Literature DB >> 6339662

What kind of expert should a system be?

P E Johnson.   

Abstract

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.

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Year:  1983        PMID: 6339662     DOI: 10.1093/jmp/8.1.77

Source DB:  PubMed          Journal:  J Med Philos        ISSN: 0360-5310


  3 in total

1.  Machine learning for an expert system to predict preterm birth risk.

Authors:  L K Woolery; J Grzymala-Busse
Journal:  J Am Med Inform Assoc       Date:  1994 Nov-Dec       Impact factor: 4.497

2.  Processing of unconventional stimuli requires the recruitment of the non-specialized hemisphere.

Authors:  Yoed N Kenett; David Anaki; Miriam Faust
Journal:  Front Hum Neurosci       Date:  2015-02-09       Impact factor: 3.169

3.  Crossing the Death Valley to Transfer Environmental Decision Support Systems to the Water Market.

Authors:  Manel Poch; Joaquim Comas; Ulises Cortés; Miquel Sànchez-Marrè; Ignasi Rodríguez-Roda
Journal:  Glob Chall       Date:  2017-04-10
  3 in total

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