Individual differences in the perception of probability.

Ronald Van Den Berg,Mel W Khaw,Michael Woodford,Luminita Stevens

doi:10.1371/journal.pcbi.1008871

Ronald Van Den Berg, Mel W Khaw + Show 2 more

Open Access

https://doi.org/10.1371/journal.pcbi.1008871

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Abstract

In recent studies of humans estimating non-stationary probabilities, estimates appear to be unbiased on average, across the full range of probability values to be estimated. This finding is surprising given that experiments measuring probability estimation in other contexts have often identified conservatism: individuals tend to overestimate low probability events and underestimate high probability events. In other contexts, repulsive biases have also been documented, with individuals producing judgments that tend toward extreme values instead. Using extensive data from a probability estimation task that produces unbiased performance on average, we find substantial biases at the individual level; we document the coexistence of both conservative and repulsive biases in the same experimental context. Individual biases persist despite extensive experience with the task, and are also correlated with other behavioral differences, such as individual variation in response speed and adjustment rates. We conclude that the rich computational demands of our task give rise to a variety of behavioral patterns, and that the apparent unbiasedness of the pooled data is an artifact of the aggregation of heterogeneous biases.

Highlights

Decision-makers often report distorted probabilities, despite the ubiquitous day-to-day experience with probability estimation
Despite the ubiquitous observation that humans are biased in estimating probabilities, a new laboratory task reportedly elicits unbiased performance
The type of distortion differs across tasks and contexts, but two commonly identified patterns are conservatism, where individuals report probabilities that are less extreme than the true values, and repulsive biases away from 50%, where extreme values are disproportionately reported

Summary

Introduction

Decision-makers often report distorted probabilities, despite the ubiquitous day-to-day experience with probability estimation. The tendencies of probability estimates to be distorted either around the average value or towards the extremes result in variants of S-shaped response functions These seemingly conflicting patterns of biased judgment reflect, at least in part, differences in the tasks analyzed. Studies involving the estimation of an observed frequency often find conservatism, such as in visual judgments of dots of different colors [3, 4], sequences of letters [5], and ratios of auditory durations [6] Reversals of this bias have been documented, though they are less common [2, 7, 8]. In the probability calibration literature, overconfidence has been documented more frequently (for a review, see [9]) These experiments involve asking subjects a question about a unique event (e.g., a general knowledge question). The modal bias can reverse, depending on the difficulty level of questions [11]

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