Recent models of cognition suggest that the brain may implement predictive processing, in which top-down expectations constrain incoming sensory data. In this perspective, expectations are updated (error minimization) only if sensory data sufficiently deviate from these expectations (prediction error). Although originally applied to perception, predictive processing is thought to generally characterize cognitive architecture, including the social cognitive processes involved in ideological thinking. Scaling up these simple computational principles to the social sphere outlines a path by which group members may adopt shared ideologies and beliefs to predict behavior and cooperate with each other. Because ideological judgments are of specific interest to others in our political groups, we may increasingly regulate each other’s thinking, sharing the process of error minimization. In this paper, we outline how this process of shared error minimization may lead to shared ideologies and beliefs that allow group members to predict and cooperate with each other, and how, as a consequence, political polarization and extremism may result.

最近的认知模型表明，大脑可能会执行预测性处理，其中自上而下的期望会限制传入的感觉数据。从这个角度来看，只有在感觉数据充分偏离这些期望（预测误差）的情况下，才更新期望（错误最小化）。尽管预测处理最初应用于感知，但通常认为预测处理是认知体系的特征，包括意识形态思维中涉及的社会认知过程。将这些简单的计算原理扩展到社会领域，可以概述小组成员可以采用共同的意识形态和信念来预测行为并相互合作的道路。由于意识形态的判断是我们政治集团中其他人特别感兴趣的，因此我们可能会越来越多地规范彼此的思想，共享错误最小化的过程。在本文中，我们概述了最小化共享错误的过程可能如何导致共享的意识形态和信念，使团体成员能够相互预测和合作，以及由此如何导致政治两极化和极端主义。