The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Decisions from Experience and the Effect of Rare Events in Risky Choice
Abstract
When people have access to information sources such as newspaper weather forecasts, drug-package inserts, and mutual-fund brochures, all of which provide convenient descriptions of risky prospects, they can make decisions from description. When people must decide whether to back up their computer's hard drive, cross a busy street, or go out on a date, however, they typically do not have any summary description of the possible outcomes or their likelihoods. For such decisions, people can call only on their own encounters with such prospects, making decisions from experience. Decisions from experience and decisions from description can lead to dramatically different choice behavior. In the case of decisions from description, people make choices as if they overweight the probability of rare events, as described by prospect theory. We found that in the case of decisions from experience, in contrast, people make choices as if they underweight the probability of rare events, and we explored the impact of two possible causes of this underweighting—reliance on relatively small samples of information and overweighting of recently sampled information. We conclude with a call for two different theories of risky choice.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Research on Decisions from Experience (DfE) shows that individuals' choices rely on small samples of recalled instances from past interactions, an experiencedependent mechanism that is inherently noisy and biased (Gonzalez et al., 2003); (Gonzalez & Dutt, 2011); (Hertwig et al., 2004).”
From Open Challenges in Multi-Agent Security: Towards Secure Systems of Interacting AI Agents (2025) · cites this paper as Hertwig et al., 2004
Experimental — accuracy not yet measured
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Prospect Theory: An Analysis of Decision under Risk
Kahneman, D., & Tversky, A. (1979) · Econometrica · doi:10.2307/1914185 · Cited by 48,524
Advances in prospect theory: Cumulative representation of uncertainty
Tversky, A., & Kahneman, D. (1992) · Journal of Risk and Uncertainty · doi:10.1007/bf00122574 · Cited by 15,467
Animal choice behavior and the evolution of cognitive architecture
Real, L. A. (1991) · Science · doi:10.1126/science.1887231 · Cited by 377
Research works printed but not linked: 17
- 10.2307/1907921 · DOI
- 10.1006/obhd.1998.2772 · DOI
- 10.1002/bdm.443 · DOI
- 10.1017/CBO9780511803475.017 · DOI
- Chu Y.P., 1990, American Economic Review, 80, 902
- 10.1037/0033-295X.105.2.280 · DOI
- 10.1037/0033-295X.107.4.659 · DOI
- Hertwig R., Information sampling as a key to understanding adaptive cognition
- 10.1017/S0140525X01004149 · DOI
- 10.1016/0010-0285(92)90002-J · DOI
- Jorland G., 1987, The probabilistic revolution: Vol. I. Ideas in history, 157
- 10.1037/0033-295X.107.2.397 · DOI
- 10.1037/0096-3445.131.2.287 · DOI
- 10.1017/S0140525X00041157 · DOI
- von Neuman J., 1947, Theory of games and economic behavior
- 10.1037/0278-7393.19.5.1151 · DOI
- 10.1037/0033-295X.111.2.430 · DOI
Cited by
Sorted by citations
The trouble with overconfidence.
Moore, D. A., & Healy, P. J. (2008) · Psychological Review · doi:10.1037/0033-295x.115.2.502 · Cited by 2,358
Data collection in a flat world: the strengths and weaknesses of Mechanical Turk samples
Goodman, J. K., Cryder, C. E., & Cheema, A. (2013) · Journal of Behavioral Decision Making · doi:10.1002/bdm.1753 · Cited by 2,242
A framework for studying the neurobiology of value-based decision making
Rangel, A., Camerer, C., & Montague, P. R. (2008) · Nature Reviews Neuroscience · doi:10.1038/nrn2357 · Cited by 2,184
Reyna, V. F., & Farley, F. (2006) · Psychological Science in the Public Interest · doi:10.1111/j.1529-1006.2006.00026.x · Cited by 1,244
Public understanding of climate change in the United States.
Weber, E. U., & Stern, P. C. (2011) · American Psychologist · doi:10.1037/a0023253 · Cited by 841
Self-citationStewart, N., Chater, N., & Brown, G. D. A. (2006) · Cognitive Psychology · doi:10.1016/j.cogpsych.2005.10.003 · Cited by 737
Humans use directed and random exploration to solve the explore–exploit dilemma.
