Curated from: nytimes.com
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The ongoing epidemic, due to its unknown nature, has provided us with a lot of uncertainties related to the characteristics, severity, mortality rate, infectious rate and spread of the disease. These uncertainties make it all the more deadly.
Conflicting guidelines (like on the use of masks) and ad hoc statements have made many people skeptical of the experts, in this post-truth society.
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In statistical science, risk is an important uncertainty, but a comparing of risks sometimes does not take into account certain human factors, leading to misinformation or even disinformation. This is due to the statistical models being oversimplifications of the real world.
Statistical data is a ‘Map’, not the actual territory.
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Uncertainty triggers an ambiguity aversion (a preference for known risks over unknown risks) among people as they feel unsettled and in limbo due to the lack of sure footing of information.
A study suggests that it is better to be completely transparent about the uncertainty than to be ambiguous.
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