Repeated decision making is subject to changes over time such as decreases in decision time and information use and increases in decision accuracy. We show that a traditional strategy selection view of decision making cannot account for these temporal dynamics without relaxing main assumptions about what defines a decision strategy. As an alternative view we suggest that temporal dynamics in decision making are driven by attentional and perceptual processes and that this view has been expressed in the information reduction hypothesis. We test the information reduction hypothesis by integrating it in a broader framework of top down and bottom up processes and derive the predictions that repeated decisions increase top down control of attention capture which in turn leads to a reduction in bottom up attention capture. To test our hypotheses we conducted a repeated discrete choice experiment with three different information presentation formats. We thereby operationalized top down and bottom up control as the effect of individual utility levels and presentation formats on attention capture on a trial-by-trial basis. The experiment revealed an increase in top down control of eye movements over time and that decision makers learn to attend to high utility stimuli and ignore low utility stimuli. We furthermore find that the influence of presentation format on attention capture reduces over time indicating diminishing bottom up control.

Although Mechanical Turk has recently become popular among social scientists as a source of experimental data, doubts may linger about the quality of data provided by subjects recruited from online labor markets. We address these potential concerns by presenting new demographic data about the Mechanical Turk subject population, reviewing the strengths of Mechanical Turk relative to other online and offline methods of recruiting subjects, and comparing the magnitude of effects obtained using Mechanical Turk and traditional subject pools. We further discuss some additional benefits such as the possibility of longitudinal, cross cultural and prescreening designs, and offer some advice on how to best manage a common subject pool.

This study analyzes the relative accuracy of experts, polls, and the so-called ‘fundamentals’ in predicting the popular vote in the four U.S. presidential elections from 2004 to 2016. Although the majority (62%) of 452 expert forecasts correctly predicted the directional error of polls, the typical expert’s vote share forecast was 7% (of the error) less accurate than a simple polling average from the same day. The results further suggest that experts follow the polls and do not sufficiently harness information incorporated in the fundamentals. Combining expert forecasts and polls with a fundamentals-based reference class forecast reduced the error of experts and polls by 24% and 19%, respectively. The findings demonstrate the benefits of combining forecasts and the effectiveness of taking the outside view for debiasing expert judgment.

We conducted a replication of Shafir (1993) who showed that people are inconsistent in their preferences when faced with choosing versus rejecting decision-making scenarios. The effect was demonstrated using an enrichment paradigm, asking subjects to choose between enriched and impoverished alternatives, with enriched alternatives having more positive and negative features than the impoverished alternative. Using eight different decision scenarios, Shafir found support for a compatibility principle: subjects chose and rejected enriched alternatives in choose and reject decision scenarios (d = 0.32 [0.23,0.40]), respectively, and indicated greater preference for the enriched alternative in the choice task than in the rejection task (d = 0.38 [0.29,0.46]). In a preregistered very close replication of the original study (N = 1026), we found no consistent support for the hypotheses across the eight problems: two had similar effects, two had opposite effects, and four showed no effects (overall d = −0.01 [−0.06,0.03]). Seeking alternative explanations, we tested an extension, and found support for the accentuation hypothesis.

Previous research has demonstrated a link between illusory pattern perception and various irrational beliefs. On this basis, we hypothesized that participants who displayed greater degrees of illusory pattern perception would also be more likely to rate pseudo-profound bullshit statements as profound. We find support for this prediction across three experiments (N = 627) and four distinct measures of pattern perception. We further demonstrate that this observed relation is restricted to illusory pattern perception, with participants displaying greater endorsement of non-illusory patterns being no more likely to rate pseudo-profound bullshit statements as profound. Additionally, this relation is not a product of a general proclivity to rate all statements as profound and is not accounted for by individual differences in analytic thinking. Overall, we demonstrate that individuals with a tendency to go beyond the available data such that they uncritically endorse patterns where no patterns exist are also more likely to create and endorse false-meaning in meaningless pseudo-profound statements. These findings are discussed in the context of a proposed framework that views individuals’ receptivity to pseudo-profound bullshit as, in part, an unfortunate consequence of an otherwise adaptive process: that of pattern perception.

