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24 - Intelligence and Decision-Making

from Part V - Intelligence and Information Processing

Published online by Cambridge University Press:  13 December 2019

By
Gerd Gigerenzer
Edited by
Robert J. Sternberg
Robert J. Sternberg
Affiliation:
Cornell University, New York
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Summary

There are two ways to study how people make decisions. Decision-making under risk deals with well-defined situations where all possible outcomes and their probabilities are known for certain. Examples are playing roulette or buying a lottery ticket. Decision-making under uncertainty, by contrast, deals with ill-defined situations where this certainty is not attainable for humans or machines, such as how to invest your money, or whom to marry. Risk can be tamed by logic probability theory; uncertainty needs more smart heuristics. Many situations require both competencies. In this chapter, I introduce the tools for both forms of decision-making, the debates associated with the nature of rationality, and the link between decision-making and intelligence.

Keywords

adaptive toolboxecological rationalityexpected utility theoryfast-and-frugal treesgaze heuristicintuitive designrecognition heuristicrisksatisficinguncertainty
Type
Chapter
Information
The Cambridge Handbook of Intelligence , pp. 580 - 601
Publisher: Cambridge University Press
Print publication year: 2020

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References

Allais, M. (1953). Le comportement de l’homme rationnel devant le risque: Critique des postulates et axiomes de l’ecole américaine [Rational man’s behavior: Critique of the American School’s postulates and axioms]. Econometrica 21, 503–546.Google Scholar
Arkes, H. R., Gigerenzer, G., & Hertwig, R. (2016). How bad is incoherence? Decision, 3, 20–39. https://doi.org/10.1037/dec0000043Google Scholar
Axelrod, R. (1984). The evolution of cooperation. New York: Basic Books.Google Scholar
Berg, N. (2014). Success from satisficing and imitation: Entrepreneurs’ location choice and implications of heuristics for local economic development. Journal of Business Research, 67, 1700–1709. https://doi.org/10.1016/j.jbusres.2014.02.016Google Scholar
Berg, N., Biele, G., & Gigerenzer, G. (2016). Consistent Bayesians are no more accurate than non-Bayesians: Economists surveyed about PSA. Review of Behavioral Economics, 3, 189–219. https://doi.org/10.1561/105.00000034Google Scholar
Bernoulli, D. (1738/1954). Exposition of a new theory on the measurement of risk. Econometrica, 22, 23–36. https://doi.org/10.2307/1909829Google Scholar
Boyd, R., & Richardson, P. J. (2005). The origin and evolution of cultures. New York: Oxford University Press.Google Scholar
Bröder, A. (2012). The quest for take-the-best. In Todd, P. M., Gigerenzer, G., & ABC Research Group, Ecological rationality: Intelligence in the world (pp. 216–240). New York: Oxford University Press.Google Scholar
Clark, G. (2002). Embracing fatality through life insurance. In Baker, T. & Simon, J. (Eds.), Embracing risk: The changing culture of insurance and responsibility (pp. 80–96). Chicago: University of Chicago Press.Google Scholar
Cronbach, L. J. (1957). The two disciplines of scientific psychology. American Psychologist, 12, 671–684.Google Scholar
Daston, L. (1987). The domestication of risk: Mathematical probability and insurance 1650–1830. In Krüger, L., Daston, L., & Heidelberger, M. (Eds.), The probabilistic revolution, vol. 1, Ideas in history. Cambridge, MA: MIT Press.Google Scholar
Daston, L. (1988). Classical probability in the Enlightenment. Princeton: Princeton University Press.Google Scholar
