To predict human choice, consider the context. Issue 10 (October 2021)

• Record Type: Journal Article
• Authors: Plonsky, Ori; Erev, Ido
• Is Part Of: Trends in cognitive sciences. Volume 25:Issue 10(2021)
• Page Start: 819
• Page End: 820
• Publication Date: 2021-10
• Subjects: machine learning -- reliance on small samples -- BEAST -- decisions under risk -- decisions under uncertainty; Cognitive science -- Periodicals; Cognitive neuroscience -- Periodicals; 153.05
• DOI: 10.1016/j.tics.2021.07.007
• Languages: English
• ISSNs: 1364-6613

Abstract

Abstract : Choice prediction competitions suggest that popular models of choice, including prospect theory, have low predictive accuracy. Peterson et al . show the key problem lies in assuming each alternative is evaluated in isolation, independently of the context. This observation demonstrates how a focus on predictions can promote understanding of cognitive processes.