Recent research has shown that risk and reward are positively correlated in many environments, and that people have internalized this association as a “risk-reward heuristic”: when making choices based on incomplete information, people infer probabilities from payoffs and vice-versa, and these inferences shape their decisions. We extend this work by examining people’s expectations about another fundamental trade-off — that between monetary reward and delay. In 2 experiments (total N = 670), we adapted a paradigm previously used to demonstrate the risk-reward heuristic. We presented participants with intertemporal choice tasks in which either the delayed reward or the length of the delay was obscured. Participants inferred larger rewards for longer stated delays, and longer delays for larger stated rewards; these inferences also predicted people’s willingness to take the delayed option. In exploratory analyses, we found that older participants inferred longer delays and smaller rewards than did younger ones. All of these results replicated in 2 large-scale pre-registered studies with participants from a different population (total N = 2138). Our results suggest that people expect intertemporal choice tasks to offer a trade-off between delay and reward, and differ in their expectations about this trade-off. This “delay-reward heuristic” offers a new perspective on existing models of intertemporal choice and provides new insights into unexplained and systematic individual differences in the willingness to delay gratification.

In order to minimize the risk of infection during the Covid-19 pandemic, peopleare recommended to keep interpersonal distance (e.g., 1 m, 2 m, 6 feet), washtheir hands frequently, limit social contacts and sometimes to wear a face mask.We investigated how people judge the protective effect of interpersonal distanceagainst the Corona virus. The REM model, based on earlier empirical studies,describes how a person’s virus exposure decreases with the square of thedistance to another person emitting a virus in a face to face situation. In acomparison with model predictions, most participants underestimated theprotective effect of moving further away from another person. Correspondingly,most participants were not aware of how much their exposure would increase ifthey moved closer to the other person. Spectral analysis of judgments showedthat a linear ratio model with the independent variable = (initialdistance)/(distance to which a person moves) was the most frequently usedjudgment rule. It leads to insensitivity to change in exposure compared with theREM model. The present study indicated a need for information about the effectsof keeping interpersonal distance and about the importance of virus carryingaerosols in environments with insufficient air ventilation. Longer conversationsemitting aerosols in a closed environment may lead to ambient concentrations ofaerosols in the air that no distance can compensate for. The results of thestudy are important for risk communications in countries where people do notwear a mask and when authorities consider removal of a recommendation or arequirement to wear a face mask.

As the adage goes, “money makes the world go round” – but which direction does it spin? This analysis considers how basic decision research can help us work out how to answer this question. It suggests that the difficulty of deriving clear predictions based on existing decision research is at least partly rooted in two restrictive conventions. The first is the focus on deviations from rational choice, and the effort to capture observed deviations by assuming subjective value functions. While it is difficult to reject the hypothesis that choice behavior reflects the weighting of subjective values, it is not clear that it advances the derivation of useful predictions. A second restrictive convention is the focus on objective hypothesis testing, which favors analyses that evaluate small refinements of the popular models. The potential benefits of relaxing these conventions are considered, with reference to recent choice prediction competitions that facilitate the exploration of distinct assumptions and model development techniques. The winners in these competitions assume very different decision processes than those assumed by the popular “subjective functions” models. The relationship of the results to the big data revolution is discussed.

When people donate, they rarely give to the charities that do the most good perdollar. Why is this? One possibility is that they do not know how to giveeffectively. Another possibility is that they are not motivated to do so. Acrosssix tasks (Studies 1a, 1b), we found support for both explanations. Among laydonors, we observed multiple misconceptions—regarding disaster relief,overhead costs, donation splitting, and the relative effectiveness of local andforeign charities—that reduced the effectiveness of their giving.Similarly, we found that they were unfamiliar with the most effective charities(Studies 2a, 2b). Debunking these misconceptions and informing people abouteffectiveness boosted effective donations; however, a portion of lay donorscontinued to give ineffectively to satisfy their personal preferences. Bycontrast, a sample of self-identified effective altruists gave effectivelyacross all tasks. They exhibited none of the misconceptions that we observedamong lay donors and overwhelmingly favored the most effective option in theirchoice set (Study 3). Taken together, our studies imply that donors need to beboth informed and motivated to give effectively on a consistent basis.

Is prosociality parochial or universalist? To shed light on this issue, we examine the relationship between the amount of money given to a stranger (giving in an incentivized Dictator Game) and intergroup attitudes and behavior in the context of randomly assigned teams (a minimal group paradigm) among N = 4,846 Amazon Mechanical Turk workers. Using a set of Dynamic Identity Diffusion Index measures, we find that participants who give more in the Dictator Game show less preferential identification with their team relative to the other team, and more identification with all participants regardless of team. Furthermore, in an incentivized Voter Game, participants who give more in the Dictator Game are more likely to support compromise by voting for the opposing team in order to avoid deadlock. Together, these results suggest that – at least in this subject pool and using these measures – prosociality is better characterized by universalism than parochialism.

