Expertise is a reliable cue for accuracy – experts are often correct in their judgments and opinions. However, the opposite is not necessarily the case – ignorant judges are not guaranteed to err. Specifically, in a question with a dichotomous response option, an ignorant responder has a 50% chance of being correct. In five studies, we show that people fail to understand this, and that they overgeneralize a sound heuristic (expertise signals accuracy) to cases where it does not apply (lack of expertise does not imply error). These studies show that people 1) tend to think that the responses of an ignorant person to dichotomous-response questions are more likely to be incorrect than correct, and 2) they tend to respond the opposite of what the ignorant person responded. This research also shows that this bias is at least partially intuitive in nature, as it manifests more clearly in quick gut responses than in slow careful responses. Still, it is not completely corrected upon careful deliberation. Implications are discussed for rationality and epistemic vigilance.

This research explores the preference for playing order in games in which each ofseveral players draws a random event (e.g., a ball from an urn), with andwithout replacement after each draw. Three studies show that people tend toprefer to draw early regardless of whether the game is with or withoutreplacement, although the expected probability of winning is the sameirrespective of the draw order. The reasons for preferring earlier draws differdepending on the game type. For games without replacement, the biased preferencefor earlier draws is related to multiple motivational factors such as aversionto uncertainty, ambiguity, and uncontrollability. Game valence also affects draworder preference through the misestimation of winning probabilities: people tendto prefer earlier draws in a gain-dominant game (i.e., a higher probability ofwinning) but prefer later draws in a loss-dominant game (i.e., a higherprobability of losing). For games with replacement, preference for earlier drawsis mainly explained by uncertainty aversion, with little bias in probabilityestimations.

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.

Undersampling biases are common in the optimal stopping literature, especiallyfor economic full choice problems. Among these kinds of number-based studies,the moments of the distribution of values that generates the options (i.e., thegenerating distribution) seem to influence participants’ sampling rate.However, a recent study reported an oversampling bias on a different kind ofoptimal stopping task: where participants chose potential romantic partners fromimages of faces (Furl et al., 2019). The authors hypothesised that thisoversampling bias might be specific to mate choice. We preregistered thishypothesis and so, here, we test whether sampling rates across differentimage-based decision-making domains a) reflect different over- or undersamplingbiases, or b) depend on the moments of the generating distributions (as shownfor economic number-based tasks). In two studies (N = 208 andN = 96), we found evidence against the preregisteredhypothesis. Participants oversampled to the same degree across domains (comparedto a Bayesian ideal observer model), while their sampling rates depended on thegenerating distribution mean and skewness in a similar way as number-basedparadigms. Moreover, optimality model sampling to some extent depended on thethe skewness of the generating distribution in a similar way to participants. Weconclude that oversampling is not instigated by the mate choice domain and thatsampling rate in image-based paradigms, like number-based paradigms, depends onthe generating distribution.

Field studies in many domains have found evidence of decision fatigue, a phenomenon describing how decision quality can be impaired by the act of making previous decisions. Debate remains, however, over posited psychological mechanisms underlying decision fatigue, and the size of effects in high-stakes settings. We examine an extensive set of pretrial arraignments in a large, urban court system to investigate how judicial release and bail decisions are influenced by the time an arraignment occurs. We find that release rates decline modestly in the hours before lunch and before dinner, and these declines persist after statistically adjusting for an extensive set of observed covariates. However, we find no evidence that arraignment time affects pretrial release rates in the remainder of each decision-making session. Moreover, we find that release rates remain unchanged after a meal break even though judges have the opportunity to replenish their mental and physical resources by resting and eating. In a complementary analysis, we find that the rate at which judges concur with prosecutorial bail requests does not appear to be influenced by either arraignment time or a meal break. Taken together, our results imply that to the extent that decision fatigue plays a role in pretrial release judgments, effects are small and inconsistent with previous explanations implicating psychological depletion processes.

We study the effects of experimental manipulation of decision mode (rational“brain” vs. affective “heart”) and individualdifference in processing styles (intuition vs. deliberation) on prosocialbehavior. In a survey experiment with a diverse sample of the Swedish population(n = 1,828), we elicited the individuals’ processingstyle and we experimentally manipulated reliance on affect or reason, regardlessof subjects’ preferred mode. Prosocial behavior was measured across aseries of commonly used and incentivized games (prisoner’s dilemma game,public goods game, trust game, dictator game). Our results show that prosocialbehavior increased for the affective (“heart”) decision mode.Further, individual differences in processing style did not predict prosocialbehavior and did not interact with the experimental manipulation.