Wilson, R. C., Geana, A., White, J. M., Ludvig, E. A., & Cohen, J. D. (2014) · Journal of Experimental Psychology: General · doi:10.1037/a0038199 · Cited by 580
Using cognitive psychology to understand GPT-3
Binz, M., & Schulz, E. (2023) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2218523120 · Cited by 559
Neural prediction errors reveal a risk-sensitive reinforcement-learning process in the human brain
Niv, Y., Edlund, J. A., Dayan, P., & O'Doherty, J. P. (2012) · The Journal of Neuroscience · doi:10.1523/jneurosci.5498-10.2012 · Cited by 356
Choosing to make an effort: The role of striatum in signaling physical effort of a chosen action
Kurniawan, I. T., Seymour, B., Talmi, D., Yoshida, W., Chater, N., & Dolan, R. J. (2010) · Journal of Neurophysiology · doi:10.1152/jn.00027.2010 · Cited by 225
Adaptive capacity: Exploring the research frontier
Mortreux, C., & Barnett, J. (2017) · WIREs Climate Change · doi:10.1002/wcc.467 · Cited by 211
Error effects in anterior cingulate cortex reverse when error likelihood is high
Jessup, R. K., Busemeyer, J. R., & Brown, J. W. (2010) · The Journal of Neuroscience · doi:10.1523/jneurosci.4130-09.2010 · Cited by 151
Hypothetical Outcome Plots Help Untrained Observers Judge Trends in Ambiguous Data
Kale, A., Nguyen, F., Kay, M., & Hullman, J. (2019) · IEEE Transactions on Visualization and Computer Graphics · doi:10.1109/tvcg.2018.2864909 · Cited by 122
Decision making and learning while taking sequential risks.
Pleskac, T. J. (2008) · Journal of Experimental Psychology: Learning, Memory, and Cognition · doi:10.1037/0278-7393.34.1.167 · Cited by 121
Lee, K., & Joshi, K. (2017) · Information Systems Journal · doi:10.1111/isj.12118 · Cited by 94
Goal-directed control and its antipodes
Dayan, P. (2009) · Neural Networks · doi:10.1016/j.neunet.2009.03.004 · Cited by 93
P300 amplitude variations, prior probabilities, and likelihoods: a Bayesian ERP study
Kopp, B., Seer, C., Lange, F., Kluytmans, A., Kolossa, A., Fingscheidt, T., & Hoijtink, H. (2016) · Cognitive, Affective, & Behavioral Neuroscience · doi:10.3758/s13415-016-0442-3 · Cited by 60
“Leaving it to chance”—Passive risk taking in everyday life
Keinan, R., & Bereby-Meyer, Y. (2012) · Judgment and Decision Making · doi:10.1017/s1930297500003259 · Cited by 55
An encounter frequency account of how experience affects likelihood estimation
Obrecht, N. A., Chapman, G. B., & Gelman, R. (2009) · Memory & Cognition · doi:10.3758/mc.37.5.632 · Cited by 54
Chen, J., Mishler, S., Hu, B., Li, N., & Proctor, R. W. (2018) · International Journal of Human-Computer Studies · doi:10.1016/j.ijhcs.2018.05.010 · Cited by 50
Schulze, C., & Hertwig, R. (2021) · Cognition · doi:10.1016/j.cognition.2020.104580 · Cited by 36
Self-citationOpen Challenges in Multi-Agent Security: Towards Secure Systems of Interacting AI Agents
de Witt, C. S., Krawiecka, K., Krawczuk, I., Hagag, B., Anderson, W. L., Belcak, P., Bucknall, B., Cai, X., Chopra, A., Cohen, D., et al. (2025) · arXiv · doi:10.48550/arxiv.2505.02077 · Cited by 108
Metadata
- Authors
- Hertwig, R., Barron, G., Weber, E. U., & Erev, I.
- Affiliations
- University of Basel, Basel, Switzerland
- Harvard University
- Columbia University
- Technion, Haifa, Israel
- Venue
- Psychological Science
- Publisher
- SAGE Publications
- Published
- 2004-08
- Volume
- 15
- Issue
- 8
- Pages
- 534-539
- ISSN
- 0956-7976
- 1467-9280
- Cited by
- 1,225
- References
- 3
- Language
- en
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
