2 HN users recommended this commentary2 months2017–2021score 2
Years with an HN recommendation, 2007–2026
HN cites it when arguing that different risks follow different distributions and should be judged by growth rates and tails rather than current counts.
Nassim Taleb argues that evidence on terrorism risk presented in media is statistically naive, using extreme value theory without math to separate fat-tailed risks like Ebola and terrorism from thin-tailed ones.
“Watch this to understand that we're talking about two different distributions” (HN, 2017)
I will give an alternative explanation why people fear terrorism: Falling from a ladder also kills more people than terrorism, right, but this is not what people are afraid of. Watch this to understand that we're talking about two different distributions: [this video] Terrorism SUDDENLY increases the odds of you being killed by it. And that is what - rightfully - scares people. Example: Before 9/11 the chances of being killed by terrorism was let's say 0.000000.....1%. After 9/11 the chance SUDDENLY increased a hundredfold. That change in probability never ever happened in the distributions of car-accidents, being shot in the US or falling ladders.
Taleb on why terrorism and ladder falls follow different distributions
No it isn't, in this case. I think Taleb has the best summary of this, for all his flaws: [this video] In short, risk due to coconuts vs sharks is a valid comparison because we have good priors about growth rates, and they are similar. Coconuts vs covid is a terrible, terrible comparison because again we have good priors on growth but they are mind-bogglingly different functions of time.
Funny, Nassim Taleb, a worldwide (if controversial) risk probability expert, would say that you are the one which is being very bad at reasoning with probabilities, because you are putting Ebola and terrorism in the same class of risk as falling off a ladder: [this video]
Taleb argues Ebola and terrorism are a different risk class
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