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Folke, T.

Publications and source records attributed to Folke, T..

2 recordsLinked to original sources

Cherry-picking information: humans actively sample evidence to support prior beliefs

No one likes to be wrong. Previous research has shown that participants may underweight information incompatible with previous choices, a phenomenon called confirmation bias. In this paper we argue that a similar bias exists in the way information is actively sought. We investigate how choice influences information gathering using a perceptual choice task and find that participants sample more information from a previously chosen alternative. Furthermore, the higher the confidence in the initial choice, the more biased information sampling becomes. As a consequence, when faced with the possibility of revising an earlier decision, participants are more likely to stick with their original choice, even when incorrect. Critically, we show that agency controls this phenomenon. The effect disappears in a fixed sampling condition where presentation of evidence is controlled by the experimenter, suggesting that the way in which confirmatory evidence is acquired critically impacts the decision process. These results suggest active information acquisition plays a critical role in the propagation of strongly held beliefs over time.

neuroscience

Confirmation bias optimizes reward learning

Confirmation bias--the tendency to overweight information that matches prior beliefs or choices--has been shown to manifest even in simple reinforcement learning. In line with recent work, we find that participants learned significantly more from choice-confirming outcomes in a reward-learning task. What is less clear is whether asymmetric learning rates somehow benefit the learner. Here, we combine data from human participants and artificial agents to examine how confirmation-biased learning might improve performance by counteracting decisional and environmental noise. We evaluate one potential mechanism for such noise reduction: visual attention--a demonstrated driver of both value-based choice and predictive learning. Surprisingly, visual attention showed the opposite pattern to confirmation bias, as participants were most likely to fixate on "missed opportunities", slightly dampening the effects of the confirmation bias we observed. Several million simulated experiments with artificial agents showed this bias to be a reward-maximizing strategy compared to several alternatives, but only if disconfirming feedback is not completely ignored--a condition that visual attention may help to enforce.

animal behavior and cognition