This paper asks whether moral preferences in eight medical dilemmas change as a function of how preferences are expressed, and how people choose when they are faced with two equally attractive help projects. In two large-scale studies, participants first read dilemmas where they “matched” two suggested helping projects (which varied on a single attribute) so that they became equally attractive. They did this by filling in a missing number (e.g., how many male patients must Project M save in order to be equally attractive as Project F which can save 100 female patients). Later, the same participants were asked to choose between the two equally attractive projects. We found robust evidence that people do not choose randomly, but instead tend to choose projects that help female (vs. male), children (vs. adult), innocent (vs. non-innocent), ingroup (vs. outgroup) and existing (vs. future) patients, and imply no (vs. some) risk of a harmful side-effect, even when these projects have been matched as equally attractive as, and save fewer patients than the contrasting project. We also found that some moral preferences are hidden when expressed with matching but apparent when expressed with forced choice. For example, 88–95% of the participants expressed that female and male patients are equally valuable when doing the matching task, but over 80% of them helped female patients in the choice task.

For two decades, researchers have investigated the correlates and consequences of individual differences in maximizing, the tendency to pursue the goal of making the best possible choice by extensively seeking out and comparing alternatives. In this time, many different conceptualizations of maximizing have been proposed, including several that incorporate a construct called “decision difficulty.” We propose that including decision difficulty in measures of maximizing is problematic because the tendency to experience difficulty when making decisions is a separate individual difference construct already studied independently of maximizing — namely, indecisiveness. Across two studies (total N = 639), we find that scales measuring decision difficulty and indecisiveness are strongly correlated (r’s ≥ .85), load on the same component in a principal component analysis, and show a very similar pattern of correlations with related variables. Moreover, decision difficulty and indecisiveness scales both show a divergent pattern of correlations when compared to measures of maximizing. We argue that decision difficulty scales are best interpreted as tapping the same underlying tendency as indecisiveness scales, and conclude that the tendency to experience difficulty in decision making is best conceptualized not as a component of maximizing, but rather a cause or consequence of it.

A prosocial action typically provides a more sizable benefit when directed at those who have less as opposed to those who have more. However, not all prosocial acts have a direct bearing on socioeconomic disadvantage, nor does disadvantage necessarily imply a greater need for the prosocial outcome. Of interest here, welfare impact may depend on the number of beneficiaries but not on their socioeconomic status. Across four preregistered studies of life-saving decisions, we demonstrate that when allocating resources, many people are benevolently partial. That is, they choose to help the disadvantaged even when this transparently implies sacrificing lives. We suggest that people construct prosocial aid as an opportunity to correct morally aversive inequalities, thus making relatively more disadvantaged recipients a more justifiable target of help. Benevolent partiality is reduced when people reflect beforehand on what aspects they will prioritize in their donation decision.

Prescriptive rules guide human behavior across various domains of community life, including law, morality, and etiquette. What, specifically, are rules in the eyes of their subjects, i.e., those who are expected to abide by them? Over the last sixty years, theorists in the philosophy of law have offered a useful framework with which to consider this question. Some, following H. L. A. Hart, argue that a rule’s text at least sometimes suffices to determine whether the rule itself covers a case. Others, in the spirit of Lon Fuller, believe that there is no way to understand a rule without invoking its purpose — the benevolent ends which it is meant to advance. In this paper we ask whether people associate rules with their textual formulation or their underlying purpose. We find that both text and purpose guide people’s reasoning about the scope of a rule. Overall, a rule’s text more strongly contributed to rule infraction decisions than did its purpose. The balance of these considerations, however, varied across experimental conditions: In conditions favoring a spontaneous judgment, rule interpretation was affected by moral purposes, whereas analytic conditions resulted in a greater adherence to textual interpretations. In sum, our findings suggest that the philosophical debate between textualism and purposivism partly reflects two broader approaches to normative reasoning that vary within and across individuals.

