The Future of Decisions From Experience: Connecting Real-World Decision Problems to Cognitive Processes.

In many important real-world decision domains, such as finance, the environment, and health, behavior is strongly influenced by experience. Renewed interest in studying this influence led to important advancements in the understanding of these decisions from experience (DfE) in the last 20 years. Building on this literature, we suggest ways the standard experimental design should be extended to better approach important real-world DfE. These extensions include, for example, introducing more complex choice situations, delaying feedback, and including social interactions. When acting upon experiences in these richer and more complicated environments, extensive cognitive processes go into making a decision. Therefore, we argue for integrating cognitive processes more explicitly into experimental research in DfE. These cognitive processes include attention to and perception of numeric and nonnumeric experiences, the influence of episodic and semantic memory, and the mental models involved in learning processes. Understanding these basic cognitive processes can advance the modeling, understanding and prediction of DfE in the laboratory and in the real world. We highlight the potential of experimental research in DfE for theory integration across the behavioral, decision, and cognitive sciences. Furthermore, this research could lead to new methodology that better informs decision-making and policy interventions.

Fenneman et al.'s (2022) review of formal impulsivity models: Implications for theory and measures of impulsivity.

In Fenneman et al.'s (2022) review of theories and integrated impulsivity model, the authors distinguish between information impulsivity (i.e., acting without considering consequences) and temporal impulsivity (i.e., the tendency to pick sooner outcomes over later ones). The authors find that both types of impulsivity can be adaptive in different contexts. For example, when individuals experience scarcity of resources or when they are close to a minimum level of reserves (critical threshold). In this commentary, we extend their findings to a discussion about the measurement of impulsivity. We argue that a common method for measuring temporal impulsivity in which people make decisions between outcomes that are spaced out in time (intertemporal choice tasks), puts individuals in a specific context that is unlikely to generalize well to other situations. Furthermore, trait measures of impulsivity may only be modestly informative about future impulsive behavior because they largely abstract away from important context. To address these issues, we advocate for the development of dynamic measures of the two types of impulsivity. We argue that measuring temporal impulsivity in naturalistic contexts with varying environmental and state parameters could provide insights into whether individuals (i.e., humans and nonhuman animals) react to environmental changes adaptively, while trait measures of impulsivity more generally should collect and provide more contextual information. Dynamic measurement of different types of impulsivity will also allow for more discussion about adaptive impulsive responses in different contexts, which could help combat the stigmatization of various disorders associated with impulsivity. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

A systematic investigation into the reliability of inter-temporal choice model parameters.

Decades of work have been dedicated to developing and testing models that characterize how people make inter-temporal choices. Although parameter estimates from these models are often interpreted as indices of latent components of the choice process, little work has been done to examine their reliability. This is problematic because estimation error can bias conclusions that are drawn from these parameter estimates. We examine the reliability of parameter estimates from 11 prominent models of inter-temporal choice by (a) fitting each model to data from three previous experiments with designs representative of those typically used to study inter-temporal choice, (b) examining the consistency of parameters estimated for the same person based on different choice sets, and (c) conducting a parameter recovery analysis. We find generally low correlations between parameters estimated for the same person from the different choice sets. Moreover, parameter recovery varies considerably between models and the experimental designs upon which parameter estimates are based. We conclude that many parameter estimates reported in previous research are likely unreliable and provide recommendations on how to enhance the reliability of inter-temporal choice models for measurement purposes.

Patterns of choice adaptation in dynamic risky environments.

An important aspect of making good decisions is the ability to adapt to changes in the values of available choice options, and research suggests that we are poor at changing behavior and adapting our choices successfully. The current paper contributes to clarifying the role of memory on learning and successful adaptation to changing decision environments. We test two aspects of changing decision environments: the direction of change and the type of feedback. The direction of change refers to how options become more or less rewarding compared to other options, over time. Feedback refers to whether full or partial information about decision outcomes is received. Results from behavioral experiments revealed a robust effect of the direction of change: risk that becomes more rewarding over time is harder to detect than risk that becomes less rewarding over time; even with full feedback. We rely on three distinct computational models to interpret the role of memory on learning and adaptation. The distributions of individual model parameters were analyzed in relation to participants' ability to successfully adapt to the changing conditions of the various decision environments. Consistent across the three models and two distinct data sets, results revealed the importance of recency as an individual memory component for choice adaptation. Individuals relying more on recent experiences were more successful at adapting to change, regardless of its direction. We explain the value and limitations of these findings as well as opportunities for future research.

