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RESEARCH ARTICLE   Open Access    

Engineering experts critics for cooperative systems

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  • Abstract: Knowledge collection systems often assume they are cooperating with an unbiased expert. They have few functions for checking and fixing the realism of the expertise transferred to the knowledge base, plan, document or other product of the interaction. The same problem arises when human knowledge engineers interview experts. The knowledge engineer may suffer from the same biases as the domain expert. Such biases remain in the knowledge base and cause difficulties for years to come.To prevent such difficulties, this paper introduces the reader to “critic engineering”, a methodology that is useful when it is necessary to doubt, trap and repair expert judgment during a knowledge collection process. With the use of this method, the human expert and knowledge-based critic form a cooperative system. Neither agent alone can complete the task as well as the two together.The methodology suggested here offers a number of extensions to traditional knowledge engineering techniques. Traditional knowledge engineering often answers the questions delineated in generic task (GT) theory, yet GT theory fails to provide four additional sets of questions that one must answer to engineer a knowledge base, plan, design or diagnosis when the expert is prone to error. This extended methodology is called “critic engineering”.
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  • Bailley D.1991. Developing a Rule Base for Identifying Human Judgement Bias in information Acquisition Tasks, Master Thesis, Engineering Management Department, George Washington University, DC, 04.

    Google Scholar

    Berger M, Coleman L, Muilenburg B and Rohrer R, 1991. Influencer Effects on Confirmation Bias, Experiment Report, Institute for Artificial Intelligence, George Washington University, DC, 04.

    Google Scholar

    Bingham WP, Datko L, Jackson G and Oh S-H, 1990. Establishing and Approving Quality Critical Operational Issues: An Application Using the COPE Shell, Experiment Report, Institute for Artificial Intelligence, George Washington University, 04.

    Google Scholar

    Boose J, 1984. “Personal construct theory and the transfer of human expertise”. In: Proceedings of the National Conference on Al, Morgan Kaufman.

    Google Scholar

    Bylander T and Chandrasekaran B, 1987. “Generic tasks for knowledge based reasoning: The right level of abstraction for knowledge acquisition” Int. J. Man-Machine Stud.26231–243.

    Google Scholar

    Creevy L, Neal R, Reichard E and Turrentine B, 1991. Comparison of a Dynamic Critic to a Static Critic Using the Wason's 2 4 6 Problem, Experiment Report, Institute for Artificial Intelligence, George Washington University, 04.

    Google Scholar

    Fischer G, 1987. “A critic for Lisp”. In: Proceedings 10th International Joint Conference on Artificial Intelligence, pp 177–184, Morgan Kaufman.

    Google Scholar

    Gingrich S, Lehner G, Lepich C, Powell D, and Vautier J, 1990. The Mission: A Group One Final Report, Experiment Report, Institute for Artificial Intelligence, George Washington University, 04.

    Google Scholar

    Herron T, Mackoy R, Mohan , 1990. Critics for Expert Statisticians, Experiment Report, Institute for Artificial Intelligence, George Washington University, 12.

    Google Scholar

    Langlotz CP and Shortliffe EH, 1983. “Adapting a consultation system to critique user plans” Int. J. Man–Machine Stud.19479–496.

    Google Scholar

    Miller PL, 1983. “ATTENDING: Critiquing a physician's management plan” IEEE Trans. PAMI5 (5) 09, 449–461.

    Google Scholar

    Ratte D, Crowe C, Skarpness P and Allen T, 1991. Watson's 246 Confirmation Bias, Experiment Report, Institute for Artificial Intelligence, George Washington University, 04.

    Google Scholar

    Silverman BG, 1990. “Critiquing expert judgment via knowledge acquisition systems” AI Magazine11 (3) Fall, 60–79.

    Google Scholar

    Silverman BG, 1991a. “Expert critics: Operationalizing the judgment/decisionmaking literature as a theory of ‘bugs’ and repair strategies” Knowledge Acquisition3 (2), 06, 175–214.

