Mindful Judgment and Decision Making

Metacognitive Myopia: A Major Obstacle on the Way to Rationality

The notion of metacognitive myopia refers to a conspicuous weakness of the quality control of memory and reasoning processes. Although people are often remarkably sensitive even to complex samples of information when making evaluative judgments and decisions, their uncritical and naive tendency to take the validity of sampled information for granted constitutes a major obstacle to rational behavior. After illustrating this phenomenon with reference to prominent biases (base-rate neglect, misattribution, perseverance), we decompose metacognitive myopia into two distinct but intertwined functions, monitoring and control. We offer explanations for why effectively monitoring the biases resulting from information sampling in an uncertain world is so difficult and why the control function is severely restricted by the lack of volitional control over mental actions. Because of these and other difficulties, metacognitive myopia constitutes a major obstacle to rational judgment and decision making.

Cognitive Bias Lab | Learn to Make Better Decisions

Explore cognitive biases with interactive tests, simulations, and real-world examples. Free platform to sharpen decision-making and critical thinking — no sign-up needed.

Mental Models: The Best Way to Make Intelligent Decisions (~100 Models Explained)

The smartest people in the world use mental models to make intelligent decisions, avoid stupidity, and increase productivity. Let's take a look at how ...

Adult age differences in monetary decisions with real and hypothetical reward

Abstract Age differences in monetary decisions may emerge because younger and older adults perceive the value of outcomes differently. Yet, age‐differential effects of monetary rewards on decisions are not well understood. Most laboratory studies on aging and decision making have used scenarios in which rewards were merely hypothetical (decisions did not have any real consequences) or in which only small amounts of money were at stake. In the current study, we compared younger adults' (20–29 years) and older adults' (61–82 years) decisions in probabilistic choice problems with real or hypothetical rewards. Decision‐contingent rewards were in a typical range of previous studies (gains of up to ~4.25 USD) or substantially scaled up (gains of up to ~85 USD per participant). Reward type (real vs. hypothetical) affected decision quality, including value maximization, switching between options, and dominance violations (choices of an option that was inferior to another option in all respects). Decision quality was markedly better with real than hypothetical rewards in older adults and correlated with numeracy in both age groups. However, we found no evidence that reward type affected people's risk preferences. Overall, the findings portray a fairly positive picture regarding the use of hypothetical scenarios to assess preferences: With carefully prepared instructions, people from different age groups indicate preferences in hypothetical scenarios that match their decisions with real and much higher rewards. One advantage of using real rewards is that they help to reduce decision noise.

Beware of samples! A cognitive-ecological sampling approach to judgment biases.

Resource-rational belief revision can mitigate as well as amplify polarization

People's beliefs sometimes diverge after observing the same information, which has been interpreted as evidence of irrationality. This behaviour has been proposed to result from people's limited cognitive resources and motivated reasoning, but how belief revision differs across these explanations has not been formalized or compared to a rational norm. Further, while people may be biased relative to a normative ideal, they may still make optimal choices given their limited cognitive resources, or rationally balance the utility of holding accurate beliefs with the belief's intrinsic utility. Across two studies, we develop and test a unified computational account of belief polarization under these proposed mechanisms, showing that people's performance on a belief updating task best fits a limited-resource Bayesian model; external motivations may contribute to divergence (or convergence) by determining what pre-existing information people consider relevant to a situation, rather than by changing how people evaluate new information in isolation.

Characterizing the causes, dynamics, and consequences of choice deferral

The fact that people often avoid making decisions is well known, and past research has helped to identify some of the conditions and reasons for doing so. For instance, people may forgo choices between bad options because they prefer not to end up with one of those options. It is much less clear when and why people avoid choosing in cases where they eventually will have to make a given decision. To study such instances of choice deferral, we presented participants with a series of choices, and for each choice they were allowed to either choose immediately or defer the decision until later in the experiment. Across six experiments and three choice domains (choices among consumer goods, artwork, and political candidates), we find that the strongest predictor of choice deferral is the overall value of a given set of options, with relative value (i.e., how hard it is to identify the best option) counterintuitively playing a smaller role. We show that the influence of overall value on choice deferral can be accounted for by a dynamic decision model according to which participants appraise the option set relative to a criterion before deciding whether to choose or defer, comparing this to a previous model whereby participants make such a decision based on a predetermined decision time limit. We further reveal that the influence of overall value on choice deferral is determined by how congruent options are with a given choice goal (choose-best or choose-worst) rather than simply how bad those options are. Collectively, our findings shed new light on how people decide to put off the inevitable.

Self-Distancing: What It Is and How You Can Use It to Make Better Decisions – Effectiviology

It’s hard to set your emotions aside when you’re faced with a difficult decision. This is problematic, since our emotions often cause us to make the wrong decision in important areas of life, including in our relationships, our finances, and our health.

