization’ practices. This paper addresses various strategies for providing the transfer of expert systems technology within organizations. Specifically, this paper will address expert system technology transfer strategies using examples from United States and Mexican organizations.
This paper uses Perrow’s sociological framework as a basis for a comparative organisation analysis of the impact of expert systems on organisational issues. The study analyses the relative impact of expert systems on two different types of accounting work: auditing and tax. The results indicate an impact on factors that ultimately improve productivity. The aggregate results indicate that expert systems are found to allow the user substantial control of search for solutions and discretion on whether to follow (...) system recommendations, increased access to top management, and a decrease in the need for supervision. The systems allow the user the ability to solve a broader range of problems, while allowing the user the ability to perform more work. The comparison of auditing and tax expert systems indicates that audit systems seem to allow for greater control over search. Tax systems seem to allow more work to be done without supervision, make more decisions immediately, and allow the user to make a wider range of decisions. (shrink)
The consensus among legal philosophers is probably that rule-based legal expert systems leave much to be desired as aids in legal decision-making. Why? What can we do about it? A bureaucrat administering some set of complex rules will ascertain the facts and apply the rules to them in order to discover their consequences for the case in hand. This process of deductive reasoning is characteristically bureaucratic.
This paper presents a four layer model for working with legal knowledge in expert systems. It distinguishes five sources of knowledge. Four contain basic legal knowledge found in published and unpublished sources. The fifth consists of legal metaknowledge. In the model the four basic legal knowledge sources are placed at the lowest level. The metaknowledge is placed at levels above the other four knowledge sources. The assumption is that the knowledge is represented only once. The use of metaknowledge at (...) various levels should make it possible to use the appropriate knowledge for the problem presented to the system. The knowledge has to be represented as closely to the original format as possible for this purpose. Suitable representation formalisms for the various types of knowledge in the five knowledge sources are discussed. It is not possible to indicate a best representation formalism for each knowledge source. (shrink)
Los's probability semantics are used to identify the appropriate probability conditional for use in probabilistic explanations. This conditional is shown to have applications to probabilistic reasoning in expert systems. The reasoning scheme of the system MYCIN is shown to be probabilistically invalid; however, it is shown to be "close" to a probabilistically valid inference scheme.
Medical expert systems (MES) are knowledge-based computer programs that are designed for advising physicians on diagnostical and therapeutical decision-making. They use heuristic methods developed by Artificial Intelligence researchers in order to retrieve from large knowledge-bases information needed in the situation. Constructing the knowledge-base of a MES embraces the problem of explicating and fixing the conceptual, causal and epistemic relations between a lot of medical objects. There is a number of preconditions which any adequate representation of such knowledge must fulfil, (...) among them the conditions of consistency, of completeness, of unequivocality, etc. Existing systems for classification and coding, like ICD and SNOMED, are not designed for the needs of constructing expert systems or, more generally, of knowledge processing and knowledge engineering. Their syntax is not sufficiently rich for expressing the more complex structures of (medical) knowledge. What is needed, is a language that can be used for expressing logical and descriptive relations between medical objects and facts, approximately at the level of the language of second order predicate logic. Simultaneously, it must be possible to process this language at the machine level. This can be achieved by using some dialects of the programming language LISP or, particularly, by using the programming language PROLOG. Thus, in order to achieve a suitable classification system, it is necessary to develop a system of medical data structures and predicates expressed in LISP or PROLOG. (shrink)
Applications of Artificial Intelligence, particularly Expert Systems, are rapidly increasing. This science promises to give computer-based systems the capability of reasoning and decision making in near human-like fashion. Whether used for farm management or intelligent machine control, Expert Systems will find many agricultural applications. Much of the development and distribution of such systems will probably take place in the public sector, particularly the Cooperative Extension Service. A major nontechnical factor affecting the development and extensive use of (...) Expert Systems is the legal issue of products, liability, and negligence. The legal issues surrounding Expert Systems have not yet been fully tested and defined by the courts. Developers and users of Expert Systems must consider these factors for each particular application. (shrink)
