Why we distort probability
Scientists identify the cognitive limitations that hamper our decision-
making

Date:
August 25, 2020
Source:
New York University
Summary:
A team of scientists has concluded that our cognitive limitations
lead to probability distortions and to subsequent errors in
decision-making.



FULL STORY ==========================================================================
The chances of a commercial airliner crashing are vanishingly small --
and yet many people are uncomfortable flying. Vaccination for many common childhood diseases entail almost no risk -- but parents still worry. Human perception of probabilities -- especially very small and very large probabilities -- can be markedly distorted and these distortions can
lead to potentially disastrous decisions.


==========================================================================
But why we distort probability is unclear. While the question has been previously studied, there is no consensus on its causes.

A team of scientists from New York University and Peking University,
using experimental research, has now concluded that our cognitive
limitations lead to probability distortions and to subsequent errors
in decision-making. The researchers have developed a model of human
cognitive limitations and tested its predictions experimentally, as
reported in the latest issue of the journal Proceedings of the National
Academy of Sciences.

The team, which included New York University's Laurence Maloney as
well as the University of Peking University's Hang Zhang, a professor,
and Xiangjuan Ren, a post-doctoral fellow, initiated the analysis by
examining the nature of distortions as a potential clue for explaining
this phenomenon.

"Probability distortion limits human performance in many tasks, and
we conjectured that the observed changes in probability distortion
with task was a kind of partial compensation for human limitations,"
explains Maloney. "A marathon runner with a sprained ankle will not run
as well as she might have with ankle intact, but the awkward, limping
gait we observe could in fact be an optimal compensation for injury."
The key step in the model is the recoding of probabilities that depends
on the range of probabilities in a task.

"Much like a variable magnification microscope, the brain can represent
a wide range of probabilities, but not very accurately, or a narrow
range at high precision," explains Maloney. "If, for example, a task
involves reasoning about the probability of various causes of death,
for example, then the probabilities are all very small (thankfully) and
small differences are important. We can set the microscope to give us high resolution over a limited window of very small probabilities. In another
task we might accept less precision in return for the ability to represent
a much wider range of probabilities." Zhang, Ren, and Maloney set out to
test this model in two experiments, one in which subjects made typical
economic decisions under risk (e.g. choosing between a 50:50 chance of
$200 and the certainty of $70) and one involving judgements of relative frequency (the relative frequency of black and white dots appearing on
a computer screen). The two experiments together tapped into the basic
ways we use probability and frequency in everyday life. The researchers
found that their model predicted human performance far better than any
previous model.

They discovered that -- like the marathon runner -- people's limitations
were costly but, subject to those limitations, we do as well as we
possibly can.

Zhang and Ren are part of Peking University's School of Psychological
and Cognitive Sciences; Maloney is a professor in NYU's Department of Psychology and Center for Neural Science.

This research was supported by the National Eye Institute of the National Institutes of Health (EY019889).


========================================================================== Story Source: Materials provided by New_York_University. Note: Content
may be edited for style and length.


========================================================================== Journal Reference:
1. Hang Zhang, Xiangjuan Ren, Laurence T. Maloney. The bounded
rationality
of probability distortion. Proceedings of the National Academy of
Sciences, 2020; 201922401 DOI: 10.1073/pnas.1922401117 ==========================================================================

Link to news story: https://www.sciencedaily.com/releases/2020/08/200825145228.htm

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