Dawes, R. M. (1979). The robust beauty of improper linear models in decision making. American Psychologist, 34, 571–582. https://doi.org/10.1037/0003-066X.34.7.571CrossRefGoogle Scholar
DeMiguel, V., Garlappi, L., & Uppal, R. (2009). Optimal versus naïve diversification: How inefficient is the 1/N portfolio strategy? Review of Financial Studies, 22, 1915 – 1953. https://doi.org/10.1093/rfs/hhm075Google Scholar
Dhami, M. K. (2003). Psychological models of professional decision making. Psychological Science, 14, 175–180. https://doi.org/10.1111/1467-9280.01438Google Scholar
Ellsberg, D. (1961). Risk, ambiguity, and the Savage axioms. Quarterly Journal of Economics, 75, 643–669. https://doi.org/10.2307/1884324Google Scholar
Gigerenzer, G. (1996). On narrow norms and vague heuristics: A reply to Kahneman and Tversky (1996). Psychological Review, 103, 592–596. https://doi.org/10.1037/0033-295X.103.3.592Google Scholar
Gigerenzer, G. (2014). Risk savvy: How to make good decisions. New York: Viking.Google Scholar
Gigerenzer, G. (2015). On the supposed evidence for libertarian paternalism. Review of Philosophy and Psychology, 6, 363–383. https://doi.org/10.1007/s13164-015-0248-1Google Scholar
Gigerenzer, G. (2016). Towards a rational theory of heuristics. In Frantz, R. & Marsh, L. (Eds.), Minds, models, and milieux: Commemorating the centennial of the birth of Herbert Simon (pp. 34–59). New York: Palgrave Macmillan.Google Scholar
Gigerenzer, G. (2018). The bias bias in behavioral economics. Review of Behavioral Economics, 5, 303–336. http://dx.doi.org/10.1561/105.00000092Google Scholar
Gigerenzer, G., & Gaissmaier, W. (2011). Heuristic decision making. Annual Review of Psychology, 62, 451–482. https://doi.org/10.1146/annurev-psych-120709-145346Google Scholar
Gigerenzer, G., & Garcia-Retamero, R. (2017). Cassandra’s regret. The psychology of not wanting to know. Psychological Review, 124, 179–196. https://doi.org/10.1037/rev0000055Google Scholar
Gigerenzer, G., & Goldstein, D. G. (1996). Reasoning the fast and frugal way: Models of bounded rationality. Psychological Review, 104, 650–669. https://doi.org/10.1037/0033-295X.103.4.650Google Scholar
Gigerenzer, G., & Goldstein, D. G. (2011). The recognition heuristic: A decade of research. Judgment and Decision Making, 6, 100–121.Google Scholar
Gigerenzer, G., Hertwig, R., & Pachur, T. (Eds.) (2011). Heuristics: The foundations of adaptive behavior. New York: Oxford University Press.Google Scholar
Gigerenzer, G., Todd, P. M., & ABC Research Group (1999). Simple heuristics that make us smart. New York: Oxford University Press.Google Scholar
Goldstein, D. G., & Gigerenzer, G. (2002). Models of ecological rationality: The recognition heuristic. Psychological Review, 109, 75–90. https://doi.org/10.1037/0033-295X.109.1.75Google Scholar
Green, L, & Mehr, D. R. (1997). What alters physicians’ decisions to admit to the coronary care unit? Journal of Family Practice, 45, 219–226.Google Scholar
Hamlin, R. P. (2017). “The gaze heuristic”: Biography of an adaptively rational decision process. Topics in Cognitive Science, 9, 264–288. https://doi.org/10.1111/tops.12253Google Scholar
Hertwig, R., & Hoffrage, U. (2013). Simple heuristics: The foundations of adaptive social behavior. In Hertwig, R. & Hoffrage, U. (Eds.), Simple heuristics in a social world (pp. 3–36). New York: Oxford University Press.Google Scholar
Hutchinson, J. M. C., & Gigerenzer, G. (2005). Simple heuristics and rules of thumb: Where psychologists and behavioural biologists might meet. Behavioural Processes, 69, 97–124. https://doi.org/10.1016/j.beproc.2005.02.019Google Scholar
Johnson, E. J., & Goldstein, D. G. (2003). Do defaults save lives? Science, 302, 1338–1339.Google Scholar
