Money, Kisses, and Electric Shocks: On the Affective Psychology of Risk
Abstract
Prospect theory's S-shaped weighting function is often said to reflect the psychophysics of chance. We propose an affective rather than psychophysical deconstruction of the weighting function resting on two assumptions. First, preferences depend on the affective reactions associated with potential outcomes of a risky choice. Second, even with monetary values controlled, some outcomes are relatively affect-rich and others relatively affect-poor. Although the psychophysical and affective approaches are complementary, the affective approach has one novel implication: Weighting functions will be more S-shaped for lotteries involving affect-rich than affect-poor outcomes. That is, people will be more sensitive to departures from impossibility and certainty but less sensitive to intermediate probability variations for affect-rich outcomes. We corroborated this prediction by observing probability-outcome interactions: An affect-poor prize was preferred over an affect-rich prize under certainty, but the direction of preference reversed under low probability. We suggest that the assumption of probability-outcome independence, adopted by both expected-utility and prospect theory, may hold across outcomes of different monetary values, but not different affective values.
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In the Rottenstreich and Hsee (2001) survey, in both the certain-outcome and 1%-probability conditions, 100% of surveyed GPT-3.5 runs (N = 1040, 520 per condition) preferred a favourite movie star's kiss over $50.
“We unexpectedly found in both conditions that 100% of surveyed GPT-3.5 runs (N = 1040, with 520 in each condition) preferred the movie star’s kiss.”
From Diminished diversity-of-thought in a standard large language model (2024) · cites this paper as Rottenstreich and Hsee (2001)
For the Rottenstreich and Hsee (2001) 1%-probability condition, reversing the order of answer choices substantially changed the original finding: 54% (281) retained the kiss preference and 46% (239) preferred cash.
“For the condition in which outcomes were awarded with 1% probability, the same number of runs was surveyed (N = 520), but the new order substantially changed the original finding that 100% of GPT runs preferred the movie star’s kiss. In the reversed-order condition, 54% of the runs (total of 281) retained the original preference of the kiss, while 46% of them (total of 239 runs) preferred the cash”
From Diminished diversity-of-thought in a standard large language model (2024) · cites this paper as Rottenstreich and Hsee (2001)
For the Rottenstreich and Hsee (2001) certain-outcome condition, reversing the order of answer choices did not affect GPT runs' responses; 100% still preferred the movie star's kiss.
“For the condition in which outcomes were awarded with certainty, the same number of runs was surveyed (N = 520), and the changed order of answer choices did not have an effect on GPT runs’ responses. Just like for the original- order condition, 100% of GPT runs preferred the movie star’s kiss in the reversed-order condition.”
From Diminished diversity-of-thought in a standard large language model (2024) · cites this paper as Rottenstreich and Hsee (2001)
Cites
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 · see citing works
Kahneman, D., & Tversky, A. (1984) · American Psychologist · doi:10.1037/0003-066x.39.4.341 · Cited by 6,544 · see citing works
Kahneman, D. J., & Tversky, A. (2013) · World Scientific handbook in financial economic series · doi:10.1142/9789814417358_0016 · Cited by 5,372 · see citing works
(1994) · Journal of the American Dietetic Association · doi:10.1016/0002-8223(94)92568-2 · Cited by 1,985 · see citing works
The Probability Weighting Function
Prelec, D. (1998) · Econometrica · doi:10.2307/2998573 · Cited by 1,945 · see citing works
Anticipation and the Valuation of Delayed Consumption
Loewenstein, G. F. (1987) · The Economic Journal · doi:10.2307/2232929 · Cited by 1,361 · see citing works
On the Shape of the Probability Weighting Function
Gonzalez, R., & Wu, G. (1999) · Cognitive Psychology · doi:10.1006/cogp.1998.0710 · Cited by 1,353 · see citing works
Between Hope and Fear: The Psychology of Risk
Lopes, L. L. (1987) · Advances in experimental social psychology · doi:10.1016/s0065-2601(08)60416-5 · Cited by 1,160 · see citing works
PROBABILITY WEIGHTING FUNCTIONPreprint
al‐Nowaihi, A., & Dhami, S. (2005) · SSRN Electronic Journal · Cited by 1,077 · see citing works
Curvature of the Probability Weighting Function
Wu, G. Y., & Gonzalez, R. (1996) · Management Science · doi:10.1287/mnsc.42.12.1676 · Cited by 1,021 · see citing works
Weighing risk and uncertainty.
