What kind of expert should a system be?

Human experts are the source of knowledge required to develop computer systems that perform at an expert level. Human beings are not, however, able to reliably express what they know. As a result, experts often develop non-authentic accounts of their own expertise. These accounts, here termed reconstructed methods of reasoning, lead to computer systems that perform at a high level of proficiency but have the disadvantage that they often do not reflect the heuristics and processing constraints of a system user. Reconstructed methods of reasoning are compared with authentic methods derived from the study of expert human behavior. Tests are proposed to establish the authenticity of reasoning methods and examples from medical diagnosis are used to illustrate how authentic methods of reasoning can be incorporated into an expert computer system. CiteULike Connotea Del.icio.us What's this?
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DOI 10.1093/jmp/8.1.77
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Dianne C. Berry (1994). A Step Too Far? Behavioral and Brain Sciences 17 (3):397-398.
Elizabeth Ennen (1994). Implicit Practical Learning. Behavioral and Brain Sciences 17 (3):404-405.

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Roger M. Cooke (1986). Probabilistic Reasoning in Expert Systems Reconstructed in Probability Semantics. PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association 1986:409 - 421.

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