群体决策
背景(考古学)
不公平厌恶
感知
政府(语言学)
过程(计算)
群(周期表)
微观经济学
计算机科学
社会心理学
心理学
经济
数学
不平等
生物
操作系统
数学分析
哲学
古生物学
神经科学
有机化学
化学
语言学
作者
Ming Tang,Huchang Liao
出处
期刊:Omega
[Elsevier]
日期:2023-12-03
卷期号:124: 103015-103015
被引量:3
标识
DOI:10.1016/j.omega.2023.103015
摘要
In group decision making, the consensus model with minimum cost has been researched with the aim of improving group efficiency and saving resources. However, one limitation of the minimum cost consensus model is that the reach of consensus is usually at the expense of some group members. We consider two issues that we see as keys in group consensus: efficiency and fairness. We propose the price of fairness in the opinion revision process and give two kinds of fairness schemes. According to the individual's perception of inequity, we introduce inequity aversion parameters and classify experts into two types: experts with non-cooperative behaviors and with altruistic behaviors. Experts with altruistic behaviors will be allowed to contribute more than the recommended number of modifications. Then, we discuss how to achieve the tradeoff between efficiency and fairness. Furthermore, with the rapid development of social media, cloud, and e-government platforms, collective intelligence (CI), i.e., groups of individuals doing things collectively that seem intelligent, has been a hot topic. We expand our work to a crowd context with many individuals. We investigate how the opinion revision process and fairness schemes can influence the emergence of CI. Results suggest that the proportional fairness and max-min fairness have similar performance in stimulating CI. Moreover, the improvement of group accuracy is mainly related to two factors: the group consensus level of initial opinions and the relative distance between group aggregated opinion and the ground truth.
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