Tversky, A., & Fox, C. R. (1995) · Psychological Review · doi:10.1037/0033-295x.102.2.269 · Cited by 972 · see citing works
Parameter-Free Elicitation of Utility and Probability Weighting Functions
Abdellaoui, M. (2000) · Management Science · doi:10.1287/mnsc.46.11.1497.12080 · Cited by 901 · see citing works
Decision Affect Theory: Emotional Reactions to the Outcomes of Risky Options
Mellers, B. A., Schwartz, A., Ho, K., & Ritov, I. (1997) · Psychological Science · doi:10.1111/j.1467-9280.1997.tb00455.x · Cited by 736 · see citing works
Violations of the betweenness axiom and nonlinearity in probability
Camerer, C. F., & Ho, T. (1994) · Journal of Risk and Uncertainty · doi:10.1007/bf01065371 · Cited by 707 · see citing works
Decision making: Descriptive, normative, and prescriptive interactions.
Bell, D. E., Raiffa, H., & Tversky, A. (1988) · Cited by 639 · see citing works
Slovic, P., Monahan, J. T., & MacGregor, D. G. (2000) · Law and Human Behavior · doi:10.1023/a:1005595519944 · Cited by 502 · see citing works
A Parameter-Free Elicitation of the Probability Weighting Function in Medical Decision Analysis
Bleichrodt, H., & Prades, J. L. P. (2000) · Management Science · doi:10.1287/mnsc.46.11.1485.12086 · Cited by 473 · see citing works
DESCRIPTIVE, NORMATIVE, AND PRESCRIPTIVE INTERACTIONS IN DECISION MAKING
Bell, D. E., Raiffa, H., & Tversky, A. (1988) · Cambridge University Press eBooks · doi:10.1017/cbo9780511598951.003 · Cited by 301 · see citing works
Judging Risk and Return of Financial Assets
Ganzach, Y. (2000) · Organizational Behavior and Human Decision Processes · doi:10.1006/obhd.2000.2914 · Cited by 279 · see citing works
What Determines the Shape of the Probability Weighting Function Under Uncertainty?
Kilka, M., & Weber, M. (2001) · Management Science · doi:10.1287/mnsc.47.12.1712.10239 · Cited by 236 · see citing works
Recent Tests of Generalizations of Expected Utility Theory
Camerer, C. F. (1992) · Studies in risk and uncertainty · doi:10.1007/978-94-011-2952-7_9 · Cited by 154 · see citing works
Anxiety and Decision Making with Delayed Resolution of Uncertainty
Wu, G. (1999) · Theory and Decision · doi:10.1023/a:1004990410083 · Cited by 105 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Maps of Bounded Rationality: Psychology for Behavioral Economics
Kahneman, D. (2003) · American Economic Review · doi:10.1257/000282803322655392 · Cited by 5,377 · see citing works
Using social and behavioural science to support COVID-19 pandemic response
Bavel, J. J. V., Baicker, K., Boggio, P. S., Capraro, V., Cichocka, A., Cikara, M., Crockett, M. J., Crum, A. J., Douglas, K. M., Druckman, J. N., et al. (2020) · Nature Human Behaviour · doi:10.1038/s41562-020-0884-z · Cited by 4,964 · see citing works
Risk as Analysis and Risk as Feelings: Some Thoughts about Affect, Reason, Risk, and Rationality
Slovic, P., Finucane, M. L., Peters, E., & MacGregor, D. G. (2004) · Risk Analysis · doi:10.1111/j.0272-4332.2004.00433.x · Cited by 3,885 · see citing works
Lerner, J. S., Li, Y., Valdesolo, P., & Kassam, K. S. (2015) · Annual Review of Psychology · doi:10.1146/annurev-psych-010213-115043 · Cited by 2,913 · see citing works
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 · see citing works
Many Labs 2: Investigating variation in replicability across samples and settings
Klein, R. A., Vianello, M., Hasselman, F., Adams, B. G., Adams, R. B., Alper, S., Aveyard, M., Axt, J. R., Babalola, M. T., Bahník, Š., et al. (2018) · Advances in Methods and Practices in Psychological Science · doi:10.1177/2515245918810225 · Cited by 944 · see citing works
Schaefer, A., Nils, F., Sanchez, X., & Philippot, P. (2010) · Cognition & Emotion · doi:10.1080/02699930903274322 · Cited by 875 · see citing works
Full Disclosure: The Perils and Promise of Transparency
Fung, A., Graham, M., & Weil, D. (2007) · doi:10.1017/cbo9780511510533 · Cited by 752 · see citing works
Music, Pandas, and Muggers: On the Affective Psychology of Value.
