http://whatho.in/2013/plausibility-versus-probability/ refers to pp 155-156 of 533 of Thinking, Fast and Slow by Daniel Kahneman. I'll use one of Kahneman's other questions from p 156:
A massive flood somewhere in North America next year, in which more than 1,000 people drown
An earthquake in California sometime next year, causing a flood in which more than 1,000 people drown
The California earthquake scenario is more plausible than the North America scenario, although its probability is certainly smaller. As expected, probability judgments were higher for the richer and more entdetailed scenario, contrary to logic. This is a trap for forecasters and their clients: adding detail to scenarios makes them $\color{darkred}{more \, persuasive}$, but less likely to come true.
Since Pr('adding detail') means adding more events to the intersection in $\Pr(\cap A_j)$,
and $Pr(A \wedge B) \le Pr(X)$ where X is either A or B, thus:
$\Pr(\cap_{j \le 1} A_j) \le \Pr(\cap_{j \le 1} A_{j+1})$, or in words, 'adding detail to scenarios makes them...less likely to come true' (♦).
Yet how does this make them $\color{darkred}{more \, persuasive}$ or more plausible? Doesn't (♦) prove 'less probable'? What did I miss in the definition of plausible which contains the word probable?
Perhaps people are subconsciously doing a conditional probability, and they are actually comparing Pr(Flood with 1000 dead in U.S.) with Pr(Flood with 1000 dead in CA | Earthquake in CA). Then the second (conditional) probability could well be greater than the first (unconditional) probability.
[The people doing this would not necessarily need to know any probability theory to make a qualitative comparison of this type.]