Uncertainty in Artificial Intelligence
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When Should a Decision Maker Ignore the Advice of a Decision Aid?
Paul Lehner, Theresa Mullin, Marvin Cohen
This paper argues that the principal difference between decision aids and most other types of information systems is the greater reliance of decision aids on fallible algorithms--algorithms that sometimes generate incorrect advice. It is shown that interactive problem solving with a decision aid that is based on a fallible algorithm can easily result in aided performance which is poorer than unaided performance, even if the algorithm, by itself, performs significantly better than the unaided decision maker. This suggests that unless certain conditions are satisfied, using a decision aid as an aid is counterproductive. Some conditions under which a decision aid is best used as an aid are derived.
Pages: 216-223
PS Link:
PDF Link: /papers/89/p216-lehner.pdf
AUTHOR = "Paul Lehner and Theresa Mullin and Marvin Cohen",
TITLE = "When Should a Decision Maker Ignore the Advice of a Decision Aid?",
BOOKTITLE = "Proceedings of the Fifth Conference Annual Conference on Uncertainty in Artificial Intelligence (UAI-89)",
ADDRESS = "Corvallis, Oregon",
YEAR = "1989",
PAGES = "216--223"

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