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Empirical evidence for resource-rational anchoring and adjustment

descriptionPublicationkeyboard_double_arrow_right Article , Other literature type , Preprint 22 Jan 2017Embargo end date: 01 Jan 2018 United States, Switzerland English Publisher:Springer Science and Business Media LLCJournal:Psychonomic Bulletin & Review, volume 25, pages 775-784 (issn: 1069-9384, eissn: 1531-5320, Copyright policy )
Authors: Falk Lieder; Tom Griffiths; Quentin J.M. Huys; Noah D. Goodman;

doi: 10.3758/s13423-017-1288-6 , 10.31234/osf.io/zu4pt , 10.5167/uzh-137869 , 10.17605/osf.io/zu4pt

pmid: 28484951

Empirical evidence for resource-rational anchoring and adjustment

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 experimentsconfirmed 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.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
27
Top 10%
Top 10%
Top 10%
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