Erev, Ert, and Roth organized three choice prediction competitions focused on three related choice tasks: One shot decisions from description (decisions under risk), one shot decisions from experience, and repeated decisions from experience. Each competition was based on two experimental datasets: An estimation dataset, and a competition dataset. The studies that generated the two datasets used the same methods and subject pool, and examined decision problems randomly selected from the same distribution. After collecting the experimental data to be used for estimation, the organizers posted them on the Web, together with their fit with several baseline models, and challenged other researchers to compete to predict the results of the second (competition) set of experimental sessions. Fourteen teams responded to the challenge: The last seven authors of this paper are members of the winning teams. The results highlight the robustness of the difference between decisions from description and decisions from experience. The best predictions of decisions from descriptions were obtained with a stochastic variant of prospect theory assuming that the sensitivity to the weighted values decreases with the distance between the cumulative payoff functions. The best predictions of decisions from experience were obtained with models that assume reliance on small samples. Merits and limitations of the competition method are discussed. Copyright © 2009 John Wiley & Sons, Ltd.

Risky prospects come in different forms. Sometimes options are presented with convenient descriptions summarizing outcomes and their respective likelihoods. People can thus make decisions from description. In other cases people must call on their encounters with such prospects, making decisions from experience. Recent studies report a systematic and large description-experience gap. One key determinant of this gap is people's tendency to rely on small samples resulting in substantial sampling error. Here we examine whether this gap exists even when people draw on large samples. Although smaller, the gap persists. We use the choices of the present and previous studies to test a large set of candidate strategies that model decisions from experience, including 12 heuristics, two associative-learning models and the two-stage model of cumulative prospect theory. This model analysis suggests-as one explanation for the remaining description-experience gap in large samples-that people treat probabilities differently in both types of decisions.

The distinction between risk and uncertainty is deeply entrenched in psychologists ' and economists' thinking. Knight (1921), to whom it is frequently attributed, however, went beyond this dichotomy. Within the domain of risk, he set apart a priori and statistical probabilities, a distinction that maps onto that between decisions from description and experience, respectively. We argue this distinction is important because risky choices based on a priori (described) and statistical (experienced) probabilities can substantially diverge. To understand why, we examine various possible contributing factors to the description-experience gap. We find that payoff variability and memory limitations play only a small role in the emergence of the gap. In contrast, the presence of rare events and their representation as either natural frequencies in decisions from experience or single-event probabilities in decisions from description appear relevant for the gap.

Twin-studies suggest that a significant portion of individual differences in the propensity to take risks resides in people’s genetic make-up and there is evidence that variability in dopaminergic systems relates to individual differences in risky choice. We examined the link between risk taking in a risk taking task (the Balloon Analogue Risk Task, BART) and a variable number tandem repeat (VNTR) polymorphism in the 3′UTR of the dopamine transporter gene (SLC6A3/DAT1). Behavior in BART is known to be associated with activity in striatal reward-processing regions, and DAT1 is assumed to modulate striatal dopamine levels. We find that carriers of DAT1 alleles, which presumably result in lower striatal dopamine availability, showed more risk taking, relative to carriers of the alleles associated with higher striatal dopamine availability. Our analyses suggest that the mechanism underlying this association is diminished sensitivity to rewards among those who take more risks. Overall, our results support the notion that a behavioral genetic approach can be helpful in uncovering the basis of individual differences in risk taking.

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