According to the Selective Accessibility Model of anchoring, the comparison question in the standard anchoring paradigm activates information that is congruent with an anchor. As a consequence, this information will be more likely to become the basis for the absolute judgment which will therefore be assimilated toward the anchor. However, if the activated information overlaps with information that is elicited by the absolute judgment itself, the preceding comparative judgment should not exert an incremental effect and should fail to result in an anchoring effect. The present studies find this result when the comparative judgment refers to a general category and the absolute judgment refers to a subset of the general category that was activated by the anchor value. For example, participants comparing the average annual temperature in New York City to a high 102 °F judged the average winter, but not summer temperature to be higher than participants making no comparison. On the other hand, participants comparing the annual temperature to a low –4 °F judged the average summer, but not winter temperature to be lower than control participants. This pattern of results was shown also in another content domain. It is consistent with the Selective Accessibility Model but difficult to reconcile with other main explanations of the anchoring effect.

Most decision-making models describing individual differences in heuristics and biases tasks build on the assumption that reasoners produce a first incorrect answer in a quick, automatic way which they may or may not override later and that the advantage of high capacity reasoners arises from this late correction mechanism. To investigate this assumption, we developed a mouse-tracking analysis technique to capture individuals’ first answers and subsequent thinking dynamics. Across two denominator neglect task experiments, we observed that individuals initially move the mouse cursor towards the correct answer option in a substantial number of cases suggesting that reasoners may not always produce an incorrect answer first. Furthermore, we observed that, compared to low capacity reasoners, high capacity individuals revise their first answer more frequently if it is incorrect and make fewer changes if it is correct. However, we did not find evidence that high capacity individuals produce correct initial answers more frequently. Consistent with the predictions of previous decision-making models, these results suggest that in the denominator neglect task the capacity-normativity relationship arises after the initial response is formulated. The present work demonstrates how the analysis of mouse trajectories can be utilized to investigate individual differences in decision-making and help us better apprehend the dynamics of thinking behind decision biases.

Combining meaning, memory, and development, the perennially popular topic of intuition can be approached in a new way. Fuzzy-trace theory integrates these topics by distinguishing between meaning-based gist representations, which support fuzzy (yet advanced) intuition, and superficial verbatim representations of information, which support precise analysis. Here, I review the counterintuitive findings that led to the development of the theory and its most recent extensions to the neuroscience of risky decision making. These findings include memory interference (worse verbatim memory is associated with better reasoning); nonnumerical framing (framing effects increase when numbers are deleted from decision problems); developmental decreases in gray matter and increases in brain connectivity; developmental reversals in memory, judgment, and decision making (heuristics and biases based on gist increase from childhood to adulthood, challenging conceptions of rationality); and selective attention effects that provide critical tests comparing fuzzy-trace theory, expected utility theory, and its variants (e.g., prospect theory). Surprising implications for judgment and decision making in real life are also discussed, notably, that adaptive decision making relies mainly on gist-based intuition in law, medicine, and public health.

When people are confronted with multiple tasks, how do they decide which task to do first? Normatively, priority should be given to the most efficient task (i.e., the task with the best cost/benefit ratio). However, we hypothesize that people consistently choose to address smaller (involving less work) tasks first, and continue to focus on smaller tasks, even when this strategy emerges as less efficient, a phenomenon we term the “smaller tasks trap”. We also hypothesize that the preference for the smaller tasks is negatively related to individual differences in the tendency for rational thinking. To test these hypotheses, we developed a novel paradigm consisting of an incentive-compatible task management game, in which participants are saddled with multiple tasks and have to decide how to handle them. The results lend weight to the smaller tasks trap and indicate that individual differences in rational thinking predict susceptibility to this trap. That is, participants low in rational thinking preferred to start with a smaller (vs. larger) task and focused more on the smaller tasks regardless of their efficiency. Consequently, their overall performance in the task management game was significantly lower. We discuss the theoretical and practical implications of these findings and suggest possible interventions that may help people improve their task management.

We compare and critique two measures of risk perception. We suggest that a single question — “How risky is the situation?” — captures the concept of risk perception more accurately than the multiple-item measure used by Sitkin and Weingart (1995). In fact, this latter measure inadvertently captures notions of attractiveness or expected return, rather than risk perception. We further propose that the error underlying the construction of Sitkin and Weingart’s measure is explained in terms of a top-down model of risk perception, in which perceived risk and perceived return are consequences, rather than determinants, of attractiveness. Two studies compare the validity of the two alternative measures.

