The degree to which individuals prefer smaller sooner versus larger delayed rewards serves as a powerful predictor of their impulsivity towards a number of different kinds of rewards. Here we test the limits of its predictive ability within a variety of cognitive and social domains. Across several large samples of subjects, individuals who prefer smaller more immediate rewards (steeper discounters) are less reflective (or more impulsive) in their choices, preferences, and beliefs. First, steeper discounters used more automatic, less controlled choice strategies, giving more intuitive but incorrect responses on the Cognitive Reflection Test (replicating previous findings); employing a suboptimal probability matching heuristic for a one-shot gamble (rather than maximizing their probability of reward); and relying less on optimal planning in a two-stage reinforcement learning task. Second, steeper discounters preferred to consume information that was less complex and multi-faceted, as suggested by their self-reported Need for Cognitive Closure, their use of short-form social media (i.e., Twitter), and their preferred news sources (in particular, whether or not they preferred National Public Radio over other news sources). Third, steeper discounters had interpersonal and religious beliefs that are associated with reduced epistemic complexity: they were more likely to believe that the behavior of others could be explained by fixed rather than dynamic factors, and they believed more strongly in God and in the afterlife. Together these findings provide evidence for a link between individual differences in temporal discounting for monetary rewards and preferences for the path of least resistance (less reflective and/or more automatic modes of processing) across a variety of domains.

We consider the wisdom of the crowd situation in which individuals make binary decisions, and the majority answer is used as the group decision. Using data sets from nine different domains, we examine the relationship between the size of the majority and the accuracy of the crowd decisions. We find empirically that these calibration curves take many different forms for different domains, and the distribution of majority sizes over decisions in a domain also varies widely. We develop a growth model for inferring and interpreting the calibration curve in a domain, and apply it to the same nine data sets using Bayesian methods. The modeling approach is able to infer important qualitative properties of a domain, such as whether it involves decisions that have ground truths or are inherently uncertain. It is also able to make inferences about important quantitative properties of a domain, such as how quickly the crowd accuracy increases as the size of the majority increases. We discuss potential applications of the measurement model, and the need to develop a psychological account of the variety of calibration curves that evidently exist.

The literature on behavioral decision-making and negotiations to date usually advocates first-mover advantage in distributive negotiations, and bases this preference on the anchoring heuristic. In the following paper, we suggest that the preference for moving first vs. moving second in negotiations may not be as clear-cut as presumed, especially in situations characterized by information asymmetry between negotiating counterparts. In Study 1, we examined people’s initiation preferences and found that unless taught otherwise, people intuitively often prefer to move second. In Studies 2–4, we experimentally tested the suggested advantage of moving second, and demonstrated that in information-asymmetry scenarios – when one party has perfect background information and the other has none — it is actually preferable for both counterparts not to give the first offer while negotiating. We discuss the implications of our findings on the field of negotiation and decision-making, and lay the groundwork for future studies examining this issue.

This article proposes an Item Response Theoretical (IRT) forecasting model that incorporates proper scoring rules and provides evaluations of forecasters’ expertise in relation to the features of the specific questions they answer. We illustrate the model using geopolitical forecasts obtained by the Good Judgment Project (GJP) (see Mellers, Ungar, Baron, Ramos, Gurcay, Fincher, Scott, Moore, Atanasov, Swift, Murray, Stone & Tetlock, 2014). The expertise estimates from the IRT model, which take into account variation in the difficulty and discrimination power of the events, capture the underlying construct being measured and are highly correlated with the forecasters’ Brier scores. Furthermore, our expertise estimates based on the first three years of the GJP data are better predictors of both the forecasters’ fourth year Brier scores and their activity level than the overall Brier scores obtained and Merkle’s (2016) predictions, based on the same period. Lastly, we discuss the benefits of using event-characteristic information in forecasting.

This paper investigates how the numerosity bias influences individuals’ allocation of resources between themselves and others, using the backdrop of the traditional dictator game. Across four studies including both hypothetical and real exchanges of money, we show that the form of the numerical value representing the quantity of the resource (e.g., $20 vs 2000 cents) systematically biases the decision-maker to perceive the quantity s/he is thinking of allocating as being “less than adequate” or “more than adequate”. Essentially, such a biased perception of adequacy with respect to the quantity of the resource consequently influences the decision-maker’s final allocation decision. We attribute this systematic bias to the “numerosity” of the resource. We find that bigger numerical values representing quantity (e.g., 2000 cents) bias decision-makers to over-infer the quantity, thus inducing them to allocate less to the entities they are focusing on.

