Stories Knowledge Engineers Tell About Expert Systems

Abstract

This paper describes part of a more extensive investigation of the values operating in the development and implementation of expert systems. The data come from a group of beginning knowledge engineers who have participated in a corporate sponsored Intelligent Systems Training Program. As part of the training they were asked to complete a number of stories describing a fictional knowledge engineer encountering a non-technical complication while building an expert system. Of particular concern for this report is a single scenario in which the knowledge engineer encounters a reluctant expert who may be fearing job displacement. The stories are analyzed for insights as to how system builders conceptualize their responsibilities vis-à-vis the expert. This is done by scrutinizing how knowledge engineers define the problem, whose responsibility it is to effect a solution, what kind of solution is adopted and whether the outcome is successful. Results are discussed in terms of their implications for a number of social issues attendant upon the introduction of intelligent computing machines. Keywords: social values, expert systems, ethical issues in computing.

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References

Boden, M. (1977). Artificial intelligence and natural man. New York Basic Books.

Buchanan, B. , & Shortliffe, E. (1984). The problem of evaluation . In B. Buchanan & E. Shortliffe (Eds.), Rule-based expert systems The MYCIN experiments of the Stanford Heuristic Programming Project Reading, MA: Addison-Wesley.

Collins, H.M. (1987). Expert systems and the science of knowledge. In W. E. Bijker , T. P. Hughes & T. J. Pinch (Eds.), The social construction of technological systems New directions m the sociology and history of technology. Cambridge, MA MIT Press.

Dreyfus, H.L. , & Dreyfus, S.E. (1986). Mind over machine. New York : Free Press.

Harmon, P. , & King, D. (1985). Expert systems. New York: Wiley.

Hart, A. (1986). Knowledge acquisition for expert systems. New York: McGraw Hill.

Hayes-Roth, F. (1984). The knowledge-based system: A tutorial. IEEE, September, 11-28.

Hayes-Roth, F. , Waterman, D.A. , & Lenat, D. (1983). Building expert systems. Reading, MA: Addison-Wesley.

Lenat, D. (1984). Knowledge-based systems in artificial intelligence . New York: McGraw-Hill.

10.

McCorduck, P. (1979). Machines who think San Francisco : Freeman.

11.

McDermott, J. (1982). Ri. A rule based configurer of computer systems. Artificial Intelligence 19, 39-88.

12.

Miller, G.A. , Galanter, E. , & Pribram, K. (1960). Plans and the structure of behavior New York: Holt, Rmehart & Winston.

13.

Perrolle, J.A. (1987). Computers and social change. Information, property, and power. Belmont, CA: Wadsworth .

14.

Read, S.J. (1987). Constructing causal scenarios: A knowledge structure approach to causal reasoning. Journal of Personality and Social Psychology, 52, 288-302.

15.

Schank, R.C. , & Abelson, R.P. (1977). Scripts, plans, goals and understanding. Hillsdale, NJ: Lawrence Erlbaum Associates.

16.

Schon, D.A. (1983). The reflective practitioner: How professionals think in action. New York Basic Books.

17.

Shortliffe, T. (1976). Computer-based medical consultations. MYCIN. New York: Elsevier.

18.

Texas Instruments Data Systems Group (1986 , February). Knowledge-based systems gain momentum in the marketplace . Artificial Intelligence Letter.

19.

Waterman, D. (1986). A guide to expert systems. Reading, MA: Addison-Wesley.

20.

Whitby, B. (1988). Artificial intelligence A handbook for professionals Chichester, England: Ellis Horwood