The Generic Decision-Making

The generic decision-making task we describe usually consists of repeated predictions, based on the same set of observable variables, about a complicated outcome – graduate school success, financial performance, health- that is rather unpredictable. For the sake of brevity, we shall not discuss other important tasks such as probability estimation or revision, inference, categorization, or trade-offs among attributes, costs, and benefits.

The literature we review is indirectly related to the well-known “heuristics and biases” approach. Our theme is that experts know a lot but predict poorly. Perhaps their knowledge is biased, if it comes from judgment heuristics or they use heuristics in applying it. We can only speculate about this possibility (as we do later, in a few places) until further research draws the connection more clearly.

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For our purposes, an expert is a person who is experienced at making predictions in a domain and has some professional or social credentials. The experts described here are no slouches: They are psychologists, doctors, academics, accountants, gamblers, and parole officers who are intelligent, well paid, and often proud. We draw no special distinction between them and extraordinary experts, or experts acclaimed by peers. We suspect that our general conclusions would apply to more elite populations of experts, 1 but clearly there have been too few studies of these populations.

The chapter is organized as follows: In section 2 we review what we currently know about how well experts perform decision tasks, then in section 3 we review recent work on expert decision processes. Section 4 integrates the views described in sections 2 and 3. Then we examine the implications of this work for decision research and for the study of expertise in general.


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