We provide evidence for a bias that we call “representative signal distortion” (RSD) which is particularly relevant to settings of statistical discrimination. Experimental subjects distort their evaluation of new evidence on individual group members and interpret such information to be more representative of the group to which the individual belongs (relative to a reference group) than it really is. This produces a discriminatory gap in the evaluation of members of the two groups. Because it is driven by representativeness, the bias (and the discriminatory gap) disappears when subjects are prevented from contrasting different groups; because it is a bias in the interpretation of information, it disappears when subjects receive information before learning of the individual’s group. We show that this bias can be easily estimated from appropriately constructed datasets and can be distinguished from previously documented inferential biases in the literature. Importantly, we document how removing the bias produces a kind of free lunch in reducing discrimination, making it possible to significantly reduce discrimination without lowering accuracy of inferences.

中文翻译：

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看什么是代表

我们为我们称之为“代表性信号失真”(RSD) 的偏差提供了证据，这与统计歧视的设置特别相关。实验对象歪曲了他们对个别群体成员的新证据的评估，并将这些信息解释为比实际情况更能代表个人所属的群体（相对于参考群体）。这在对两个群体成员的评价中产生了歧视性的差距。因为它是由代表性驱动的，所以当受试者被阻止对比不同的群体时，偏见（和歧视性差距）就会消失；因为它是对信息解释的偏见，所以当受试者在了解个人群体之前接收信息时，它就会消失。我们表明，这种偏差可以很容易地从适当构建的数据集中估计出来，并且可以与文献中先前记录的推理偏差区分开来。重要的是，我们记录了消除偏见如何在减少歧视方面产生一种免费午餐，从而有可能在不降低推理准确性的情况下显着减少歧视。