How to use a multicriteria comparison procedure to improve modeling competitions: A comment on Erev et al. (2017).

Modeling competitions are a promising method for advancing psychological science. In this commentary to Erev et al. (Psychological Review, 2017, 124, p. 369), we highlight how this promise could be enhanced through modifying competition structures to produce insights more directly in line with the goals of promoting psychological knowledge. We argue that a single criterion on which models is compared limits the diversity of models entered into competitions, restricting the number and type of insights that can be gained consequently. We propose an alternative competition structure with multiple evaluative criteria and outline a quantitative selection method for choosing a winner. Our proposed competition structure has the advantages of (a) increasing the diversity of models entered, (b) incentivizing desirable qualities of models, (c) disambiguating competition winners, and (d) enhancing the impact and possible insights gained from competitions, all these while allowing flexibility for competition organizers to emphasize specific qualities of models. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

The Role of Personal Experience and Prior Beliefs in Shaping Climate Change Perceptions: A Narrative Review.

Global climate change is increasing the frequency and intensity of extreme weather events such as heatwaves, droughts, and flooding. This is the primary way many individuals experience climate change, which has led researchers to investigate the influence of personal experience on climate change concern and action. However, existing evidence is still limited and in some cases contradictory. At the same time, behavioral decision research has highlighted the importance of pre-existing values and beliefs in shaping how individuals experience changes in environmental conditions. This is in line with theories of motivated reasoning, which suggest that people interpret and process information in a biased manner to maintain their prior beliefs. Yet, the evidence for directional motivated reasoning in the context of climate change beliefs has recently been questioned. In the current paper, we critically review the literature on the interrelationships between personal experience of local weather anomalies, extreme weather events and climate change beliefs. Overall, our review shows that there is some evidence that local warming can generate climate change concern, but the capacity for personal experience to promote action may rely upon the experience first being attributed to climate change. Rare extreme weather events will likely have limited impact on judgments and decisions unless they have occurred recently. However, even recent events may have limited impact among individuals who hold strong pre-existing beliefs rejecting the reality of climate change. We identify limitations of existing research and suggest directions for future work.

An Attempt to Correct Erroneous Ideas Among Teacher Education Students: The Effectiveness of Refutation Texts.

There is sound evidence about the high prevalence of misconceptions about education among pre-service teachers. This trend continues after students complete the degree in education and once they are in the exercise of their profession. In fact, several studies show that these misconceptions are widespread among in-service teachers. Erroneous ideas about education may divert material and human resources to poor grounded methods and teaching tools, compromising the quality of education. Strategies to debunk misconceptions among future teachers, who may not have a firm position about many educational issues, might contribute to reversing this trend. The main goal of the present study was to assess the efficacy of refutation texts in the correction of misconceptions among pre-service teachers. As in previous studies with in-service teachers, refutation texts were effective in reducing participants' endorsement of misconceptions. But this effect was short-lived and did not affect participants' intention to use educational methods that are based on the misconceptions addressed in the refutation texts.

Choice rates are independent from perceived patterns (when patterns are not obvious): A reply to Plonsky and Teodorescu.

In Ashby, Konstantinidis, and Yechiam (2017) we argued that the variance in people's choices in decisions from experience stems from uncertainty about preferences. This was confirmed by high correlations between the variance in experiential choices and subsequent one-shot policy decisions: both showing considerable diversification. In the present paper we address a comment regarding our paper by Plonsky and Teodorescu (2020). These authors suggested that variance in experiential choices is driven by responses to perceived patterns in prior outcomes (rather than individuals' preferences), and that these responses can also drive subsequent policy decisions. This was supported by an apparent "wavy recency" effect in our data indicatory of responses to patterns, and by an experiment showing that outcome patterns affected subsequent policy decisions. We demonstrate that our study results do not in fact show a significant wavy recency. We do find positive recency but it is very poorly correlated with the overall choice rates. Hence, we contend that the variance in choice rates mostly reflects one's preferences when there are no obvious patterns. Moreover, we argue that because Plonsky and Teodorescu's experimental manipulation was confounded with the frequency of relatively positive/negative outcomes, their results do not conclusively show an effect of response to patterns on subsequent policies.

