ArticleJournal of Intelligence2018
When Irrational Biases Are Smart: A Fuzzy-Trace Theory of Complex Decision Making.
Article in Journal of Intelligence, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
8 citing papers in PubMed.
- Decision-Making Styles, Prosociality, and Behavioral Difficulties in Adolescent Offenders: The Mediating Role of Life Satisfaction and Emotional Experiences.Behavioral sciences (Basel, Switzerland) · 2025Article
- Impact of gist intervention on automated system interpretability and user decision making.Cognitive research: principles and implications · 2024Article
- Critical tests of fuzzy trace theory in brain and behavior: uncertainty across time, probability, and development.Cognitive, affective & behavioral neuroscience · 2023Article
- Supporting Health and Medical Decision Making: Findings and Insights from Fuzzy-Trace Theory.Medical decision making : an international journal of the Society for Medical Decision Making · 2022Article
- How Fuzzy-trace Theory Predicts Development of Risky Decision Making, with Novel Extensions to Culture and Reward Sensitivity.Developmental review : DR · 2021Article
- A scientific theory of gist communication and misinformation resistance, with implications for health, education, and policy.Proceedings of the National Academy of Sciences of the United States of America · 2021Review
- On the memory processes underlying conscious deliberation in complex decision making: the role of verbatim and gist memory.Psychological research · 2020Article
- Neural Underpinnings of Financial Decision Bias in Older Adults: Putative Theoretical Models and a Way to Reconcile Them.Frontiers in neuroscience · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
Abstract
I take a decision-making approach to consider ways of addressing the "unresolved and dramatic problems in the world". Traditional approaches to good decision-making are reviewed. These approaches reduce complex decisions to tradeoffs between magnitudes of probabilities, and outcomes in which the quantity and precision of information are key to making good decisions. I discuss a contrasting framework, called "fuzzy-trace theory", which emphasizes understanding the simple gist of options and applying core social and moral values. Importantly, the tendency to rely on meaningful but simple gist increases from childhood to adulthood (or, in adulthood, as people gain experience in a domain), so that specific irrational biases grow with knowledge and experience. As predicted theoretically, these violations of rationality in the traditional sense are associated empirically with healthier and more adaptive outcomes. Thus, interventions that help decision makers understand the essential gist of their options and how it connects to core values are practical approaches to reducing "unresolved and dramatic problems in the world" one decision at a time.
Indexed as
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.