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Overview

We must discipline ourselves to overcome the tendency for our decisions to not fully account for all information, reward timescale, decision context, and probability.

Types

Name Description Sources
Discounting Discounting is the tendency for people to have a stronger preference for more immediate payoffs relative to later payoffs. [1]
Hyperbolic discounting Leads to choices that are inconsistent over time – people make choices today that their future selves would prefer not to have made, despite using the same reasoning. [1] [2]
Neglect of probability The tendency to completely disregard probability when making a decision under uncertainty. [1] [3]
Outcome bias The tendency to judge a decision by its eventual outcome instead of based on the quality of the decision at the time it was made. [1]

Practical Perspectives

  • Our best decisions are the ones we will want to continue over the long-term.
  • Structured decision-making can provide formal cues to describe various dimensions of decision-making that can help prevent their from being omitted from the process.

Key Research

  • From [1]: A study showed that when making food choices for the coming week, 74% of participants chose fruit, whereas when the food choice was for the current day, 70% chose chocolate.

Related Fallacies

Information omission

Name Description Sources
McNamara fallacy (quantitative fallacy) Making a decision based only on quantitative observations, discounting all other considerations. [4]
Base rate fallacy Making a probability judgment based on conditional probabilities, without taking into account the effect of prior probabilities. [4] [5]
Overwhelming exception An accurate generalization that comes with qualifications that eliminate so many cases that what remains is much less impressive than the initial statement might have led one to assume. [4] [6]
Slothful induction (also called appeal to coincidence) An inductive argument is denied its proper conclusion, despite strong evidence for inference. [7] [8]
No true Scotsman Makes a generalization true by changing the generalization to exclude a counterexample. [4] [9]
The third-cause fallacy A logical fallacy where a spurious relationship is confused for causation. It asserts that X causes Y when, in reality, X and Y are both caused by Z. [10] [9]
Regression fallacy Ascribes cause where none exists. The flaw is failing to account for natural fluctuations. It is frequently a special kind of post hoc fallacy. [4]

Faulty information

Some fallacies of information neglect involve simply using the wrong or faulty information.

Name Description Sources
Double counting Counting events or occurrences more than once in probabilistic reasoning, which leads to the sum of the probabilities of all cases exceeding unity. [4]
Hasty generalization Basing a broad conclusion on a small sample or the making of a determination without all of the information required to do so. [4] [11]
False analogy An argument by analogy in which the analogy is poorly suited. [4] [12]
Cherry picking Act of pointing at individual cases or data that seem to confirm a particular position, while ignoring a significant portion of related cases or data that may contradict that position. [4] [13]
Survivorship bias A small number of successes of a given process are actively promoted while completely ignoring a large number of failures [4]
Sampling bias A bias in which a sample is collected in such a way that some members of the intended population have a lower or higher sampling probability than others. It results in a biased sample, a non-random sample of a population (or non-human factors) in which all individuals, or instances, were not equally likely to have been selected. [14] [15, 16]
References & Acknowledgements

[1] Wikipedia contributors. "List of cognitive biases." Wikipedia, The Free Encyclopedia. Wikipedia, The Free Encyclopedia, 14 Jul. 2020. Web. 23 Jul. 2020. link

[2] Laibson D (1997). "Golden Eggs and Hyperbolic Discounting". Quarterly Journal of Economics. 112 (2): 443–477. CiteSeerX 10.1.1.337.3544. doi:10.1162/003355397555253.

[3] Baron J (1994). Thinking and deciding (2nd ed.). Cambridge University Press. ISBN 978-0-521-43732-5.

[4] Wikipedia contributors. "List of fallacies." Wikipedia, The Free Encyclopedia. Wikipedia, The Free Encyclopedia, 26 Jul. 2020. Web. 28 Jul. 2020.

[5] Kahneman, Daniel; Amos Tversky (1985). "Evidential impact of base rates". In Daniel Kahneman, Paul Slovic & Amos Tversky (ed.). Judgment under uncertainty: Heuristics and biases. pp. 153–160. PMID 17835457.

[6] Fischer, David Hackett (1970). Historians' Fallacies: Toward a Logic of Historical Thought. HarperCollins. ISBN 978-0-06-131545-9.

[7] Wikipedia contributors. "Slothful induction." Wikipedia, The Free Encyclopedia. Wikipedia, The Free Encyclopedia, 17 Apr. 2020. Web. 28 Jul. 2020.

[8] Barker, Stephen F. (24 July 2002). The Elements of Logic (6th ed.). McGraw-Hill. ISBN 0-07-283235-5.

[9] Flew, Antony (1984). A Dictionary of Philosophy (Revised 2nd ed.). Macmillan. ISBN 978-0-312-20923-0.

[10] Wikipedia contributors. "Correlation does not imply causation." Wikipedia, The Free Encyclopedia. Wikipedia, The Free Encyclopedia, 24 Jul. 2020. Web. 28 Jul. 2020.

[11] Hurley, Patrick J. (2007). A Concise Introduction to Logic (10th ed.). Cengage. ISBN 978-0-495-50383-5.

[12] Damer, T. Edward (2009). Attacking Faulty Reasoning: A Practical Guide to Fallacy-free Arguments (6th ed.). Wadsworth. ISBN 978-0-495-09506-4. Retrieved 30 November 2010.

[13] Hurley, Patrick J. (2007). A Concise Introduction to Logic (10th ed.). Cengage. ISBN 978-0-495-50383-5.

[14] Wikipedia contributors. "Sampling bias." Wikipedia, The Free Encyclopedia. Wikipedia, The Free Encyclopedia, 27 May. 2020. Web. 28 Jul. 2020.

[15] Medical Dictionary – 'Sampling Bias' Retrieved on September 23, 2009 Archived March 10, 2016, at the Wayback Machine

[16] TheFreeDictionary – biased sample Retrieved on 2009-09-23. Site in turn cites: Mosby's Medical Dictionary, 8th edition.

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