Hsee, C. K., & Rottenstreich, Y. (2004) · Journal of Experimental Psychology: General · doi:10.1037/0096-3445.133.1.23 · Cited by 654 · see citing works
Self-citationEmotion and Rationality: A Critical Review and Interpretation of Empirical Evidence
Pham, M. T. (2007) · Review of General Psychology · doi:10.1037/1089-2680.11.2.155 · Cited by 552 · see citing works
Hsee, C. K., & Zhang, J. (2010) · Perspectives on Psychological Science · doi:10.1177/1745691610374586 · Cited by 410 · see citing works
Self-citationEmotion and decision-making: affect-driven belief systems in anxiety and depression
Paulus, M. P., & Yu, A. J. (2012) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2012.07.009 · Cited by 287 · see citing works
The Functions of Affect in Health Communications and in the Construction of Health Preferences
Peters, E., Lipkus, I., & Diefenbach, M. A. (2006) · Journal of Communication · doi:10.1111/j.1460-2466.2006.00287.x · Cited by 251 · see citing works
Why and When Leaders’ Affective States Influence Employee Upward Voice
Liu, W., Song, Z., Li, X., & Liao, Z. (2017) · Academy of Management Journal · doi:10.5465/amj.2013.1082 · Cited by 241 · see citing works
A dual system model of preferences under risk
Mukherjee, K. (2010) · Psychological Review · doi:10.1037/a0017884 · Cited by 198 · see citing works
Diminished diversity-of-thought in a standard large language model
Park, P. S., Schoenegger, P., & Zhu, C. (2024) · Behavior Research Methods · doi:10.3758/s13428-023-02307-x · Cited by 83 · see citing works
Effects of emotion on medical decisions involving tradeoffs.
Ellis, E. M., Klein, W. M. P., Orehek, E., & Ferrer, R. A. (2018) · Medical Decision Making · doi:10.1177/0272989x18806493 · Cited by 19 · see citing works
- Authors
- Rottenstreich, Y., & Hsee, C. K.
- Affiliations
- University of Chicago (US)
- Corresponding author
- Rottenstreich, Yuval
- Venue
- Psychological Science
- Publisher
- SAGE Publications
- Published
- 2001-05
- Volume
- 12
- Issue
- 3
- Pages
- 185-190
- ISSN
- 0956-7976 (ISSN-L)
- 1467-9280
- OpenAlex
- W2112818819
- Cited by
- 825
- References
- 23
- Citations by year
- 2026: 11 · 2025: 12 · 2024: 53 · 2023: 22 · 2022: 32 · 2021: 36 · 2020: 38 · 2019: 45 · 2018: 45 · 2017: 33 · 2016: 36 · 2015: 53 · 2014: 33 · 2013: 54 · 2012: 41
- FWCI
- 21.97
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Psychological Science (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Social Sciences › Decision Sciences › General Decision Sciences › Decision-Making and Behavioral Economics
- Social Sciences › Safety Research › Experimental Behavioral Economics Studies
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
- Keywords
- prospect theory, probability weighting function, expected utility theory, decision making under risk, lotteries, monetary value
- MeSH terms
- Adult, Affect, Choice Behavior, Female, Humans, Male, Models, Psychological, Probability, Risk-Taking
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