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" "A particular example (i. e., of irrationality) involves interviews. Despite all the evidence about the uselessness of interviews in predicting future behavior, people remain convinced that some people—especially themselves—are superb at “psyching out” other people during an interview. In contrast, the research indicates that interviews are effective only insofar as they yield information they could more consistently and more validly be incorporated into a statistical model. One problem, of course, that leads to the belief in the superiority of the unstructured interview is that it is, in fact, not studied; there is almost no systematic feedback to most interviewers. Much of the time, the interviewer is in a particular position in an organization and never sees the interviewee again. Second, if the interviewer does see the interviewee later, then that means that the interviewee has been accepted, which often implies fairly reasonable performance. Moreover, it is always possible to rationalize failures.
Robyn Mason Dawes (July 23, 1936 – December 14, 2010) was an American psychologist who specialized in the field of human judgment.
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Again, what cannot be is not, and what is can be regarded as an instance of what can be. Individuals who make pseudodiagnoses on the basis of “typical” characteristics—by attending only to the numerator of the likelihood ratio rather than to both numerator and denominator—will similarly be doomed to failure by making diagnoses that are not empirically supported. Because such a diagnostic procedure is based on irrationality, it cannot in general succeed. And similarly, people who argue that both the evidence and its negation support the same conclusion are arguing irrationally, and hence the conclusions will be empirically flawed. The principle is the same.
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The DID problem is an example of arguing from a vacuum. The argument is basically that if one type of procedure (diagnosis, therapy, business venture, or whatever) does not work, then something else will. Well, perhaps nothing will work, or perhaps the only reason we observe that something did not work is that we were ignoring the cases in which it did—often because, for some very compelling social reasons, they never come to our attention.
I have discovered this argument from a vacuum often in the context of various “critiquing” studies of statistical versus clinical prediction. There is one overwhelming result from all the studies: When both predictions are made on the basis of the same information, which is either combined according to a statistical (actuarial) model or combined “in the head” of an experienced clinician, the statistical prediction is superior.