In a world that offers children abundant activities from which to choose, understanding how to motivate children to engage longer in productive activities is crucial. This paper examines how the offered assortment size affects children’s engagement with their chosen option. In the first study, I show children prefer to choose from a larger set even though they think doing so is more difficult. Then, in Studies 2 and 3, four- to five-year-old children choose from either a small set (two options) or a large set (six or seven options). In study 2, children choose a book to look at and I measure how long they look at it. In Study 3, children choose a game to play with and I measure how long they play. Children spend more time looking at the book and playing with the game they choose from the small versus the large set. By contrast, the size of the choice set does not affect food consumption. Such findings contribute to our understanding of young children’s decision-making and have important implications for determining the optimal assortment size to offer children to increase engagement with desirable activities.

Many decisions in everyday life involve a choice between exploring options that are currently unknown and exploiting options that are already known to be rewarding. Previous work has suggested that humans solve such “explore-exploit” dilemmas using a mixture of two strategies: directed exploration, in which information seeking drives exploration by choice, and random exploration, in which behavioral variability drives exploration by chance. One limitation of this previous work was that, like most studies on explore-exploit decision making, it focused exclusively on the domain of gains, where the goal was to maximize reward. In many real-world decisions, however, the goal is to minimize losses and it is well known from Prospect Theory that behavior can be quite different in this domain. In this study, we compared explore-exploit behavior of human subjects under conditions of gain and loss. We found that people use both directed and random exploration regardless of whether they are exploring to maximize gains or minimize losses and that there is quantitative agreement between the exploration parameters across domains. Our results also revealed an overall bias towards the more uncertain option in the domain of losses. While this bias towards uncertainty was qualitatively consistent with the predictions of Prospect Theory, quantitatively we found that the bias was better described by a Bayesian account, in which subjects had a prior that was optimistic for losses and pessimistic for gains. Taken together, our results suggest that explore-exploit decisions are driven by three independent processes: directed and random exploration, and a baseline uncertainty seeking that is driven by a prior.

People often object to inequity; they react negatively to receiving less than others (disadvantageous inequity aversion), and more than others (advantageous inequity aversion). Here we study people’s folk intuitions about inequity aversion: what do people infer about others’ fairness concerns, when they observe their reactions to disadvantageous or advantageous inequity? We hypothesized that, people would not intuitively regard disadvantageous inequity aversion by itself as being rooted in fairness, but they would regard advantageous inequity aversion by itself as being rooted in fairness. In four studies, we used vignettes describing inequity aversion of a made up alien species to assess people’s folk intuitions about inequity aversion. The studies supported our main hypothesis that disadvantageous inequity aversion, without advantageous inequity aversion, does not fit people’s folk conception of fairness. Instead, participants reported it to be rooted in envy. According to these results, the claim that disadvantageous inequity aversion reveals a concern with fairness, does not readily accord with people’s intuitions. We connect these findings to other pieces of evidence in the literatures of behavioral economics, developmental psychology, and social psychology, indicating that lay people’s intuitions may be on the mark in this case. Specifically, unlike advantageous inequity aversion, disadvantageous inequity aversion need not be rooted in a sense of fairness.

There is a growing interest in studying individual differences in choices that involve trading off reward amount and delay to delivery because such choices have been linked to involvement in risky behaviors, such as substance abuse. The most ubiquitous proposal in psychology is to model these choices assuming delayed rewards lose value following a hyperbolic function, which has one free parameter, named discounting rate. Consequently, a fundamental issue is the estimation of this parameter. The traditional approach estimates each individual’s discounting rate separately, which discards individual differences during modeling and ignores the statistical structure of the population. The present work adopted a different approximation to parameter estimation: each individual’s discounting rate is estimated considering the information provided by all subjects, using state-of-the-art Bayesian inference techniques. Our goal was to evaluate whether individual discounting rates come from one or more subpopulations, using Mazur’s (1987) hyperbolic function. Twelve hundred eighty-four subjects answered the Intertemporal Choice Task developed by Kirby, Petry and Bickel (1999). The modeling techniques employed permitted the identification of subjects who produced random, careless responses, and who were discarded from further analysis. Results showed that one-mixture hierarchical distribution that uses the information provided by all subjects suffices to model individual differences in delay discounting, suggesting psychological variability resides along a continuum rather than in discrete clusters. This different approach to parameter estimation has the potential to contribute to the understanding and prediction of decision making in various real-world situations where immediacy is constantly in conflict with magnitude.

