Dynamical system model predicts when social learners impair collective performance

被引:15
|
作者
Yang, Vicky Chuqiao [1 ]
Galesic, Mirta [1 ,2 ,3 ]
McGuinness, Harvey [4 ]
Harutyunyan, Ani [5 ]
机构
[1] Santa Fe Inst, Santa Fe, NM 87501 USA
[2] Complex Sci Hub Vienna, A-1080 Vienna, Austria
[3] Univ Vermont, Vermont Complex Syst Ctr, Burlington, VT 05405 USA
[4] Johns Hopkins Univ, Zanvyl Krieger Sch Arts & Sci, Baltimore, MD 21218 USA
[5] Sunwater Inst, North Bethesda, MD 20852 USA
基金
美国国家科学基金会;
关键词
collective decisions; dynamical system modeling; social learning; collective intelligence; INFORMATION; CONSENSUS; PARADOX; PROMOTE; WISDOM;
D O I
10.1073/pnas.2106292118
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
A key question concerning collective decisions is whether a social system can settle on the best available option when some members learn from others instead of evaluating the options on their own. This question is challenging to study, and previous research has reached mixed conclusions, because collective decision outcomes depend on the insufficiently understood complex system of cognitive strategies, task properties, and social influence processes. This study integrates these complex interactions together in one general yet partially analytically tractable mathematical framework using a dynamical system model. In particular, it investigates how the interplay of the proportion of social learners, the relative merit of options, and the type of conformity response affect collective decision outcomes in a binary choice. The model predicts that, when the proportion of social learners exceeds a critical threshold, a bistable state appears in which the majority can end up favoring either the higher-or lower-merit option, depending on fluctuations and initial conditions. Below this threshold, the high-merit option is chosen by the majority. The critical threshold is determined by the conformity response function and the relative merits of the two options. The study helps reconcile disagreements about the effect of social learners on collective performance and proposes a mathematical framework that can be readily adapted to extensions investigating a wider variety of dynamics.
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页数:5
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