    Google Scholar

    Silverman BG, 1991b. “Criticism based knowledge acquisition for document generation” Innovative Applic. Artif. Intell. pp 291–319, AAAI Press.

    Google Scholar

    Silverman BG, 1992a. Critiquing Human Error: A Knowledge Based Human Computer Collaboration Approach, Academic Press.

    Google Scholar

    Silverman BG, 1992b. “Human-computer collaboration” Human-Computer Interaction7 (2) Summer, 165–196.

    Google Scholar

    Silverman BG, 1992c. “Modeling and critiquing the confirmation bias in human reasoning” IEEE Trans. Systems. Man and Cybernetics, 09/10973–983.

    Google Scholar

    Silverman BG, Donnell ML and Bialley D, 1992. Toward the Implementation of Cognitive Bias Theory: A Methodology and a Rule Base, Institute for AI Technology Report, Washington, DC.

    Google Scholar

    Silverman BG and Mezher T, 1992. “Expert critics for engineering design applications” AI Magazine13 (1) 04, 45–62.

    Google Scholar

    Spickelmier RL and Newton AR. 1988. “Critic: A knowledge-based program for critiquing circuit designs” Proceedings of the IEEE International Conference on Computer Design: VLSI in Computers and Processors, pp 324–327, IEEE Computer Society Press.

    Google Scholar

    Staff , 1989. Knowledge Engineers Guide to COPE, Potomac: IntelliTek.

    Google Scholar

    Staff , 1990. COPE Users Guide, Potomac: IntelliTek.

    Google Scholar

    Zhou H, Simkol J and Silverman BG, 1989. “Configuration assessment logics for electromagnetic effects reduction (CLEER) of equipment on naval ships” Naval Engineers J.101 (3) 05, 127–137.

    Google Scholar

  • Cite this article

    Barry G. Silverman, R. Gregory Wenig. 1993. Engineering experts critics for cooperative systems. The Knowledge Engineering Review. 8:321 doi: 10.1017/S0269888900000321
    Barry G. Silverman, R. Gregory Wenig. 1993. Engineering experts critics for cooperative systems. The Knowledge Engineering Review. 8:321 doi: 10.1017/S0269888900000321

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RESEARCH ARTICLE   Open Access    

Engineering experts critics for cooperative systems

The Knowledge Engineering Review  8 Article number: 10.1017/S0269888900000321  (1993)  |  Cite this article

Abstract: Abstract: Knowledge collection systems often assume they are cooperating with an unbiased expert. They have few functions for checking and fixing the realism of the expertise transferred to the knowledge base, plan, document or other product of the interaction. The same problem arises when human knowledge engineers interview experts. The knowledge engineer may suffer from the same biases as the domain expert. Such biases remain in the knowledge base and cause difficulties for years to come.To prevent such difficulties, this paper introduces the reader to “critic engineering”, a methodology that is useful when it is necessary to doubt, trap and repair expert judgment during a knowledge collection process. With the use of this method, the human expert and knowledge-based critic form a cooperative system. Neither agent alone can complete the task as well as the two together.The methodology suggested here offers a number of extensions to traditional knowledge engineering techniques. Traditional knowledge engineering often answers the questions delineated in generic task (GT) theory, yet GT theory fails to provide four additional sets of questions that one must answer to engineer a knowledge base, plan, design or diagnosis when the expert is prone to error. This extended methodology is called “critic engineering”.

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    Barry G. Silverman, R. Gregory Wenig. 1993. Engineering experts critics for cooperative systems. The Knowledge Engineering Review. 8:321 doi: 10.1017/S0269888900000321
    Barry G. Silverman, R. Gregory Wenig. 1993. Engineering experts critics for cooperative systems. The Knowledge Engineering Review. 8:321 doi: 10.1017/S0269888900000321
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