Two fundamental paradigms are in conflict. Expert systems are the creation of the artificial intelligence paradigm which presumes that an objective reality can be understood and controlled by an individual expert intelligence that can be replaced by machinery. The alternative paradigm assumes that reality is the subjective product of human beings striving to collaborate through shared norms and experiences, a process that can be assisted by but never replaced by computers. The first paradigm is appropriate in the domains of (...) natural science and mathematics but dangerous in social sciencet business and, especially, the law. Expert systems are constructed on the basis of a number of metaphysical assumptions that are invalid in the legal domain. These assumptions are assimilated through a number ofcommonplace metaphors that guide the thoughts of the majority of people entering the computing field who are usually trained in first paradigm subjects such as mathematics and the natural science. This inappropriate paradigm hinders our progress in the field of computers and law. We need to adopt a socially orientated view of tbe nature of reality, of language, of meaning, of intelligence, and of reasoning. It will be easier then to build computer systems to facilitate social interactions in the legal domain and easier to understand why boxes that try to imitate legal expertise are intrinsically fraudulent. (shrink)
Dutch municipalities are confronted with an increased number of prescribed environmental tasks and also with a growing demand, both from the central government and environmental pressure groups, to undertake environmental activities on their own initiative. This development over-taxed the information management of most municipalities. In the past few years, computer technology was introduced to relieve part of this pressure (e.g., by automation of registration systems). In this article we present a classification of computer applications for environmental management, investigate their (...) possible impact on the environmental knowledge and information system, and distinguish between a formal and informal knowledge domain. Special attention will be paid to expert systems. (shrink)
Although Berman and Hafner [Berman 1989, pp. 928–938] presented the possibility to adapt the model of reasoning of development of an expert system for medical diagnosis to the reasoning of a judge when he/she sentences criminals does not resemble the reasoning found in the decisions of physicians, mathematicians or statisticians.When a lawyer reasons, he/she not only looks for the solution of a case; he/she simultaneously looks for the bases on which his/her reasoning can rest [Galindo 1992, pp. 363–367]. That is (...) to say, he/she not only needs to find the solution but moreover he/she has to find the references (laws, jurisprudence and bibliography) that allow him/her to argue the solution. (shrink)
The paper questions the expert system paradigm, both in terms of its range of application, and as a significant contribution to the understanding of artificial intelligence. The viewpoint is that of the systems designer who must judge the applicability of these methods in imminent and future systems. The expert system paradigm, (ESP for short), is criticised not because it is ubiquitously wrong, but because its range of application appears to be very limited, and much promise is made of (...) its application in areas where its success is likely to be little more than a matter of luck. The paper considers the success in both academic and commercial settings. It is suggested that the contribution of the ESP to the wider ambitions of AI is modest, and to the practical user is still a considerable and largely unquantifiable risk. (shrink)
The aim of my contribution is to try to analyse some points of similarity and difference between post-Parsonian social systems theory models for sociology — with special reference to those of W. Buckley, F.E. Emery and N. Luhmann — and expert systems models1 from Artificial Intelligence. I keep specifically to post-Parsonian systems theories within sociology because they assume some postulates and criteria derived from cybernetics and which are at the roots of AI. I refer in particular to (...) the fundamental relevance of the system-environment relationship in both sociology and AI. (shrink)
Shrinking resources and the increasing complexity of clinical decisions are stimulating research in knowledge-intensive computer applications for the delivery of social services. The expected benefits of knowledge-intensive applications such as expert systems include improvement in both the quality and the consistency of service delivery, augmentation of institutional memory, and reduced labour costs through greater reliance on paraprofessionals. This paper analyses the likely impacts of knowledge-intensive systems on social service organisations, drawing on trends in related service-delivery fields, and on (...) known impacts of computer applications in organisations. A structural change may be anticipated: decision making and planning functions will shift increasingly from social service professionals to administrators. (shrink)
Legal liabilities pertaining to the identification and selection of domain experts is an issue that could adversely impact expert systems developers. Problems pertaining to flawed knowledge, improperly defined expertise, and behavioural and psychological impediments are just some of the issues. This paper examines the torts of strict products liability and negligence that system developers could incur as a result of expert-related difficulties. Parallels from legal scholars and federal and state court decisions are discussed relevant to expert system projects and (...) developers. The paper concludes with a presentation of steps that systems developers can take to minimize potential legal liability. (shrink)
