The evolutionary background to (mis)understanding an uncertain world

David M. Wilkinson and Thomas N. Sherratt

Journal of Risk Research, 2019, vol. 22, issue 9, 1116-1127

Abstract: Misunderstandings of causality are often referred to as superstitions. More formally, superstitious behaviours can be defined as actions (or inactions) that are performed in order to increase the probability that a beneficial outcome arises when there is no causal relationship between the action and the outcome. While superstitious behaviours are common in humans, they also arise in non-human animals. Although behaving superstitiously may on first reflection appear always maladaptive, recent models have shown that superstitions will readily arise as a by-product of adaptive learning, in which individuals seek to balance gaining new information about the world with exploiting their current information. In short, if a behavior appears associated with a beneficial outcome, it may not be worthwhile experimenting and losing out on this benefit to determine whether the association has arisen by chance. The models help explain why superstitions get started, and indicate the types of superstitious behaviours that are likely to persist. In support, empiricists have widely observed that superstitions are more likely to develop when the perceived benefit of adopting a behaviour is high compared to the cost of not adopting it and when the number of opportunities to test one’s understanding is low. Collectively, therefore, while superstitions are commonly presented as entirely irrational behaviours, they can actually represent a smart strategy, promoted by natural selection, in situations where causal relationships are uncertain.

Date: 2019
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/13669877.2019.1588914 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:jriskr:v:22:y:2019:i:9:p:1116-1127

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/RJRR20

DOI: 10.1080/13669877.2019.1588914

Access Statistics for this article

Journal of Risk Research is currently edited by Bryan MacGregor

More articles in Journal of Risk Research from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().