Learning From Older Adults: An Intergoal Compatibility Account for Successful Happiness Pursuit

Academic Abstract People want to pursue happiness but often fail, a phenomenon known as the paradox of pursuing happiness. The mechanisms underlying this paradox remain elusive. Age differences in happiness—specifically that older adults appear more successful in pursuing happiness (the emotion paradox of aging)—provide valuable insights into effective happiness pursuit. Drawing on this literature, we propose an intergoal compatibility account to interpret both paradoxes through the lens of intergoal interactions, an intuitively critical yet underexplored factor in existing interpretations. This account asserts that greater compatibility (fewer conflicts and greater facilitation) between happiness pursuit and other important personal goals enhances the effectiveness of happiness pursuit, and such compatibility can be enhanced through contextual influences (e.g., age-graded developmental tasks) and strategic self-regulation (e.g., goal adjustments). This account generates testable predictions and practical implications for enhancing happiness pursuit across the lifespan. Public Abstract Why do people often struggle to achieve happiness? And why are older adults happier than younger adults, even though they face more losses in life? While these questions have drawn extensive attention, they remain puzzling. A crucial yet insufficiently explored factor in successful happiness pursuit is intergoal compatibility —the extent to which the pursuit of happiness aligns or conflicts with other important personal goals. For younger adults, the demands of age-related developmental tasks (e.g., educational and career aspirations) often create conflicts with the pursuit of happiness, diminishing its effectiveness. Conversely, in older adults, happiness becomes more prioritized and compatible with other important personal goals, thereby enhancing the effectiveness of pursuing happiness. A lesson we can learn from older adults is to pursue happiness in ways compatible with other important personal goals.

Metacognitive experiences as information: Processing fluency in consumer judgment and decision making

Abstract Thinking is accompanied by metacognitive experiences of ease or difficulty. People draw on these experiences as a source of information that can complement or challenge the implications of declarative information. We conceptualize the operation of metacognitive experiences within the framework of feelings‐as‐information theory and review their implications for judgments relevant to consumer behavior, including popularity, trust, risk, truth, and beauty.

Metacognitive experiences as information: Processing fluency in consumer judgment and decision making

Abstract Thinking is accompanied by metacognitive experiences of ease or difficulty. People draw on these experiences as a source of information that can complement or challenge the implications of declarative information. We conceptualize the operation of metacognitive experiences within the framework of feelings‐as‐information theory and review their implications for judgments relevant to consumer behavior, including popularity, trust, risk, truth, and beauty.

Choice Bracketing

When making many choices, a person can broadly bracket them by assessing the consequences of all of them taken together, or narrowly bracket them by making each choice in isolation. We integrate research conducted in a wide range of decision contexts which shows that choice bracketing is an important determinant of behavior. Because broad bracketing allows people to take into account all the consequences of their actions, it generally leads to choices that yield higher utility. The evidence that we review, however, shows that people often fail to bracket broadly when it would be feasible for them to do so. In addition to documenting the diverse effects of bracketing, we also discuss factors that determine whether people bracket narrowly or broadly. We conclude with a discussion of normative aspects of bracketing and argue that there are some situations in which narrower bracketing results in superior decision making.

Mechanisms of social cognition

Social animals including humans share a range of social mechanisms that are automatic and implicit and enable learning by observation. Learning from others includes imitation of actions and mirroring of emotions. Learning about others, such as their group membership and reputation, is crucial for social interactions that depend on trust. For accurate prediction of others' changeable dispositions, mentalizing is required, i.e., tracking of intentions, desires, and beliefs. Implicit mentalizing is present in infants less than one year old as well as in some nonhuman species. Explicit mentalizing is a meta-cognitive process and enhances the ability to learn about the world through self-monitoring and reflection, and may be uniquely human. Meta-cognitive processes can also exert control over automatic behavior, for instance, when short-term gains oppose long-term aims or when selfish and prosocial interests collide. We suggest that they also underlie the ability to explicitly share experiences with other agents, as in reflective discussion and teaching. These are key in increasing the accuracy of the models of the world that we construct.

A sampling model of social judgment.

Thinking—Fast, Slow, and Artificial: How AI is Reshaping Human Reasoning and the Rise of Cognitive Surrender

People increasingly consult generative artificial intelligence (AI) while reasoning. As AI becomes embedded in daily thought, what becomes of human judgment? We

Reason-Mediated Behavioral Models for Auditing LLM Social Simulators

Large language models are increasingly used as social simulators, including as synthetic survey respondents. Most evaluations ask whether simulated outcomes resemble human outcomes. We argue that this is necessary but too weak: a simulator can match the final answer while using the wrong behavioral mechanism. We study this problem through a 94-person sunscreen concept test in which each respondent evaluated three product concepts and wrote open-ended rationales. We map those rationales into signed reason states $Z$, where positive signs support adoption and negative signs block it. This gives a practical audit: holding respondent descriptors $D$, category context $K$, and concept treatment $X$ fixed, do human-stated reasons help predict behavior $Y$, and can an LLM simulate the same reason state without seeing the human rationale or outcome? Human-stated reasons substantially improve held-out prediction of purchase intent. LLM-simulated reasons are more brittle: they often sound plausible, but frequently echo the concept board rather than recover the respondent's acceptance or rejection path. The paper contributes an evaluation framework for social simulators. Reason states do not identify natural causal effects by themselves, but they provide an interpretable test of whether a simulator's stated reasons align with human evidence.