The effectiveness of refutation texts to correct misconceptions among educators.

Teachers around the world hold a considerable number of misconceptions about education. Consequently, schools can become epicenters for dubious practices that might jeopardize the quality of teaching and negatively influence students' wellbeing. The main objective of this study was to assess the efficacy of refutation texts in the correction of erroneous ideas among in-service teachers. The results of Experiment 1 indicate that refutation texts can be an effective means to correct false ideas among educators, even for strongly endorsed misconceptions. However, the results of Experiment 2 suggest that these effects may be short-lived. Furthermore, attempts to correct misconceptions seemed to have no beneficial effect on teachers' intention to implement educational practices that are based on those erroneous beliefs. The implications of these results for the training of preservice and in-service teachers are discussed. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Simultaneous underweighting and overestimation of rare events: Unpacking a paradox.

We investigated previous findings suggesting a paradoxical inconsistency of people's beliefs and choices: When making decisions under uncertainty, people seem to both overestimate the probability of rare events in their judgments and underweight the probability of the same rare events in their choices. In our reexamination, we found that people's beliefs are consistent with their decisions, but they do not necessarily correspond with the environment. Both overestimation and underweighting of the rare event seemed to result from (most, but not all) participants' mistaken belief that they can infer and exploit sequential patterns in a static environment. In addition, we found that such inaccurate representations can be improved through incentives. Finally, detailed analysis suggested a mixture of individual-level response patterns, which can give rise to an erroneous interpretation of group-level patterns. Our results offer an explanation for why beliefs and decisions can appear contradictory and present challenges to some current models of decisions under uncertainty. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Putting bandits into context: How function learning supports decision making.

The authors introduce the contextual multi-armed bandit task as a framework to investigate learning and decision making in uncertain environments. In this novel paradigm, participants repeatedly choose between multiple options in order to maximize their rewards. The options are described by a number of contextual features which are predictive of the rewards through initially unknown functions. From their experience with choosing options and observing the consequences of their decisions, participants can learn about the functional relation between contexts and rewards and improve their decision strategy over time. In three experiments, the authors explore participants' behavior in such learning environments. They predict participants' behavior by context-blind (mean-tracking, Kalman filter) and contextual (Gaussian process and linear regression) learning approaches combined with different choice strategies. Participants are mostly able to learn about the context-reward functions and their behavior is best described by a Gaussian process learning strategy which generalizes previous experience to similar instances. In a relatively simple task with binary features, they seem to combine this learning with a probability of improvement decision strategy which focuses on alternatives that are expected to lead to an improvement upon a current favorite option. In a task with continuous features that are linearly related to the rewards, participants seem to more explicitly balance exploration and exploitation. Finally, in a difficult learning environment where the relation between features and rewards is nonlinear, some participants are again well-described by a Gaussian process learning strategy, whereas others revert to context-blind strategies. (PsycINFO Database Record

Task complexity moderates the influence of descriptions in decisions from experience.

Decisions-makers often have access to a combination of descriptive and experiential information, but limited research so far has explored decisions made using both. Three experiments explore the relationship between task complexity and the influence of descriptions. We show that in simple experience-based decision-making tasks, providing congruent descriptions has little influence on task performance in comparison to experience alone without descriptions, since learning via experience is relatively easy. In more complex tasks, which are slower and more demanding to learn experientially, descriptions have stronger influence and help participants identify their preferred choices. However, when the task gets too complex to be concisely described, the influence of descriptions is reduced hence showing a non-monotonic pattern of influence of descriptions according to task complexity. We also propose a cognitive model that incorporates descriptive information into the traditional reinforcement learning framework, with the impact of descriptions moderated by task complexity. This model fits the observed behavior better than previous models and replicates the observed non-monotonic relationship between impact of descriptions and task complexity. This research has implications for the development of effective warning labels that rely on simple descriptive information to trigger safer behavior in complex environments.

Magnitude and incentives: revisiting the overweighting of extreme events in risky decisions from experience.