Kahneman, D. (2011). Thinking fast and slow. London: Allen Lane.Google Scholar
Kahneman, D., & Tversky, A. (1974). Judgment under uncertainty: Heuristics and biases. Science, 185, 1124–1131. https://doi.org/10.1126/science.185.4157.1124Google Scholar
Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica, 47, 263–291. https://doi.org/10.2307/1914185Google Scholar
Kahneman, D., & Tversky, A. (1996). On the reality of cognitive illusions. Psychological Review, 103, 582–591. https://doi.org/10.1037/0033-295X.103.3.582Google Scholar
Knight, F. (1921). Risk, uncertainty and profit, vol. 31. Boston: Houghton Mifflin.Google Scholar
Luan, S., Schooler, L., & Gigerenzer, G. (2011). A signal detection analysis of fast-and-frugal trees. Psychological Review, 118, 316–338. https://doi.org/10.1037/a0022684Google Scholar
Martignon, L., Vitouch, O., Takezawa, M., & Forster, M. R. (2003). Naive and yet enlightened: From natural frequencies to fast and frugal decision trees. In Hardman, D. & Macchi, L. (Eds.), Thinking: Psychological perspectives on reasoning, judgment and decision making (pp. 189–211). Chichester, UK: Wiley.Google Scholar
McBeath, M. K., Shafer, D. M., & Kaiser, M. K. (1995). How baseball outfielders determine where to run to catch fly balls. Science, 268, 569–573. https://doi.org/10.1126/science.7725104Google Scholar
Mischel, W. (2008). The toothbrush problem. Observer, 21(11). www.psychologicalscience.org/observer/the-toothbrush-problemGoogle Scholar
Payne, J. W., Bettman, J. R., & Johnson, E. J. (1993). The adaptive decision maker. New York: Cambridge University Press.Google Scholar
Pohl, R. (2006). Empirical tests of the recognition heuristic. Journal of Behavioral Decision Making, 19, 251–271. https://doi.org/10.1002/bdm.522Google Scholar
Schooler, L. J., & Hertwig, R. (2005). How forgetting aids heuristic inference. Psychological Review, 112, 610–628. https://doi.org/10.1037/0033-295X.112.3.610Google Scholar
Schwartz, B., Ward, A., Monterosso, J., Lyubomirsky, S., White, K., & Lehman, D. R. (2002). Maximizing versus satisficing: Happiness is a matter of choice. Journal of Personality and Social Psychology, 83, 1178–1197. https://doi.org/10.1037/0022-3514.83.5.1178Google Scholar
Simon, H. A. (1955). A behavioral model of rational choice. Quarterly Journal of Economics, 69, 99–118. https://doi.org/10.2307/1884852Google Scholar
Simon, H. A. (1979). Models of thought. New Haven, CT: Yale University Press.Google Scholar
Simon, H. A. (1990). Invariants of human behavior. Annual Review of Psychology, 41, 1–19. https://doi.org/10.1146/annurev.ps.41.020190.000245Google Scholar
Stanovich, K. E., & West, R. F. (2008). On the relative independence of thinking biases and cognitive ability. Journal of Personality and Social Psychology, 94, 672–695.Google Scholar
Taleb, N. N. (2007). The black swan: The impact of the highly improbable. New York: Random House.Google Scholar
Thaler, R. H., & Sunstein, C. R. (2008). Nudge: Improving decisions about health, wealth, and happiness. New Haven, CT: Yale University Press.Google Scholar
Todd, P. M., Gigerenzer, G., & ABC Research Group (2012). Ecological rationality: Intelligence in the world. New York: Oxford University Press.Google Scholar
Todd, P. M., & Miller, G. F. (1999). From pride and prejudice to persuasion: Realistic heuristics for mate search. In Gigerenzer, G., Todd, P. M., & ABC Research Group, Simple heuristics that make us smart (pp. 287–308). New York: Oxford University Press.Google Scholar
Tversky, A., & Kahneman, D. (1971). Belief in the law of small numbers. Psychological Bulletin, 76, 105–110. https://doi.org/10.1037/h0031322Google Scholar

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