Fast-and-frugal trees (FFTs) are simple algorithms that facilitate efficient and accurate decisions based on limited information. But despite their successful use in many applied domains, there is no widely available toolbox that allows anyone to easily create, visualize, and evaluate FFTs. We fill this gap by introducing the R package FFTrees. In this paper, we explain how FFTs work, introduce a new class of algorithms called fan for constructing FFTs, and provide a tutorial for using the FFTrees package. We then conduct a simulation across ten real-world datasets to test how well FFTs created by FFTrees can predict data. Simulation results show that FFTs created by FFTrees can predict data as well as popular classification algorithms such as regression and random forests, while remaining simple enough for anyone to understand and use.

According to the recognition heuristic (RH), for decision domains where recognition is a valid predictor of a choice criterion, recognition alone is used to make inferences whenever one object is recognized and the other is not, irrespective of further knowledge. Erdfelder, Küpper-Tetzel, and Mattern (2011) questioned whether the recognition judgment itself affects decisions or rather the memory strength underlying it. Specifically, they proposed to extend the RH to the memory state heuristic (MSH), which assumes a third memory state of uncertainty in addition to recognition certainty and rejection certainty. While the MSH already gathered significant support, one of its basic and more counterintuitive predictions has not been tested so far: In guessing pairs (none of the objects recognized), the object more slowly judged as unrecognized should be preferred, since it is more likely to be in a higher memory state. In this paper, we test this prediction along with other recognition latency predictions of the MSH, thereby adding to the body of research supporting the MSH.

People often perform poorly on stock-flow reasoning tasks, with many (but not all) participants appearing to erroneously match the accumulation of the stock to the inflow – a response pattern attributed to the use of a “correlation heuristic”. Efforts to improve understanding of stock-flow systems have been limited by the lack of a principled approach to identifying and measuring individual differences in reasoning strategies. We present a principled inferential method known as Hierarchical Bayesian Latent Mixture Models (HBLMMs) to analyze stock-flow reasoning. HBLMMs use Bayesian inference to classify different patterns of responding as coming from multiple latent populations. We demonstrate the usefulness of this approach using a dataset from a stock-flow drawing task which compared performance in a problem presented in a climate change context, a problem in a financial context, and a problem in which the financial context was used as an analogy to assist understanding in the climate problem. The hierarchical Bayesian model showed that the proportion of responses consistent with the “correlation heuristic” was lower in the financial context and financial analogy context than in the pure climate context. We discuss the benefits of HBLMMs and implications for the role of contexts and analogy in improving stock-flow reasoning.

This paper experimentally investigates a well-known anomaly in portfolio management, i.e., the fact that paper losses are realized less than paper gains (disposition effect). I confirm the existence of the disposition effect in a simple risky task in which choices are taken sequentially. However, when choices are planned ahead and a contingent plan is defined, a reversal in the disposition effect is observed.

Two psychological sources of uncertainty bear implications for judgment and decision-making: external uncertainty is seen as stemming from properties of the world, whereas internal uncertainty is seen as stemming from lack of knowledge. The apparent source of uncertainty can be conveyed through linguistic markers, such as the pronoun of probability phrases (e.g., I am uncertain vs. It is uncertain). Here, we investigated whether and when speakers use different pronoun subjects as such linguistic markers (Exp. 1 and 2) and what hearers infer from them (Exp. 3 and 4). Speakers more often described higher probabilities and knowable outcomes with internal probability phrases. In dialogue, speakers mirrored the source of their conversational partner. Markers of the source had a main effect or interacted with the probability conveyed and speaker expertise to shape the judgments and decisions of hearers. For example, experts voicing an internal probability phrase were judged as more knowledgeable than experts using an external probability phrase whereas the result was the opposite for lay speakers. We discuss how these findings inform our understanding of subjective uncertainty and uncertainty communication theories.

Good judgment is often gauged against two gold standards – coherence and correspondence. Judgments are coherent if they demonstrate consistency with the axioms of probability theory or propositional logic. Judgments are correspondent if they agree with ground truth. When gold standards are unavailable, silver standards such as consistency and discrimination can be used to evaluate judgment quality. Individuals are consistent if they assign similar judgments to comparable stimuli, and they discriminate if they assign different judgments to dissimilar stimuli. We ask whether “superforecasters”, individuals with noteworthy correspondence skills (see Mellers et al., 2014) show superior performance on laboratory tasks assessing other standards of good judgment. Results showed that superforecasters either tied or out-performed less correspondent forecasters and undergraduates with no forecasting experience on tests of consistency, discrimination, and coherence. While multifaceted, good judgment may be a more unified than concept than previously thought.