In the context of the COVID-19 pandemic, French public opinion has been divided about Pr. Didier Raoult and his hydroxychloroquine-based treatment against COVID-19. In this paper, our aim is to contribute to the understanding of this polarization of public opinion by investigating the relationship between (analytic vs. intuitive) cognitive style and trust in Didier Raoult and his treatment. Through three studies (total N after exclusion = 950), we found that a more intuitive cognitive style predicted higher trust in Didier Raoult and his treatment. Moreover, we found that Trust in Raoult was positively associated with belief that truth is political, belief in conspiracy theories, belief in pseudo-medicines and pseudo-medical and conspiratorial beliefs regarding the COVID-19 pandemic. We also found a negative association with knowledge of scientific methods and regard for scientific method over personal experience. However, higher trust in Didier Raoult was not associated with self-reported compliance with official regulations concerning the COVID-19 pandemic.

How do mushroom foragers make safe and efficient decisions under uncertainty, or deal with the genuine risks of misidentification and poisoning? This article is an inquiry into ecological rationality, heuristics, perception, and decision-making in mushroom foraging. By surveying 894 Finnish mushroom foragers, this article illustrates how socially learned rules of thumb and heuristics are used in mushroom foraging, and how simple heuristics are often complemented by more complex and intuitive decision-making. The results illustrate how traditional foraging cultures have evolved precautionary heuristics to deal with uncertainties and poisonous species, and how foragers develop selective attention through experience. The study invites us to consider whether other human foraging cultures might use heuristics similarly, how and why such traditions have culturally evolved, and whether early hunter-gatherers might have used simple heuristics to deal with uncertainty.

Does one’s stance toward evidence evaluation and belief revision have relevance for actual beliefs? We investigate the role of endorsing an actively open-minded thinking style about evidence (AOT-E) on a wide range of beliefs, values, and opinions. Participants indicated the extent to which they think beliefs (Study 1) or opinions (Studies 2 and 3) ought to change according to evidence on an 8-item scale. Across three studies with 1,692 participants from two different sources (Mechanical Turk and Lucid for Academics), we find that our short AOT-E scale correlates negatively with beliefs about topics ranging from extrasensory perception, to respect for tradition, to abortion, to God; and positively with topics ranging from anthropogenic global warming to support for free speech on college campuses. More broadly, the belief that beliefs should change according to evidence was robustly associated with political liberalism, the rejection of traditional moral values, the acceptance of science, and skepticism about religious, paranormal, and conspiratorial claims. However, we also find that AOT-E is more strongly predictive for political liberals (Democrats) than conservatives (Republicans). We conclude that socio-cognitive theories of belief (both specific and general) should take into account people’s beliefs about when and how beliefs should change – that is, meta-beliefs – but that further work is required to understand how meta-beliefs about evidence interact with political ideology.

While they usually should, people do not revise their beliefs more to expert (economist) opinion than to lay opinion. The present research sought to better understand the factors that make it more likely for an individual to change their mind when faced with the opinions of expert economists versus the general public. Across five studies we examined the role that overestimation of knowledge plays in this behavior. We replicated the finding that people fail to privilege the opinion of experts over the public across two different (Study 1) and five different (Study 5) economic issues. We further find that undermining an illusion of both topic-relevant (Studies 2–4) and -irrelevant knowledge (Studies 3 and 4) leads to greater normative belief revision in response to expert rather than lay opinion. We suggest one reason that people fail to revise their beliefs more in response to experts is because people think they know more than they really do.

Most prior research on the external validity of mixed-motive games has studied only one single game version and/or one specific type of real-life prosocial behavior. The present study employs a different approach. We used multiple game trials — with different payoff structures — to measure participants’ behavior in the Prisoner’s Dilemma, the Commons Dilemma, and the Public Goods Dilemma. We then examined the associations between these aggregated game behaviors and a wide set of self-reported prosocial behaviors such as donations, commuting, and environmental behaviors. We also related these prosocial behavior measures to a dispositional measure of prosociality, social value orientation. We report evidence that the weak statistical relationships routinely observed in prior studies are at least partially a consequence of failures to aggregate. More specifically, our results show that aggregation over multiple game trials was especially effective for the Prisoner’s Dilemma, whereas it was somewhat effective for the Public Goods Dilemma. Yet, aggregation on the side of the prosocial behaviors was effective for both these games, as well as for social value orientation. The Commons Dilemma, however, turned out to yield invariably poor relationships with prosocial behavior, regardless of the level of aggregation. Based on these findings, we conclude that the use of multiple instances of game behavior and prosocial behavior is preferable to the use of only a single measurement.

