Noise and bias – some controversies raised by the book ‘Noise: A Flaw in Human Judgment’, written by Daniel Kahneman, Olivier Sibony, Cass R. Sunstein

M. Szreder
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Abstract

The paper reviews and discusses the statistical aspects of the phenomenon called ‘noise’ which Daniel Kahneman, the Nobel Prize winning psychologist, and his colleagues present in their new book entitled ‘Noise: A Flaw in Human Judgment’. Noise is understood by the authors as an unexpected and undesirable variation present in people’s judgments. The variability of judgments influences decisions which are made on the basis of those judgments and, consequently, may have a negative impact on the operations of various institutions. This is the main concern presented and analyzed in this book. The objective of this paper is to look at the relationship between bias and noise – the two major components of the mean squared error (MSE) – from a different perspective which is absent in the book. Although the author agrees that each of the two components contributes equally to MSE, he claims that in some circumstances a reduction of noise can make accurate inference not less, but more difficult. It is justified that the actual impact of noise cannot be accurately determined without considering both bias and noise simultaneously.
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噪音和偏见——由丹尼尔·卡尼曼、奥利维尔·西伯尼、卡斯·r·桑斯坦合著的《噪音:人类判断的缺陷》一书引发了一些争议
本文回顾并讨论了诺贝尔心理学奖得主丹尼尔·卡尼曼及其同事在他们的新书《噪音:人类判断的缺陷》中提出的“噪音”现象的统计方面。噪音被作者理解为人们在判断中出现的一种意想不到的、不受欢迎的变化。判决的多变性影响到根据这些判决作出的决定,因此可能对各种机构的运作产生不利影响。这是本书提出和分析的主要问题。本文的目的是从不同的角度来研究偏差和噪声(均方误差(MSE)的两个主要组成部分)之间的关系,这在书中是没有的。虽然作者同意这两个分量对MSE的贡献是相等的,但他声称,在某些情况下,减少噪声不仅会减少准确的推断,而且会增加推断的难度。如果不同时考虑偏差和噪声,就不能准确地确定噪声的实际影响。
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