We introduce a rationality principle for a preference relation ⩽ on an arbitrary set of lotteries. Such a principle is a necessary and sufficient condition for the existence of an expected utility agreeing with ⩽. The same principle also guarantees a rational extension of the preference relation to any larger set of lotteries. When the extended relation is unique with respect to the alternatives under consideration, the decision maker does not need a numerical evaluation in order to make a choice. (...) Such a rationality condition needs little information in order to be applied, and its verification amounts to solving a linear system. (shrink)
A rule-based expert system is demonstrated to have both a symbolic computational network representation and a sub-symbolic connectionist representation. These alternate views enhance the usefulness of the original system by facilitating introduction of connectionist learning methods into the symbolic domain. The connectionist representation learns and stores metaknowledge in highly connected subnetworks and domain knowledge in a sparsely connected expert network superstructure. The total connectivity of the neural network representation approximates that of real neural systems and hence avoids scaling and (...) memory stability problems associated with other connectionist models. (shrink)
Actual AI research began auspiciously around 1955 with Allen Newell and Herbert Simon's work at the RAND Corporation. Newell and Simon proved that computers could do more than calculate. They demonstrated that computers were physical symbol systems whose symbols could be made to stand for anything, including features of the real world, and whose programs could be used as rules for relating these features. In this way computers could be used to simulate certain important aspects intelligence. Thus the information-processing (...) model of the mind was born. But, looking back over these fifty years, it seems that theoretical AI with its promise of a robot like HAL appears to be a perfect example of what Imre Lakatos has called a "degenerating research program". (shrink)
Knowledge engineering is the term given to the process of developing expert systems and knowledge engineers are the people who acquire the requisite knowledge from experts and structure that knowledge into a useable computer program. As knowledge engineering becomes a more accepted technology, there is increasing concern about attendant social costs, such as job displacement or possible exploitation of experts. This paper reports on our efforts to explore this latter issue by scrutinizing how knowledge engineers think about the domain (...) expert and the role that person plays in system development. To accomplish this aim, we asked several samples of novice engineers to write story completions to a preamble that describes a knowledge engineer encountering a reluctant expert who may be fearing job loss if the system is implemented. The resulting accounts were content-analysed for insights as to how novice system builders think about experts. The results indicate that experts are conceived more as a tool to be used rather than a person to be respected. (shrink)
We investigated the understanding of causal systems categories—categories defined by common causal structure rather than by common domain content—among college students. We asked students who were either novices or experts in the physical sciences to sort descriptions of real-world phenomena that varied in their causal structure (e.g., negative feedback vs. causal chain) and in their content domain (e.g., economics vs. biology). Our hypothesis was that there would be a shift from domain-based sorting to causal sorting with increasing expertise in (...) the relevant domains. This prediction was borne out: The novice groups sorted primarily by domain and the expert group sorted by causal category. These results suggest that science training facilitates insight about causal structures. (shrink)
Reasoners compare problems to prior cases to draw conclusions about a problem and guide decision making. All Case-Based Reasoning (CBR) employs some methods for generalizing from cases to support indexing and relevance assessment and evidences two basic inference methods: constraining search by tracing a solution from a past case or evaluating a case by comparing it to past cases. Across domains and tasks, however, humans reason with cases in subtly different ways evidencing different mixes of and mechanisms for these components.In (...) recent CBR research in Artificial Intelligence (AI), five paradigmatic approaches have emerged: statistically-oriented, model-based, planning/design-oriented, exemplar-based, and adversarial or precedent-based. The paradigms differ in the assumptions they make about domain models, the extent to which they support symbolic case comparison, and the kinds of inferences for which they employ cases. (shrink)
When professionals are asked about the value of information technology to their work, they typically give two kinds of answers. Some see the advent or arrival of sophisticated information technology as a great boon to their professional lives. For them, the only question is how soon can the technology be deployed to open up new horizons for professional activity and end dull and tedious work. Others sense more acutely the serious..
The introduction of massive parallelism and the renewed interest in neural networks gives a new need to evaluate the relationship of symbolic processing and artificial intelligence. The physical symbol hypothesis has encountered many difficulties coping with human concepts and common sense. Expert systems are showing more promise for the early stages of learning than for real expertise. There is a need to evaluate more fully the inherent limitations of symbol systems and the potential for programming compared with training. (...) This can give more realistic goals for symbolic systems, particularly those based on logical foundations. (shrink)