When Should a Decision Maker Ignore the Advice of a Decision Aid?

27 Mar 2013Paul E. LehnerTheresa M. MullinMarvin S. 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... (read more)

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