Automatic value learning results in counterproductive human behavior

Abstract

Humans are adept at accurately estimating the value of available choices from accumulated experience. However, cognitive processing also incorporates irrelevant information during deliberation, undermining decision accuracy. Here, we show that credit assignment operates automatically, allowing irrelevant action features to acquire value and impair choice behavior. Across four preregistered experiments (N = 504, 158, 195, 319) and a re-analysis of previously published data (N = 50), we examine outcome-irrelevant learning to spatial-motor and visual action features under conditions of explicit instruction and extensive training. In all cases, automatic value updating persists even when participants clearly understood which features were non-predictive of reward, and reliance on these irrelevant values led to suboptimal choices. Moreover, working memory capacity, known as a key regulatory resource, predicts the magnitude of this automatic outcome-irrelevant learning. Collectively, our results broaden the concept of automatic cognitive processing beyond the selective-attention literature to encompass reinforcement learning mechanisms. Humans use rewards to learn which actions are worth repeating. Here, the authors demonstrate an automatic tendency to credit unrelated actions for these rewards, driving suboptimal choices.