Drafting is a competitive task in which a set of decision makers choose from a set of resources sequentially, with each resource becoming unavailable once selected. How people make these choices raises basic questions about human decision making, including people’s sensitivity to the statistical regularities of the resource environment, their ability to reason about the behavior of their competitors, and their ability to execute and adapt sophisticated strategies in dynamic situations involving uncertainty. Sports provides one real-world example of drafting behavior, in which a set of teams draft players from an available pool in a well-regulated way. Fantasy sport competitions provide potentially large data sets of drafting behavior. We study fantasy football drafting behavior from the 2017 National Football League (NFL) season based on 1350 leagues hosted by the http://sleeper.app platform. We find people are sensitive to some important environmental regularities in the order in which they draft players, but also present evidence that they use a more narrow range of strategies than is likely optimal in terms of team composition. We find little to no evidence for the use of the complicated but well-documented strategy known as handcuffing, and no evidence of irrational influence from individual-level biases for different NFL teams. We do, however, identify a set of circumstances for which there is clear evidence that people’s choices are strongly influenced by the immediately preceding choice made by a competitor.

Previous research in economics, social psychology, and sociology has producedcompelling evidence that social norms influence behavior. In this paper we applythe Krupka and Weber (2013) norm elicitation procedure and present U.S. andnon-U.S. born subjects with two scenarios for which tipping and punctualitynorms are known to vary across countries. We elicit shared beliefs by havingsubjects match appropriateness ratings of different actions (such as arrivinglate or on time) to another randomly selected participant from the sameuniversity or to a participant who is born in the same country. We also elicitpersonal beliefs without the matching task. We test whether the responses fromthe coordination task can be interpreted as social norms by comparing responsesfrom the coordination game with actual social norms (as identified usingindependent materials such as tipping guides for travelers). We compareresponses elicited with the matching tasks to those elicited without thematching task to test whether the coordination device itself is essential foridentifying social norms. We find that appropriateness ratings for differentactions vary with the reference group in the matching task. Further, the ratingsobtained from the matching task vary in a manner consistent with the actualsocial norms of that reference group. Thus, we find that shared beliefscorrespond more closely to externally validated social norms compared topersonal beliefs. Second, we highlight the importance that reference groups (forthe coordination task) can play.

Can deliberation increase charitable giving when giving is impulsive (i.e., aone-time small gift in response to an immediate appeal)? We conduct two studiesin Israel and Sweden to compare two forms of deliberation, unguided and guided,in their ability to decrease the singularity effect (i.e., giving more to onethan many victims), often evident in impulsive giving. Under unguideddeliberation, participants were instructed to simply think hard before making adonation decision whereas participants in the guided deliberation condition wereasked to think how much different prespecified decision attributes shouldinfluence their decision. We find that both types of deliberation reduce thesingularity effect, as people no longer value the single victim higher than thegroup of victims. Importantly, this is driven by donations being decreased underdeliberation only to the single victim, but not the group of victims. Thus,deliberation affects donations negatively by overshadowing the affectiveresponse, especially in situations in which affect is greatest (i.e., to asingle victim). Last, the results show that neither type of deliberationsignificantly reversed the singularity effect, as people did not help the groupsignificantly more than the single victim. This means that deliberate thinkingdecreased the overall willingness to help, leading to a lower overall valuationof people in need.

In this paper, we show that the presence of numbers in a problem tempts people to perform mathematical operations even when the correct answer requires no math, which we term “mindless math”. In three pre-registered studies across two survey platforms (total N = 3,193), we investigate how mindless math relates to perceived problem difficulty, problem representation, and accuracy. In Study 1, we show that increasing the numeric demands of problems leads to more mindless math (and fewer correct answers). Study 2 shows that this effect is not caused by people being wary of problems that seem too easy. In Study 3, we show that this effect is robust over a wider range of numeric demands, and in the discussion we offer two possible mechanisms that would explain this effect, and the caveat that at even harder levels of numeric demands the effect may invert such that much harder math increases accuracy relative to moderately hard math.

