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用于估计自身风险和总体基础率的乐观更新偏差有多稳健?

How robust is the optimistic update bias for estimating self-risk and population base rates?

作者信息

Garrett Neil, Sharot Tali

机构信息

Affective Brain Lab, Experimental Psychology, University College London, London, United Kingdom.

出版信息

PLoS One. 2014 Jun 10;9(6):e98848. doi: 10.1371/journal.pone.0098848. eCollection 2014.

Abstract

Humans hold unrealistically optimistic predictions of what their future holds. These predictions are generated and maintained as people update their beliefs more readily when receiving information that calls for adjustment in an optimistic direction relative to information that calls for adjustment in a pessimistic direction. Thus far this update bias has been shown when people make estimations regarding the self. Here, we examine whether asymmetric belief updating also exists when making estimations regarding population base rates. We reveal that while participants update beliefs regarding risk in the population in an asymmetric manner, such valence-dependent updating of base rates can be accounted for by priors. In contrast, we show that optimistic updating regarding the self is a robust phenomenon, which holds even under different empirical definitions of desirable information.

摘要

人类对自己的未来持有不切实际的乐观预测。这些预测得以产生并维持,是因为当人们接收到需要朝着乐观方向调整的信息时,比接收到需要朝着悲观方向调整的信息时,更容易更新自己的信念。到目前为止,当人们对自我进行估计时,这种更新偏差已经得到证实。在此,我们研究在对总体基础概率进行估计时,是否也存在不对称信念更新。我们发现,虽然参与者以不对称的方式更新对总体风险的信念,但这种基础概率的效价依赖型更新可以由先验因素来解释。相比之下,我们表明,关于自我的乐观更新是一种稳健的现象,即使在对理想信息的不同实证定义下也依然成立。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7e05/4051586/d02e4c249c8c/pone.0098848.g001.jpg

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