The current study examines the construct validity of the Maximization Scale (MS; Schwartz et al., 2002) and the Maximization Tendency Scale (MTS; Diab et al., 2008) as well as the nomological net of the maximizing construct. We find that both scales of maximizing suffer psychometrically, especially in their proposed dimensionality. Using confirmatory factor analysis and item response theory (IRT) we identify and remove three problematic items from the MTS and six problematic items from the MS. Additionally, we find that the MS appears to be measuring difficulty and restlessness with the search for the best alternative, whereas the MTS is more focused on the search for the best option, regardless of choice difficulty. We then examined these revised scales in relation to other psychological constructs in the nomological net for maximizing and found that maximizers may not be unhappy but are generally distressed in the decision-making context. Finally, we suggest that future maximizng research use revised form of the MTS that seems to us to be most consistent with the original concept of maximizing/satisficing.

Butler and Pogrebna (2018) devised triples of three-branch gambles theorized to violate transitivity of preference according to a most probable winner model. According to this model, a person chooses the option that has the higher probability to yield a better outcome than the other alternative. They tested 11 triples with 100 participants and found cases that appeared to violate weak stochastic transitivity and the triangle inequality. But tests of weak stochastic transitivity and the triangle inequality do not provide a proper method to compare transitive and intransitive models that allow mixtures of preference patterns and random errors. Those older methods can yield false conclusions regarding transitivity, for example, if different participants have different true preferences or if different choice problems have different rates of error. This paper reanalyzes their data using a true and error (TE) model, which does not require these unrealistic assumptions, and which provides estimates of the incidence of transitive and intransitive behavior in a mixture. Reanalysis indicated that 3 of the 11 triples showed convincing evidence of violations of transitivity in the opposite direction of the predictions of the most probable winner model. Further, these and other triples showed other significant violations of the most probable winner model. Despite some violations of the true and error model, the data of Butler and Pogrebna appear to contradict not only transitive utility models but they also refute the most probable winner model as a descriptive theory of choice behavior.

The paper critically reexamines the well-known “Julie and Mark” vignette, a stylized account of two college-age siblings opting to engage in protected sex while vacationing abroad (e.g., Haidt, 2001). Since its inception, the story has been viewed as a rhetorically powerful validation of Hume’s “sentimentalist” dictum that moral judgments are not rationally deduced but arise directly from feelings of pleasure or displeasure (e.g., disgust). People’s typical reactions to the vignette are alleged to support this view by demonstrating that individuals are prone to become morally dumbfounded (Haidt, 2001; Haidt, Bjorklund, & Murphy, 2000), i.e., they tend to “stubbornly” maintain their disapproval of the act without supporting reasons. In what follows, we critically reassess the traditional account, predicated on the notion that, among other things, most subjects simply fail to be convinced that the siblings’ actions are truly harm-free, thus having excellent reasons to disapprove of these acts. In line with this critique, 3 studies found that subjects 1) tended not to believe that the siblings’ actions were in fact harmless; 2) notwithstanding that, and in spite of holding a number of “counterargument-immune” reasons, subjects could be effectively maneuvered into exhibiting all the trademark signs of a morally dumbfounded state (which they subsequently recanted), and 3) with subjects’ beliefs about harm and standards of normative evaluation properly factored in, a more rigorous assessment procedure yielded a dumbfounding estimate of about 0. Based on these and related results, we contend that subjects’ reactions are wholly in line with the rationalist model of moral judgment and that their use in support of claims of moral arationalism should be reevaluated.

We demonstrate that the desirability bias, the elevation of the estimated likelihood of a preferred event, can be due in part to the desire for consistency between the preference for the favored event and its predicted likelihood. An experiment uses a participant’s favorite team in Major League Baseball games and a recently devised method for priming the consistency goal. When preference is the first response, priming cognitive consistency moves prediction toward greater agreement with that preference, thereby increasing the desirability bias. In contrast, when prediction is the first response, priming cognitive consistency facilitates greater agreement with the factual information for each game. This increases the accuracy of the prediction and reduces the desirability bias.

