Lola L. Lopes’s research while affiliated with University of Wisconsin–Madison and other places

Subjects’ preferences for a set of multi-outcome lotteries were assessed, and then subjects were exposed to a feedback period in which they played the lotteries and received information concerning outcomes. Afterward, preferences were reassessed. Most subjects’ preferences were risk averse in the prefeedback assessment, regardless of whether they were making single decisions (short-run condition) or choices for repeated plays (long-run condition), but long-run subjects were less risk averse than short-run subjects. In the postfeedback assessment, about half of the subjects in each condition became risk seeking and the other half maintained their risk-averse preferences. There were, however, differences between short-run and long-run subjects in the postfeedback pattern of risk seeking.

This chapter discusses the psychology of risk: what risk is (if it is anything at all), how people think about it, what they feel about it, and what they do about it. The chapter describes the way psychologists think about risk: how they study it, what tasks they use, what factors they vary, and what models they build (or borrow) to describe risk-taking behavior. Technically, the word risk refers to situations in which a decision is made whose consequences depend on the outcomes of future events having known probabilities. Psychological studies of risky choice (it is the term used conventionally to refer to all but the most extreme instances of ignorance or ambiguity) fall into two groups. At one extreme are the studies run by mathematically inclined experimental psychologists in which subjects make decisions about gambles described in terms of amounts and probabilities. At the other extreme are studies run by personality psychologists, who are mostly interested in individual differences in risk taking. A theory of risky choice is presented in the chapter that attempts to meld the strengths of both approaches. Empirically and methodologically it is tied to the experimental approach to risky choice. But theoretically it is more strongly tied to motivational approaches.

Subjects judged whether binary strings had been generated by a random or a nonrandom process. Half of the strings were generated by a Bernoulli process with p = .5. The other half were generated by either a repetition-biased process or an alternation-biased process. Subjects were (a) not informed about the nonrandom process, (b) informed about the qualitative nature of the process, or (c) given accurate feedback after each trial about the generating process. The data show that subjects equate long runs and symmetry with nonrandomness, and high rates of alternation with randomness, making them less successful in detecting alternation-biased processes. The data also show that performance can be improved by instructions or feedback. A second experiment using statistically sophisticated subjects showed that although they perform better than naive subjects, their data are similar qualitatively. We interpret these results in terms of whether the subject must perform the task in a null hypothesis mode or a maximum likelihood mode. (PsycINFO Database Record (c) 2012 APA, all rights reserved)

This paper presents two experiments that illustrate how Bayesian inferences can be debiased by analyzing and correcting the cognitive procedures that lead to the biases. In the first experiment, a training procedure is used that corrects a common error in the adjustment process used by subjects when integrating evidence. In the second experiment, a focusing technique is used to improve the relative weighting of samples in the overall judgment. These results are discussed in terms of a model of the judgment process comprising four basic stages: (a) initial scanning of stimulus information; (b) selection of items for processing in order of importance; (c) extraction of scale values on the judgment dimension; and (d) adjustment of a composite value that summarizes already-processed components.

In an experiment with 60 undergraduates, the robustness of the reflection effect was examined both within Ss and across Ss differing in risk style for a set of multi-outcome lotteries. Reflection was found to be weak and irregular for all choice pairs except those that included a lottery with a riskless component. The latter were generally preferred for gains but not for losses by both risk-averse and risk-seeking Ss. In all other choices, risk-averse and risk-seeking Ss differed systematically from one another, but in ways that are more complex than pure risk aversion or risk seeking would predict. It is concluded that the findings suggest a general inability of weighted value theories such as the prospect theory described by D. Kahneman and A. Tversky (1979) to adequately describe the pattern of risk preferences over individuals and over the full range of lottery types. Such inadequacy suggests the need for an alternative approach to risk with emphasis on the goals and strategies that individuals bring to the risky choice process. (21 ref) (PsycINFO Database Record (c) 2012 APA, all rights reserved)

Aesthetic appreciation of normative models has hampered the development of an empirical base in the behavioral decision sciences. Two examples from the "biases and heuristics" literature are used to show that even modern descriptive theories tend to focus on normative models. The argument is made that generalizability to operational contexts requires increased emphasis on empirical research occurring in or focusing on realistically complex environments. Three studies are described that illustrate the benefits of such research.

Tested a distributional model of risk using positive lotteries in 6 experiments with 580 undergraduates. Exps I and II investigated Ss' preferences for lotteries; Exps 3–6 investigated judgments of riskiness. In all experiments, Ss were presented with a target set of stimulus lotteries in all possible pairs. Overall data support the distributional model of risk for judgments of preference and of riskiness, demonstrating the usefulness of Lorenz curves in capturing the salient psychological features of risk and revealing, as hypothesized, that people's judgments of positive risks are functionally similar to judgments of distributional inequality. It is suggested that although the distributional model must be supplemented to handle features of the risk domain that are absent in welfare economics, it is preferable to other models of decision making under risk because it can express in a psychologically acceptable way many significant features of people's processing of and preference for risks. (38 ref) (PsycINFO Database Record (c) 2012 APA, all rights reserved)

Suggests that the psychological concept of risk has been limited by the reliance of experimenters on simple, static lotteries or gambles. Several treatments of risk from the older economic literature are presented to illustrate aspects of risk that psychologists tend not to consider. These aspects include the distinction between risk and uncertainty, the problem of ambiguity in risky choice, and the relation between risk preference and planning. The role of the decision makers' goals and aspirations in risky decisions is highlighted. (14 ref) (PsycINFO Database Record (c) 2012 APA, all rights reserved)