Whereas people’s reasoning is often biased by intuitive stereotypical associations, recent debiasing studies suggest that performance can be boosted by short training interventions that stress the underlying problem logic. The nature of this training effect remains unclear. Does training help participants correct erroneous stereotypical intuitions through deliberation? Or does it help them develop correct intuitions? We addressed this issue in four studies with base-rate neglect and conjunction fallacy problems. We used a two-response paradigm in which participants first gave an initial intuitive response, under time pressure and cognitive load, and then gave a final response after deliberation. Studies 1A and 2A showed that training boosted performance and did so as early as the intuitive stage. After training, most participants solved the problems correctly from the outset and no longer needed to correct an initial incorrect answer through deliberation. Studies 1B and 2B indicated that this sound intuiting persisted over at least two months. The findings confirm that a short training can debias reasoning at an intuitive “System 1” stage and get reasoners to favour logical over stereotypical intuitions.

Hammond (1996) argued that much of the research in the field of judgment and decision making (JDM) can be categorized as focused on either coherence or correspondence (C&C) and that, in order to understand the findings of the field, one needs to understand the differences between these two criteria. Hammond’s claim is that conclusions about the competence of judgments and decisions will depend upon the selection of coherence or correspondence as the criterion (Hammond, 2008). First, I provide an overview of the terms coherence and correspondence (C&C) as philosophical theories of truth and relate them to the field of JDM. Second, I provide an example of Hammond’s claim by examining literature on base rate neglect. Third, I examine Hammond’s claim as it applies to the broader field of JDM. Fourth, I critique Hammond’s claim and suggest that refinements to the C&C distinction are needed. Specifically, the C&C distinction 1) is more accurately applied to criteria than to researchers, 2) should be refined to include two important types of coherence (inter and intrapersonal coherence) and 3) neglects the third philosophical theory of truth, pragmatism. Pragmatism, as a class of criteria in JDM, is defined as goal attainment. In order to provide the most complete assessment of human judgment possible, and understand different findings in the field of JDM, all three criteria should be considered.

Numerical predictions are of central interest for both coherence-based approaches to judgment and decisions — the Heuristic and Biases (HB) program in particular — and to correspondence-based approaches — Social Judgment Theory (SJT). In this paper I examine the way these two approaches study numerical predictions by reviewing papers that use Cue Probability Learning (CPL), the central experimental paradigm for studying numerical predictions in the SJT tradition, while attempting to look for heuristics and biases. The theme underlying this review is that both bias-prone heuristics and adaptive heuristics govern subjects’ predictions in CPL. When they have little experience to guide them, subjects fall prey to relying on bias-prone natural heuristics, such as representativeness and anchoring and adjustment, which are the only prediction strategies available to them. But, as they acquire experience with the prediction task, these heuristics are abandoned and replaced by ecologically valid heuristics.

The domain of “folk-economics” consists in explicit beliefs about the economy held by laypeople, untrained in economics, about such topics as, for example, the causes of the wealth of nations, the benefits or drawbacks of markets and international trade, the effects of regulation, the origins of inequality, the connection between work and wages, the economic consequences of immigration, or the possible causes of unemployment. These beliefs are crucial in forming people's political beliefs and in shaping their reception of different policies. Yet, they often conflict with elementary principles of economic theory and are often described as the consequences of ignorance, irrationality, or specific biases. As we will argue, these past perspectives fail to predict the particular contents of popular folk-economic beliefs and, as a result, there is no systematic study of the cognitive factors involved in their emergence and cultural success. Here we propose that the cultural success of particular beliefs about the economy is predictable if we consider the influence of specialized, largely automatic inference systems that evolved as adaptations to ancestral human small-scale sociality. These systems, for which there is independent evidence, include free-rider detection, fairness-based partner choice, ownership intuitions, coalitional psychology, and more. Information about modern mass-market conditions activates these specific inference systems, resulting in particular intuitions, for example, that impersonal transactions are dangerous or that international trade is a zero-sum game. These intuitions in turn make specific policy proposals more likely than others to become intuitively compelling, and, as a consequence, exert a crucial influence on political choices.