This paper introduces a novel theoretical model and measure of strategic thinking in social decision making. The model distinguishes four strategic orientations: egocentric (thinking about how one’s actions shape one’s outcomes), impact (thinking about how one’s actions shapes others’ outcomes), dependency (thinking about how others’ actions shape one’s outcomes), and altercentric (thinking about how others’ actions shape their outcomes). Applying this model to explain social behavior in the context of the COVID-19 pandemic, an exploratory study finds that the more people think about how their actions shape others’ outcomes, the more likely they are to: (a) comply with social distancing restrictions designed to curb the spread of the virus, and (b) donate money they received in the study to charitable organizations. These findings advance understanding of the multifaceted nature of strategic thinking and highlight the usefulness of the Strategic Thinking Scale for explaining social behavior.

Maximizing is characterized by aspirations for the highest standards. The current study explored the relationship between maximizing and risk-taking tendencies in decisions subject to risk. We propose that people first refer to expectation (i.e., the overall utility expected from an alternative) when taking risky decisions. If expectation clearly identifies the best option, maximizing will not be correlated with risk-taking tendencies. If not, people refer to maximizing to reach a decision. Maximizing will be positively associated with risk-taking tendencies because the “upper bound” of risky options helps achieve the goal of seeking the best. Four studies showed that risk-taking tendencies increased with maximizing when the options had similar expectations (Studies 1 to 3). When expectations between options were clearly different (vs. similar), the positive relationship between maximizing and risk-taking tendencies was reduced (Study 4). These findings provide an insight into how maximizing is related to risk seeking.

In this paper we investigate the effect of moral suasion on ingroup favouritism. We report a well-powered, pre-registered, two-stage 2x2 mixed-design experiment. In the first stage, groups are formed on the basis of how participants answer a set of questions, concerning non-morally relevant issues in one treatment (assorting on non-moral preferences), and morally relevant issues in another treatment (assorting on moral preferences). In the second stage, participants choose how to split a given amount of money between participants of their own group and participants of the other group, first in the baseline setting and then in a setting where they are told to do what they believe to be morally right (moral suasion). Our main results are: (i) in the baseline, participants tend to favour their own group to a greater extent when groups are assorted according to moral preferences, compared to when they are assorted according to non-moral preferences; (ii) the net effect of moral suasion is to decrease ingroup favouritism, but there is also a non-negligible proportion of participants for whom moral suasion increases ingroup favouritism; (iii) the effect of moral suasion is substantially stable across group assorting and four pre-registered individual characteristics (gender, political orientation, religiosity, pro-life vs pro-choice ethical convictions).

The translation of choice attributes into more meaningful information (e.g., from kWh to costs) is a form of choice architecture that is thought to facilitate decision making by providing decision signposts that activate personally relevant but latent objectives and guide decisions towards options that are most congruent with the activated objectives. Here, we investigated the psychological mechanisms that underlie and drive the directional effects of attribute translations on decision making. Across two choice experiments (total N = 973), we provide empirical support for our proposition that attribute translations operate via pre-decisional attention processes. Specifically, we demonstrate that attribute translations focus individuals’ attention on choice options that are most congruent with the concerns highlighted by translations, and that this attentional prioritization of alternatives predicts choice. In addition to the cognitive mechanisms underlying attribute translations, we highlight the choice architectural principles that moderate the effectiveness of translations. We show that the directional effects of attribute translations are driven by the information that translations provide rather than by contextual changes in the decision environment. In line with previous research on evaluability, we find the effectiveness of attribute translations to depend on information format, with translations conveying evaluative information having a larger impact on decision making than translations providing numerical information. The present study is among the first to investigate the decision making processes underlying a choice architectural intervention. It provides insights into the mechanisms that drive and facilitate the signpost effect and renders recommendations for the implementation of attribute translations in policy making.

This paper describes a theory of the variability of risky choice that describes empirical properties of choice data, including sequential effects and systematic violations of response independence. The Markov True and Error (MARTER) model represents the formation and fluctuation of true preferences produced by stochastic variation of parameters over time, which produces changing true preference patterns. This model includes a probabilistic association between true preferences and overt responses due to random error. Computer programs have been developed to simulate data according to this model, to fit data to the TE model, and to test and analyze violations of iid (independent and identical distributions) that are predicted by the model. Data simulated from MARTER models show properties that are characteristic of real data, including violations of iid similar to those observed in previous empirical research. This paper also illustrates how methods based on analysis of binary response proportions do not and in many cases cannot correctly diagnose what model was used to generate the data. The MARTER model is extremely general and neutral with respect to models of risky decision making. For example, the transitive transfer of attention exchange (TAX) model and intransitive Lexicographic Semiorder (LS) models can both be represented as special cases of MARTER, and they can be tested against each other, even when binary choice proportions cannot discriminate which model was used to simulate the data. Software to simulate data according to this model, and to fit data to this model, to test this model, and to compare special case theories are included or linked to this article.

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.