Research in psychology and related fields has documented a myriad of prediction biases, such as the underprediction of hedonic adaptation and the overprediction of other people’s concern for fairness. These prediction biases are ostensibly independent, each with its own cause. We argue, however, that many of these seemingly disparate biases are specific instances of a general bias—situation insensitivity: People are insensitive to variations in the situational variable that underlies the target variable (the variable to be predicted). Consequently, when encountering a condition in which the situational variable is at one of its ends such that the value of the target variable is low, people overpredict the value; conversely, when encountering a condition in which the situational variable is at its other end such that the value of the target variable is high, people underpredict it. Most prior research documenting prediction biases has focused on only one end of the situational variable and therefore has shown either only an overprediction bias or only an underprediction bias. We argue that at the other end of the situational variable, the originally documented bias can disappear or even reverse. Our framework not only explains known biases but also predicts new biases.

心理学及相关领域的研究已记录了无数的预测偏差，例如享乐主义适应的低估和其他人对公平的关注的高估。这些预测偏差表面上是独立的，每个都有其自身的原因。但是，我们认为，这些看似完全不同的偏见中有许多是普遍偏见的特定实例-情境不敏感：人们对作为目标变量（要预测的变量）基础的情境变量的变化不敏感。因此，当遇到情况变量处于其末端之一而目标变量的值较低的情况时，人们会过高地预测该值；反过来，当遇到情况变量处于另一端而目标变量的值很高时，人们会对其进行低估。先前大多数记录预测偏差的研究都只关注于情境变量的一端，因此显示出要么只是过高的预测偏差，要么就是低估的偏差。我们认为，在情境变量的另一端，最初记录的偏见可能消失甚至逆转。我们的框架不仅可以解释已知的偏差，还可以预测新的偏差。最初记录的偏见可能消失甚至逆转。我们的框架不仅可以解释已知的偏差，还可以预测新的偏差。最初记录的偏见可能消失甚至逆转。我们的框架不仅可以解释已知的偏差，还可以预测新的偏差。