Literature DB >> 28484951

Empirical evidence for resource-rational anchoring and adjustment.

Falk Lieder1,2, Thomas L Griffiths3,4, Quentin J M Huys5,6, Noah D Goodman7.   

Abstract

People's estimates of numerical quantities are systematically biased towards their initial guess. This anchoring bias is usually interpreted as sign of human irrationality, but it has recently been suggested that the anchoring bias instead results from people's rational use of their finite time and limited cognitive resources. If this were true, then adjustment should decrease with the relative cost of time. To test this hypothesis, we designed a new numerical estimation paradigm that controls people's knowledge and varies the cost of time and error independently while allowing people to invest as much or as little time and effort into refining their estimate as they wish. Two experiments confirmed the prediction that adjustment decreases with time cost but increases with error cost regardless of whether the anchor was self-generated or provided. These results support the hypothesis that people rationally adapt their number of adjustments to achieve a near-optimal speed-accuracy tradeoff. This suggests that the anchoring bias might be a signature of the rational use of finite time and limited cognitive resources rather than a sign of human irrationality.

Entities:  

Keywords:  Anchoring-and-adjustment; Bounded rationality; Cognitive biases; Heuristics; Probabilistic reasoning

Mesh:

Year:  2018        PMID: 28484951     DOI: 10.3758/s13423-017-1288-6

Source DB:  PubMed          Journal:  Psychon Bull Rev        ISSN: 1069-9384


  6 in total

1.  The effect of accuracy motivation on anchoring and adjustment: do people adjust from provided anchors?

Authors:  Joseph P Simmons; Robyn A LeBoeuf; Leif D Nelson
Journal:  J Pers Soc Psychol       Date:  2010-12

2.  The anchoring-and-adjustment heuristic: why the adjustments are insufficient.

Authors:  Nicholas Epley; Thomas Gilovich
Journal:  Psychol Sci       Date:  2006-04

3.  Judgment under Uncertainty: Heuristics and Biases.

Authors:  A Tversky; D Kahneman
Journal:  Science       Date:  1974-09-27       Impact factor: 47.728

Review 4.  Toward a Rational and Mechanistic Account of Mental Effort.

Authors:  Amitai Shenhav; Sebastian Musslick; Falk Lieder; Wouter Kool; Thomas L Griffiths; Jonathan D Cohen; Matthew M Botvinick
Journal:  Annu Rev Neurosci       Date:  2017-03-31       Impact factor: 12.449

Review 5.  The anchoring bias reflects rational use of cognitive resources.

Authors:  Falk Lieder; Thomas L Griffiths; Quentin J M Huys; Noah D Goodman
Journal:  Psychon Bull Rev       Date:  2018-02

Review 6.  Dual-processing accounts of reasoning, judgment, and social cognition.

Authors:  Jonathan St B T Evans
Journal:  Annu Rev Psychol       Date:  2008       Impact factor: 24.137

  6 in total
  5 in total

Review 1.  The anchoring bias reflects rational use of cognitive resources.

Authors:  Falk Lieder; Thomas L Griffiths; Quentin J M Huys; Noah D Goodman
Journal:  Psychon Bull Rev       Date:  2018-02

2.  Inferring an unobservable population size from observable samples.

Authors:  Jack Cao; Mahzarin R Banaji
Journal:  Mem Cognit       Date:  2020-04

3.  Ten simple rules for the computational modeling of behavioral data.

Authors:  Robert C Wilson; Anne Ge Collins
Journal:  Elife       Date:  2019-11-26       Impact factor: 8.140

4.  Non-Equilibrium Relations for Bounded Rational Decision-Making in Changing Environments.

Authors:  Jordi Grau-Moya; Matthias Krüger; Daniel A Braun
Journal:  Entropy (Basel)       Date:  2017-12-21       Impact factor: 2.524

5.  Rational metareasoning and the plasticity of cognitive control.

Authors:  Falk Lieder; Amitai Shenhav; Sebastian Musslick; Thomas L Griffiths
Journal:  PLoS Comput Biol       Date:  2018-04-25       Impact factor: 4.475

  5 in total

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