Surprisingly Rational: Probability theory plus noise explains biases in judgment

TL;DR

This paper proposes that human probability judgment biases are due to random noise in reasoning, and when accounting for this noise, judgments align closely with probability theory, challenging the view that people use heuristics.

Contribution

It introduces a noise-based model showing that human probabilistic reasoning largely follows probability theory, with biases explained by random variation rather than heuristic shortcuts.

Findings

Judgments for some expressions match probability theory closely.

Noise accounts for biases like conservatism and conjunction fallacy.

Systematic deviations occur for other probabilistic expressions.

Abstract

The systematic biases seen in people's probability judgments are typically taken as evidence that people do not reason about probability using the rules of probability theory, but instead use heuristics which sometimes yield reasonable judgments and sometimes systematic biases. This view has had a major impact in economics, law, medicine, and other fields; indeed, the idea that people cannot reason with probabilities has become a widespread truism. We present a simple alternative to this view, where people reason about probability according to probability theory but are subject to random variation or noise in the reasoning process. In this account the effect of noise is cancelled for some probabilistic expressions: analysing data from two experiments we find that, for these expressions, people's probability judgments are strikingly close to those required by probability theory. For other expressions this account produces systematic deviations in probability estimates. These deviations explain four reliable biases in human probabilistic reasoning (conservatism, subadditivity, conjunction and disjunction fallacies). These results suggest that people's probability judgments embody the rules of probability theory, and that biases in those judgments are due to the effects of random noise.