Using data from seven microworld experiments (N = 841), we investigated howparticipants reacted to simulated disasters with different risk profiles in amicroworld. Our central focus was to investigate how the scale of a disasteraffected the choices and response times of these reactions. We find that one-offlarge-scale disasters prompted stronger reactions to move away from the affectedregion than recurrent small-scale adverse events, despite the overall risk of adisaster remaining constant across both types of events. A subset ofparticipants are persistent risk-takers who repeatedly put themselves inharm’s way, despite having all the experience and information required toavoid a disaster. Furthermore, while near-misses prompted a small degree ofprecautionary movement to reduce one’s subsequent risk exposure, directlyexperiencing the costs of the disaster substantially increased the desire tomove away from the affected region. Together, the results point to ways in whichlaboratory risk-taking tasks can be used to inform the kinds of communicationand interventions that seek to mitigate people’s exposure to risk.

Bayesian statistics offers a normative description for how a person should combine their original beliefs (i.e., their priors) in light of new evidence (i.e., the likelihood). Previous research suggests that people tend to under-weight both their prior (base rate neglect) and the likelihood (conservatism), although this varies by individual and situation. Yet this work generally elicits people’s knowledge as single point estimates (e.g., x has a 5% probability of occurring) rather than as a full distribution. Here we demonstrate the utility of eliciting and fitting full distributions when studying these questions. Across three experiments, we found substantial variation in the extent to which people showed base rate neglect and conservatism, which our method allowed us to measure for the first time simultaneously at the level of the individual. While most people tended to disregard the base rate, they did so less when the prior was made explicit. Although many individuals were conservative, there was no apparent systematic relationship between base rate neglect and conservatism within each individual. We suggest that this method shows great potential for studying human probabilistic reasoning.

Decades of research show that (i) social value orientation (SVO)is related to important behavioral outcomes such as cooperation and charitablegiving, and (ii) individuals differ in terms of SVO. Aprominent scale to measure SVO is the social value orientation slider measure(SVOSM). The central premise is that SVOSM captures a stable trait. But it isunknown how reliable the SVOSM is over repeated measurements more than one weekapart. To fill this knowledge gap, we followed a sample of N =495 over 6 months with monthly SVO measurements. We find that continuous SVOscores are similarly distributed (Anderson-Darling k-sample p =0.57) and highly correlated (r ≥ 0.66) across waves. Theintra-class correlation coefficient of 0.78 attests to a high test-retestreliability. Using multilevel modeling and multiple visualizations, wefurthermore find that one’s prior SVO score is highly indicative of SVOin future waves, suggesting that the slider measure consistently capturesone’s SVO. Our analyses validate the slider measure as a reliable SVOscale.

Misinformation presents a significant societal problem. To measureindividuals’ susceptibility to misinformation and study its predictors,researchers have used a broad variety of ad-hoc item sets, scales, questionframings, and response modes. Because of this variety, it remains unknownwhether results from different studies can be compared (e.g., in meta-analyses).In this preregistered study (US sample; N = 2,622), we comparefive commonly used question framings (eliciting perceived headline accuracy,manipulativeness, reliability, trustworthiness, and whether a headline is realor fake) and three response modes (binary, 6-point and 7-point scales), usingthe psychometrically validated Misinformation Susceptibility Test (MIST). Wetest 1) whether different question framings and response modes yield similarresponses for the same item set, 2) whether people’s confidence in theirprimary judgments is affected by question framings and response modes, and 3)which key psychological factors (myside bias, political partisanship, cognitivereflection, and numeracy skills) best predict misinformation susceptibilityacross assessment methods. Different response modes and question framings yieldsimilar (but not identical) responses for both primary ratings and confidencejudgments. We also find a similar nomological net across conditions, suggestingcross-study comparability. Finally, myside bias and political conservatism werestrongly positively correlated with misinformation susceptibility, whereasnumeracy skills and especially cognitive reflection were less important(although we note potential ceiling effects for numeracy). We thus find moresupport for an “integrative” account than a “classicalreasoning” account of misinformation belief.

Previous research has focused on studying the endowment effect for transactions that take place in the present. Many real-world transactions, however, are delayed into the future (i.e., people agree to buy or sell, but the actual transaction does not materialize until a later time). Here we investigate how transaction timing affects the endowment effect. In five studies, we show that the endowment effect systematically increases as transactions are delayed into the future. Specifically, buying prices significantly decrease as the transaction is delayed, while selling prices remain constant, resulting in an amplified endowment effect (Experiment 1). This pattern is not produced by a discounting of the money involved in the transaction (Experiment 2), and it holds across different types of items (Experiment 3). We also show that the phenomenon cannot be explained by sellers anticipating becoming increasingly attached to the items over time (Experiment 4). Finally, we demonstrate that this increased endowment effect in the future holds in the field, in the context of a real market and with real transactions (Experiment 5).

