The Process-Performance Paradox

The process-performance paradox in expert judgment 209 deterministic environments, where it can be quite effective. The tendency of decision-makers to build special-case rules mirrors more adaptive processes of induction that can lead to increased accuracy. As Holland and associates pointed out, however, the validity of these mechanisms rests on the ability to check each specialization on many cases. In noisy domains like the ones we are discussing, there are few replications. It was unlikely, for example, that Dent would appear in many World Series, and even if he did, other “unique” circumstances could always yield further “explanatory” factors.

In sum, configura! rules are appealing because they are easy to use, have plausible causal explanations, and offer many degrees of freedom to fit data. Despite these advantages, configura! rules may have a downfall, as detailed in the next section.

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Why are configura/ rules often inaccurate?

One reason configura! rules may be inaccurate is that whereas they are induced under specific and often rare conditions, they may well be applied to a larger set of cases. Often, people induce such rules from observation, they will be overgeneralizing from a small sample. This is illustrated by a verbal protocol recorded by a physician who was chair of a hospital’s admissions committee for house staff, interns, and residents. Seeing an applicant from Wayne State who had very high board scores, the doctor recalled a promising applicant from the same school who had perfect board scores. Unfortunately, after being admitted, the prior aspirant had done poorly and left the program. The physician recalled this case and applied it to the new one: “We have to be quite careful with people from Wayne State with very high board scores .. : . We have had problems in the past.”

Configura! rules may also be wrong because the implicit theories that under- lie them are wrong. A large literature on “illusory correlation” contains many examples of variables that are thought to be correlated with outcomes (because they are similar) but are not. For example, most clinicians and novices think that people who see male features or androgynous figures in Rorschach ink-blots are more likely to be homosexual. They are not. A successful portfolio manager we know refused to buy stock in firms run by overweight CEOs, believing that control of one’s weight and control of a firm are correlated. Because variables that are only 111usori1y corre- lated with outcomes are likely to be used by both novices and experts, the small novice-expert difference suggests that illusory correlations may be common.

Configura! rules are also likely to be unrobust to small errors, or “brittle. “Is 1s Although the robustness of linear models is well established, we know of no analogous work on the unrobustness of configura! rules.


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