The extent of algorithm aversion in decision-making situations with varying gravity.

Autor:	Ibrahim Filiz, Jan René Judek, Marco Lorenz, Markus Spiwoks
Jazyk:	angličtina
Rok vydání:	2023
Předmět:	Medicine Science
Zdroj:	PLoS ONE, Vol 18, Iss 2, p e0278751 (2023)
Druh dokumentu:	article
ISSN:	1932-6203
DOI:	10.1371/journal.pone.0278751
Popis:	Algorithms already carry out many tasks more reliably than human experts. Nevertheless, some subjects have an aversion towards algorithms. In some decision-making situations an error can have serious consequences, in others not. In the context of a framing experiment, we examine the connection between the consequences of a decision-making situation and the frequency of algorithm aversion. This shows that the more serious the consequences of a decision are, the more frequently algorithm aversion occurs. Particularly in the case of very important decisions, algorithm aversion thus leads to a reduction of the probability of success. This can be described as the tragedy of algorithm aversion.
Databáze:	Directory of Open Access Journals
Externí odkaz:	https://doaj.org/article/551088f9de1f4258a582add43bda241a Zobrazit plný text záznamu View record in DOAJ Plný text ve formátu PDF Plný text ve formátu HTML
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