One of the many established predictors of conspiracy beliefs is reflective thinking, but no meta-analysis so far has examined this relationship. In the current meta-analysis of published and unpublished correlational data (145 samples, 181 effect sizes), we found a significant negative association between reflective thinking and conspiracy beliefs with a medium-level effect size (r = –.189) . Similar levels of correlations were found across different types of measures (self-report vs. performance-based) and conspiracy beliefs (generic vs. specific). Further, no evidence suggested publication bias in this body of work. Suggestions for future research are discussed.

Do people think that there is such a thing as too much money? The present research investigated this question in the context of hypothetical lottery wins. By employing a mental simulation approach, we were able to examine how people respond to increasing envisioned jackpot amounts, and whether there are individual differences in people’s reactions. Across five empirical studies (total N = 1,504), we consistently found that, overall, the relationship between imagined lottery wins and expected happiness is characterized by an inverted U-shaped curve, with expected happiness being highest around an envisioned win of roughly 10 million pounds. Both lower and higher envisioned wins reduced participants’ overall expected happiness. In addition to this overall pattern, we identified three clusters of participants who react differently to expected increases in wealth. These clusters mainly differed in terms of how soon the top of the expected happiness curve was reached, and if and when the curve started to drop. Finally, we also found some interesting cluster differences in terms of participants’ prosocial and proself motivations.

Games of pure mutual interest require players to coordinate their choices withoutbeing able to communicate. One way to achieve this is through team-reasoning,asking ‘what should we choose’, rather than just assessingone’s own options from an individual perspective. It has been suggestedthat team-reasoning is more likely when individuals are encouraged to think ofthose they are attempting to coordinate with as members of an in-group. In twostudies, we examined the effects of group identity, measured by the‘Inclusion of Other in Self’ (IOS) scale, on performance innondescript coordination games, where there are several equilibria but nodescriptions that a player can use to distinguish any one strategy from theothers apart from the payoff from coordinating on it. In an online experiment,our manipulation of group identity did not have the expected effect, but wefound a correlation of .18 between IOS and team-reasoning-consistent choosing.Similarly, in self-reported strategies, those who reported trying to pick anoption that stood out (making it easier to coordinate on) also reported higherIOS scores than did those who said they tended to choose the option with thelargest potential payoff. In a follow-up study in the lab, participants playedeither with friends or with strangers. Experiment 2 replicated the relationshipbetween IOS and team-reasoning in strangers but not in friends. Instead,friends’ behavior was related to their expectations of what theirpartners would do. A hierarchical cluster analysis showed that 46.4% ofstrangers played a team reasoning strategy, compared to 20.6% of friends. Wesuggest that the strangers who group identify may have been team reasoning butfriends may have tried to use their superior knowledge of their partners to tryto predict their strategy.

This paper uses the COVID-19 health crisis to study how individual preferences respond to generalized traumatic events. We review previous literature on natural and man-made disasters. Using incentive-compatible tasks, we simultaneously estimate risk and ambiguity aversion, time discounting, present bias, and prudence parameters before, during, and after the COVID-19 lockdown in France. We find patience, risk aversion, and ambiguity aversion fell during lockdown, then gradually returned toward their initial levels 4 months later. These results have implications for health and economic policies, and deepen our understanding of the responses – and resilience – of economic preferences to traumatic events.

We report on three pre-registered studies testing whether people in the positionof describing a decision problem to decision-makers exploit this opportunity fortheir benefit, by choosing descriptions that may be potentially beneficial forthemselves. In Study 1, recipients of an extreme dictator game (where dictatorscan either take the whole pie for themselves or give it entirely to thereceiver) are asked to choose the instructions used to introduce the game todictators, from six different instructions known from previous research toaffect dictators’ decisions. The results demonstrate that some dictatorgame recipients tend to choose instructions that make them more likely toreceive a higher payoff. Study 2 shows that people who choose descriptions thatmake them more likely to receive a higher payoff indeed believe that they willreceive a higher payoff. Study 3 shows that receivers are more likely thandictators to choose these self-serving descriptions. In sum, our work suggeststhat some people choose descriptions that are beneficial to themselves; we alsofound some evidence that deliberative thinking and young age are associated withthis tendency.