Sequential Sampling Beyond Decisions? A Normative Model of Decision Confidence

We study informational dissociations between decisions and decision confidence. We explore the consequences of a dual-system model: the decision system and confidence system have distinct goals, but share access to a source of noisy and costly information about a decision-relevant variable. The decision system aims to maximize utility while the confidence system monitors the decision system and aims to provide good feedback about the correctness of the decision. In line with existing experimental evidence showing the importance of post-decisional information in confidence formation, we allow the confidence system to accumulate information after the decision. We aim to base the post-decisional stage (used in descriptive models of confidence) in the optimal learning theory. However, we find that it is not always optimal to engage in the second stage, even for a given individual in a given decision environment. In particular, there is scope for post-decisional information acquisition only for relatively fast decisions. Hence, a strict distinction between one-stage and two-stage theories of decision confidence may be misleading because both may manifest themselves under one underlying mechanism in a non-trivial manner