Recent experimental evidence in experience-based decision-making suggests that people are more risk seeking in the gains domain relative to the losses domain. This critical result is at odds with the standard reflection effect observed in description-based choice and explained by Prospect Theory. The so-called reversed-reflection effect has been predicated on the extreme-outcome rule, which suggests that memory biases affect risky choice from experience. To test the general plausibility of the rule, we conducted two experiments examining how the magnitude of prospective outcomes impacts risk preferences. We found that while the reversed-reflection effect was present with small-magnitude payoffs, using payoffs of larger magnitude brought participants' behavior back in line with the standard reflection effect. Our results suggest that risk preferences in experience-based decision-making are not only affected by the relative extremeness but also by the absolute extremeness of past events.

Choice in experiential learning: True preferences or experimental artifacts?

The rate of selecting different options in the decisions-from-feedback paradigm is commonly used to measure preferences resulting from experiential learning. While convergence to a single option increases with experience, some variance in choice remains even when options are static and offer fixed rewards. Employing a decisions-from-feedback paradigm followed by a policy-setting task, we examined whether the observed variance in choice is driven by factors related to the paradigm itself: Continued exploration (e.g., believing options are non-stationary) or exploitation of perceived outcome patterns (i.e., a belief that sequential choices are not independent). Across two studies, participants showed variance in their choices, which was related (i.e., proportional) to the policies they set. In addition, in Study 2, participants' reported under-confidence was associated with the amount of choice variance in later choices and policies. These results suggest that variance in choice is better explained by participants lacking confidence in knowing which option is better, rather than methodological artifacts (i.e., exploration or failures to recognize outcome independence). As such, the current studies provide evidence for the decisions-from-feedback paradigm's validity as a behavioral research method for assessing learned preferences.

Underpowered samples, false negatives, and unconscious learning.

The scientific community has witnessed growing concern about the high rate of false positives and unreliable results within the psychological literature, but the harmful impact of false negatives has been largely ignored. False negatives are particularly concerning in research areas where demonstrating the absence of an effect is crucial, such as studies of unconscious or implicit processing. Research on implicit processes seeks evidence of above-chance performance on some implicit behavioral measure at the same time as chance-level performance (that is, a null result) on an explicit measure of awareness. A systematic review of 73 studies of contextual cuing, a popular implicit learning paradigm, involving 181 statistical analyses of awareness tests, reveals how underpowered studies can lead to failure to reject a false null hypothesis. Among the studies that reported sufficient information, the meta-analytic effect size across awareness tests was d z = 0.31 (95 % CI 0.24-0.37), showing that participants' learning in these experiments was conscious. The unusually large number of positive results in this literature cannot be explained by selective publication. Instead, our analyses demonstrate that these tests are typically insensitive and underpowered to detect medium to small, but true, effects in awareness tests. These findings challenge a widespread and theoretically important claim about the extent of unconscious human cognition.

Uncertainty and exploration in a restless bandit problem.

Decision making in noisy and changing environments requires a fine balance between exploiting knowledge about good courses of action and exploring the environment in order to improve upon this knowledge. We present an experiment on a restless bandit task in which participants made repeated choices between options for which the average rewards changed over time. Comparing a number of computational models of participants' behavior in this task, we find evidence that a substantial number of them balanced exploration and exploitation by considering the probability that an option offers the maximum reward out of all the available options.

Don't bet on it! Wagering as a measure of awareness in decision making under uncertainty.

Can our decisions be guided by unconscious or implicit influences? According to the somatic marker hypothesis, emotion-based signals can guide our decisions in uncertain environments outside awareness. Postdecision wagering, in which participants make wagers on the outcomes of their decisions, has been recently proposed as an objective and sensitive measure of conscious content. In 5 experiments we employed variations of a classic decision-making assessment, the Iowa Gambling Task, in combination with wagering in order to investigate the role played by unconscious influences. We examined the validity of postdecision wagering by comparing it with alternative measures of conscious knowledge, specifically confidence ratings and quantitative questions. Consistent with a putative role for unconscious influences, in Experiments 2 and 3 we observed a lag between choice accuracy and the onset of advantageous wagering. However, the lag was eliminated by a change in the wagering payoff matrix (Experiment 2) and by a switch from a binary wager response to either a binary or a 4-point confidence response (Experiment 3), and wagering underestimated awareness compared to explicit quantitative questions (Experiments 1 and 4). Our results demonstrate the insensitivity of postdecision wagering as a direct measure of conscious knowledge and challenge the claim that implicit processes influence decision making under uncertainty.