Lucky or clever? From expectations to responsibility judgments
Lucky or clever? From expectations to responsibility judgments
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DOI：
10.1016/j.cognition.2018.03.019
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发表时间：
2018-08-01
期刊：
影响因子：
3.4
通讯作者：
Tenenbaum, Joshua B.
中科院分区：
文献类型：
--
作者：
Gerstenberg, Tobias;Ullman, Tomer D.;Tenenbaum, Joshua B.
人们如何让他人对其行为的后果负责？我们提出了一个计算模型，将责任归因于观察到的行为所揭示的人的行为，以及人的行为在导致结果中所起的因果作用。该模型首先通过观察某人的行为来推断某人是什么类型的人。然后，它将对一个人的行为方式的先前预期与观察该人的行为后的后验预期进行比较。该模型预测，当后验期望低于先验期望时，一个人会因负面结果而受到指责；如果后验期望大于先验期望，则因积极结果而受到赞扬。我们通过使用反事实模型来模拟一个人的行为的因果作用，该模型考虑该行为与对结果至关重要的程度。该模型通过覆盖一系列不同情况的三个实验，以高度定量的准确性捕捉参与者的责任判断。它还解决了文献中关于行动期望和责任判断之间关系的现有难题。意外行为是否会产生更多或更少的信用，取决于该行为是否可以诊断未来绩效的好坏。
How do people hold others responsible for the consequences of their actions? We propose a computational model that attributes responsibility as a function of what the observed action reveals about the person, and the causal role that the person's action played in bringing about the outcome. The model first infers what type of person someone is from having observed their action. It then compares a prior expectation of how a person would behave with a posterior expectation after having observed the person's action. The model predicts that a person is blamed for negative outcomes to the extent that the posterior expectation is lower than the prior, and credited for positive outcomes if the posterior is greater than the prior. We model the causal role of a person's action by using a counterfactual model that considers how close the action was to having been pivotal for the outcome. The model captures participants' responsibility judgments to a high degree of quantitative accuracy across three experiments that cover a range of different situations. It also solves an existing puzzle in the literature on the relationship between action expectations and responsibility judgments. Whether an unexpected action yields more or less credit depends on whether the action was diagnostic for good or bad future performance.