Blargh Blog

Thursday, April 21, 2005


The Power of Letting Computers do your Thinking for you

Beyond Blink:

John Gottman, the man who predicts with startling accuracy whether marriages will last, talks about his work and "the mathematics of love." Gottman claims:
We've now gotten to the point where not only can we predict what's going to happen to the relationship, and not only can we intervene to prevent decay of relationships for people who really want to stay together, not only can we help people who really are continually unhappy with one another, to find out why their relationship isn't working, but we're really starting to understand the whole equation of this process, of having close relationships.

Sue Halpern compares the intuitive thin-slicing that Gladwell praises to the simple rules (fast and frugal heuristics) that Gigerenzer develops and advocates and Goldberg's view of intuitions as accumulated wisdom. Goldberg writes:
But in reality, intuition is the condensation of vast prior analytic experience; it is analysis compressed and crystallized.... It is the product of analytic processes being condensed to such a degree that its internal structure may elude even the person benefiting from it.... The intuitive decision-making of an expert bypasses orderly, logical steps precisely because it is a condensation of extensive use of such orderly logical steps in the past.

Neil Levy observes how often rules beat intuitions and ponders the implications that this has for the role of expert and lay intuitions in philosophy. Here's his account of the power of Statistical Prediction Rules (SPRs):

SPRs are (relatively) simple rules that are very successful in predicting a wide range of outcomes. There are SPRs for predicting whether a past criminal will reoffend, whether a psychiatric patient is likely to be violent, whether a candidate for admission to a college or university is likely to graduate, whether an applicant for a loan is a good risk, and so on. Provided with the right data (often surprisingly little data), SPRs typically do at least as well, and often better, than human experts on these problems. In many cases, SPRs outperform the experts even when the experts are presented with more evidence than the SPR uses, and even when the expert is also provided with the prediction of the SPR. Human experts, like the rest of us, tend to believe they have a special insight into cases and people, and so will selectively depart from the SPRs when they get a gut feeling that its prediction is wrong. More often than not, it is the expert who is wrong.

Blink II


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