This research investigated how different forms of overconfidence correlate with age. Contrary to stereotypes that young people are more overconfident, the results provide little evidence that overestimation of one’s performance or overplacement of one’s performance relative to that of others is correlated with age. Instead, the results suggest that precision in judgment (confidence that one knows the truth) increases with age. This result is strongest for probabilistic elicitations, and not present in quantile elicitations or reported confidence intervals. The results suggest that a lifetime of experience, rather than leading to better calibration, instead may increase our confidence that we know what we’re talking about.

When decisions involve opting in or out of competition many decision makers will opt-in even when doing so leads to losses on average. In the current paper, we examine the generality of this effect in risky choices not involving competition. We found that re-framing a sure (certain) zero option as an option to observe the results of the other options without choosing would lead to increased consequential choice (i.e., increased selection of risky options rather than the zero option). Specifically, in two studies we compared the rate of consequential choice in a novel paradigm where decision makers decide to observe or to choose with consequence from a set of risky options (decisions-to-engage) to a full-feedback decisions-from-feedback paradigm where the choice set included a labeled sure zero option. Compared to decisions-from-feedback, participants were more likely to choose from mixed (risky) gambles with consequence (over a zero outcome) in decisions-to-engage. This occurred irrespective of whether doing so was advantageous (i.e., when choice led to monetary gains on average) or disadvantageous (i.e., when choice led to monetary losses on average), and when descriptions of the options outcomes and probabilities were provided (Study 2). These findings provide an important boundary condition for the positive effects of experience on the quality of choice, and suggest that decision makers’ preference for agency can sometimes induce poorer choices.

The current studies investigated how a manipulation in joint outcome influenced individuals’ responses to pro-equality/individualistic decision makers. In Study 1 (N = 175), we examined the impact of whether equal distribution led to maximum joint outcome or not on individuals’ evaluations of, and reactions to, partners choosing either equal or individualistic distributions. In Study 2 (N = 164), we further examined the moderating roles of individual differences in general social value orientation (SVO) and preferences for joint outcome (vs. equality). Important findings include: a) individuals evaluated a pro-equality partner as less warm when equal distribution did not afford maximum joint outcome than when it did; b) individuals, especially those who scored high on preferences for joint outcome (relative to equality), were less likely to chose equal distribution when equality did not maximize joint outcome than when it did; and c) individuals who preferred joint outcome to equality evaluated individualistic partners as warmer when equal distribution did not yield maximum joint outcome than when it did. Theoretical and practical implications of these findings are discussed.

In line with earlier research, a multi-phase study found a significant positive association between a widely used measure of trait disgust and people’s tendency to favor absolutist (non-consequentialist) restrictions on genetically modified food (GMF). However, a more nuanced high-granularity approach showed that it was individual sensitivity to fear (specifically, a tendency to feel creeped out by strange and subtly deviant events) rather than a tendency to be disgusted (orally inhibited) by these events that was a unique predictor of absolutist opposition to GMF and other types of new technology. This finding is consistent with prior theorizing and research demonstrating fear to be “the major determiner of public perception and acceptance of risk for a wide range of hazards” related to new technology (e.g., nuclear power) (Slovic & Peters, 2006, p. 322). The present study calls attention to the importance of conducting future assessments of disgust (and other affective constructs) in a manner that, among other things, recognizes the substantial disconnect between theoretical and lay meanings of the term and illustrates how a policy-guiding result may arise from a sheer miscommunication between a researcher and a subject.

Many people exhibit inconsistent preferences when they make choices based on descriptive summaries as compared to choices based on prior experiences. Theoretically, factors that promote more deliberative and skilled decision making (e.g., statistical numeracy) should also tend to promote more consistent choices and preferences regardless of information presentation formats. To test this hypothesis, in two studies I investigated individual differences in information search strategies (e.g., the amount and direction of information search) while estimating the degree to which numeracy predicted risky choice consistency across (a) decisions-from-description and (b) the decisions-from-samples. Results from Study 1 revealed that numeracy was generally associated with more extensive sampling and greater choice consistency across paradigms. Instead of reflecting differences in logical maximizing strategies (e.g., calculating expected values), analyses indicated that highly-numerate participants largely generated consistent choices by relying on heuristic-type processes (e.g., alternated between options less and exploring options with higher outcome variability more). In Study 2, the relationship between numeracy and choice consistency was eliminated when all participants were forced to make choices after experiencing the same fixed amount of sampling (i.e., provided the same amount of information). Taken together, the results of both studies converge with and extend previous findings (e.g., Skilled Decision Theory), indicating that numerate participants may generally exhibit more consistent preferences and choices via deliberatative heuristic search during decision making.