The history of judgment and decision making is defined by a trend toward increasingly nuanced explanations of the decision making process. Recently, process models have become incredibly sophisticated, yet the tools available to directly test these models have not kept pace. These increasingly complex process models require increasingly complex process data by which they can be adequately tested. We propose a new class of data collection that will facilitate evaluation of sophisticated process models. Tracking mouse paths during a continuous response provides an implicit measure of the growth of preference that produces a choice—rather than the current practice of recording just the button press that indicates that choice itself. Recent research in cognitive science (Spivey & Dale, 2006) has shown that cognitive processing can be revealed in these dynamic motor responses. Unlike current process methodologies, these response dynamics studies can demonstrate continuous competition between choice options and even online preference reversals. Here, in order to demonstrate the mechanics and utility of the methodology, we present an example response dynamics experiment utilizing a common multi-alternative decision task.

Psychologists typically measure beliefs and preferences using self-reports, whereas economists are much more likely to infer them from behavior. Prediction markets appear to be a victory for the economic approach, having yielded more accurate probability estimates than opinion polls or experts for a wide variety of events, all without ever asking for self-reported beliefs. We conduct the most direct comparison to date of prediction markets to simple self-reports using a within-subject design. Our participants traded on the likelihood of geopolitical events. Each time they placed a trade, they first had to report their belief that the event would occur on a 0–100 scale. When previously validated aggregation algorithms were applied to self-reported beliefs, they were at least as accurate as prediction-market prices in predicting a wide range of geopolitical events. Furthermore, the combination of approaches was significantly more accurate than prediction-market prices alone, indicating that self-reports contained information that the market did not efficiently aggregate. Combining measurement techniques across behavioral and social sciences may have greater benefits than previously thought.

Some charities are much more cost-effective than other charities, which means that they can save many more lives with the same amount of money. Yet most donations do not go to the most effective charities. Why is that? We hypothesized that part of the reason is that people underestimate how much more effective the most effective charities are compared with the average charity. Thus, they do not know how much more good they could do if they donated to the most effective charities. We studied this hypothesis using samples of the general population, students, experts, and effective altruists in five studies. We found that lay people estimated that among charities helping the global poor, the most effective charities are 1.5 times more effective than the average charity (Studies 1 and 2). Effective altruists, in contrast, estimated the difference to be factor 50 (Study 3) and experts estimated the factor to be 100 (Study 4). We found that participants donated more to the most effective charity, and less to an average charity, when informed about the large difference in cost-effectiveness (Study 5). In conclusion, misconceptions about the difference in effectiveness between charities is thus likely one reason, among many, why people donate ineffectively.

This paper presents the results of a study that sheds new light on the shape of indifference curves in the Marschak-Machina triangle. The most important observation, obtained non-parametrically, concerns jumps in indifference curves at the triangle legs towards the triangle origin. These jumps, however, do not appear at the hypotenuse. The pattern observed suggests discontinuity in lottery valuation when the range of lottery outcomes changes and is best explained by decision-making models based on the psychological phenomenon of range dependence (Parducci, 1965; Cohen, 1992; Kontek & Lewandowski, 2018). Models founded on other psychological phenomena, e.g., discontinuity in decision weights (Kahneman & Tversky, 1979), cumulative probability weighting (Tversky & Kahneman, 1992), attention shifting (Birnbaum, 2008), overweighting of salient payoffs (Bordallo, Gennaioli & Shefrin, 2012), and treating stated probabilities as imperfect information (Viscusi, 1989), predict indifference curve shapes that differ from the one obtained in this study.

Experiments are increasingly moving online. This poses a major challenge forresearchers who rely on in-lab techniques such as eye-tracking. Researchers incomputer science have developed web-based eye-tracking applications (WebGazer;Papoutsaki et al., 2016) but they have yet to see them used in behavioralresearch. This is likely due to the extensive calibration and validationprocedure, inconsistent temporal resolution (Semmelmann & Weigelt, 2018),and the challenge of integrating it into experimental software. Here, weincorporate WebGazer into a JavaScript library widely used by behavioralresearchers (jsPsych) and adjust the procedure and code to reducecalibration/validation and improve the temporal resolution (from 100–1000ms to 20–30 ms). We test this procedure with a decision-making study onAmazon MTurk, replicating previous in-lab findings on the relationship betweengaze and choice, with little degradation in spatial or temporal resolution. Thisprovides evidence that online web-based eye-tracking is feasible in behavioralresearch.

