Benefits of commitment in hierarchical inference

Abstract

Humans have the tendency to commit to a single interpretation of what has caused some observed evidence rather than considering all possible alternatives. This tendency can explain various forms of confirmation and reference biases. However, committing to a single high-level interpretation seems short-sighted and irrational, and thus it is unclear why humans seem motivated to pursue such strategy. In a first step toward answering this question, we systematically quantified how this strategy affects estimation accuracy at the feature level in the context of two universal hierarchical inference tasks, categorical perception and causal cue combination. Using model simulations, we demonstrate that although estimation is generally impaired when conditioned on only a single high-level inter-pretation, the impairment is not uniform across the entire feature range. On the contrary, compared to a full inference strategy that considers all high-level interpretations, accuracy is actually better for feature values for which the probability of an incorrect categorical/structural commitment is relatively low. That is to say, if an observer is reasonably certain about the high-level interpretation of the feature, it is advantageous to condition subsequent feature inference only on that particular interpretation. We also show that this benefit of commitment is substantially amplified if late noise corrupts information processing (e.g., during retention in working memory). Our results suggest that top-down inference strategies that solely rely on the most likely high-level interpretation can be favorable and at least locally outperform a full inference strategy.