Representativeness and fallacies of probability judgment

Representativeness is the name given to the heuristic people often employ when they judge the probability of a sample by how well it represents certain salient features of the population from which it was drawn. The representativeness heuristic has also been used to account for how people judge the probability that a given population is the source of some sample. The latter probability, however, depends on other factors (e.g., the population's prior probability) as well as on the sample characteristics. A review of existing evidence suggests that the ignoring of such factors, a central finding of the heuristics approach to judgment under uncertainty, is a phenomenon which is conceptually distinct from the representativeness heuristic. These factors (base rates, sample size, and predictability) do not always exert the proper influence on people's first-order probability judgments, but they are not ignored when people make second-order (i.e., confidence) judgments. Other fallacies and biases in subjective evaluations of probability are, however, direct causal results of the employment of representativeness. For example, representativeness may be applied to the wrong features. Most devastating, perhaps, is that subjective probability judgments obey a logic of representativeness judgments, even though probability ought to obey an altogether different logic. Yet although the role of representativeness judgments in probability estimation leaves a lot to be desired, it is hard to envision prediction and inference completely unaided by representativeness.     

Commentary on Wolford,Taylor, and Beck: The conjunction fallacy?

AlthoughP(A&B|X) can never exceedP(A|X) (the conjunction rule), it is possible forP(X|A&B) to exceedP(X|A). Hence, people who rankA&B as more probable thanA are not necessarily violating any normative rule if the ranking is done in terms of the probability of these events to yield an eventX. Wolford, Taylor, and Beck (1990) have argued that this indeed is what happens in some problems (e.g. Tversky& Kahneman’s [1983] Linda problem). The claim made here is that the Linda problem is hard to reconcile with this interpretation; that there is little if any evidence that subjects utilize this interpretation; and that in any case, representativeness can account for all Linda problem results.     

Ideal evidence, relevance and second-order probabilities

Conclusion The concepts of supportive evidence and of relevant evidence seem very closely related to each other. Supportive evidence is clearly always relevant as well. But must relevant evidence be defined as evidence which is either supportive or weakeking? In an explicit or implicit manner, this is indeed the position of many philosophers. The paradox of ideal evidence, however, shows us that this is to restrictive. Besides increasing or decreasing the probability attached to some hypothesis, evidence can alter or interact with the background assumptions underlying the hypothesis.In most circumstances, the (post hoc) relevance of evidence can indeed be judged by its effect on the confidence one attaches to hypotheses. Occasionally, as in the circumstances described by Example I, and more generally called the Paradox of Ideal Evidence, the relevance of evidence to an hypothesis can only be understood by appeal to a broader sense.In Memory of My Father. Yehoshua Bar-HillelThe author wishes to thank Haim Gaifman for a most thoughtful and constructive review of an earlier draft of this paper.     

Seek and ye shall find: test results are what you hypothesize they are

Expert clinicians were given batteries of psychodiagnostic test results (Rorschach, TAT, Draw-A-Person, Bender-Gestalt, Wechsler) to analyze. For half, a battery came along with a suggestion that the person suffers from Borderline Personality disorder, and for half, that battery was accompanied by a suggestion that he suffers from Paranoid Personality disorder. In Study 1, the suggestion was made indirectly, through a background story that preceded the test results. In Study 2, the suggestion was made directly, by the instructions given. The experts saw in the tests what they hypothesized to be there. In particular, the target diagnoses were rated higher when they were hypothesized than when they were not. Copyright © 1998 John Wiley & Sons, Ltd.     

Where did 1850 happen first--in America or in Europe? A cognitive account for a historical bias

A professor of history at The Hebrew University noted that his students were often surprised to learn that some event in America happened at about the same time as another in Europe, because the American event seemed to them to have happened more recently. We confirmed the validity of this anecdotal observation experimentally, and offer an explanation. We discuss how this bias may be an effect of judgment, rather than memory. We then show experimentally that students like those who demonstrated the bias regarded America as the New World, as opposed to Europe's Old World. Our theoretical account, based on judgment by representativeness, posits that if one category is deemed more X than another (e.g., American history is deemed more "recent" than European history), then its members will be judged more X than members of the other, ceteris paribus. Hence, an American historical event will appear more recent than a contemporaneous European event.     

Predicting World Cup results: Do goals seem more likely when they pay off?

Bar-Hillel and Budescu (1995) failed to find a desirability bias in probability estimation. The World Cup soccer tournament provided an opportunity to revisit the phenomenon in a context in which desirability biases are notoriously rampant. Participants estimated the probabilities of various teams’ winning their upcoming games. They were promised money if one team—randomly designated by the experimenter—won its upcoming game. Participants assigned a higher probability to a victory by their target team than did other participants, whose promised monetary reward was contingent on the victory of its opponent. Prima facie, this seems to be a desirability bias. However, in a follow-up study that made one team salient, without promising monetary rewards, participants also judged their target team to be more likely to win. On grounds of parsimony, we conclude that what appears to be a desirability bias may just be a salience/marking effect, and—although optimism is a robust and ubiquitous human phenomenon—that wishful thinking still remains elusive.     

Trial by polygraph: Scientific and juridical issues in lie detection

The present article examines two methods of polygraph-assisted lie detection: the Control Question Technique (CQT) and the Guilty Knowledge Technique (GKT). It presents the rationale for both, arguing that only the latter is well grounded in psychological theory. It then surveys the empirical support for claims of the polygraph's ability to detect deception, arguing that such support often comes from studies that are methodologically flawed by contamination of various sorts—especially studies of the CQT. The article then explores the legal implications of introducing polygraph test results, as presently gathered, into the criminal courtroom.