Science often advances through disagreement among scientists and the studies they produce. For members of the public, however, conflicting results from scientific studies may trigger a sense of uncertainty that in turn leads to a feeling that nothing new has been learned from those studies. In several scenario studies, participants read about pairs of highly similar scientific studies with results that either agreed or disagreed, and were asked, “When we take the results of these two studies together, do we now know more, less, or the same as we did before about (the study topic)?” We find that over half of participants do not feel that “we know more” as the result of the two new studies when the second study fails to replicate the first. When the two study results strongly conflict (e.g., one finds a positive and the other a negative association between two variables), a non-trivial proportion of participants actually say that “we know less” than we did before. Such a sentiment arguably violates normative principles of statistical and scientific inference positing that new study findings can never reduce our level of knowledge (and that only completely uninformative studies can leave our level of knowledge unchanged). Drawing attention to possible moderating variables, or to sample size considerations, did not influence people’s perceptions of knowledge advancement. Scientist members of the American Academy of Arts and Sciences, when presented with the same scenarios, were less inclined to say that nothing new is learned from conflicting study results.

Indecisiveness is an individual difference measure of chronic difficulty and delay in decision making. Indecisiveness is associated with low decisional confidence and distinct patterns of pre-choice information search behavior. The present study explored whether the confidence levels and search behaviors associated with individual indecisiveness also emerge in group decision making contexts. In this study, 97 decisive and indecisive participants were assigned to make a decision individually or in a homogenous three-person group. Indecisiveness score was found to predict participant decisional confidence in the individual condition but not in the group condition, with group participants being overall more confident than individuals. Similar results were obtained for other related measures of participants’ perceptions of the decision task. Surprisingly, no indecisiveness-related differences in information search were found, suggesting that other aspects of the group process contribute to increased confidence. The results provide initial evidence that indecisiveness does not influence group decision making and that, especially for indecisive individuals, working in groups may be a way to boost decisional confidence.

We propose that externally induced time limits on a task overly affect predictions of other people’s completion times for that task, due to an over-generalized association between the time available and inferred task scope. We find higher estimates of the time needed to complete a given task by another person when the time limit is longer. While such predictions could be normative when time limits are informative, the effect persists even when the decision-maker knows that the limit is arbitrary and is unknown to the other person, and therefore, cannot affect behavior. Perception of task scope mediates the relationship between time limits and completion time estimates, and weakening the association between time limits and task scope attenuates the effect. The over-learned cognitive bias persists even among experienced decision-makers making estimates in a familiar setting. Our findings have implications for people who make decisions that use judgments of others’ task completion time as an input.

Birnbaum (2020) reanalyses the data from Butler and Pogrebna (2018) using his ‘true and error’ test of choice patterns. His results generally support the evidence we presented in that paper. Here we reiterate the reasons for our agnosticism as to the direction any cycles might take, even though the paradox that motivated our study takes a ‘probable winner’ direction. We conclude by returning to the potential significance of predictably intransitive preferences for decision theory generally.

Using Brunswik’s (1952) lens model framework, Hammond (1965) proposed interpersonal conflict theory to explain the nature, source, and resolution of disagreement or “cognitive conflict” between parties performing judgment tasks. An early review by Brehmer (1976) highlighted the potential of this approach in, for example, understanding the structure of cognitive conflicts, and the effect of task and person variables on judgment policy change and conflict resolution. However, our bibliographic and content reviews from 1976 to the present day demonstrate that research on cognitive conflict using the lens model has declined sharply, while research on “task conflict” has grown dramatically. There has also been a shift to less theoretical precision and methodological rigor. We discuss possible reasons for these developments, and suggest ways in which lens model research on cognitive conflict can be revitalized by borrowing from recent theoretical and methodological advances in the field of judgment and decision making.