231–240 of 541 posts
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Isn't that called Pascal's Wager?
Pascal's Wager is a fallacy resulting from plugging infinity into your risk analysis and interpreting ∞/0 in a way that suits you.
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Drug testing is a good example for most people to understand why Bayesian thinking is relevant. https://www.mun.ca/biology/scarr/4250_Bayes_Theorem.html Imagine that a driver gets hit by accident. He's tested as part of company policy, and tests positive. He gets fired, even though the test only really tells us there's a 33.2% chance he was actually using the drug. Real world drug tests are a lot worse than 1% false…
>All that matters is if an officer feels like fucking up your day. This is what most people don't seem to get. Devices like the ADE 651 or the GT200 were bought by the thousands by law enforcement agencies worldwide, not because they were stupid, but instead, so they could have another "data point" against you that they can use at their discretion. "Sorry, this dot blinked three times so I'm gonna have to detain you:…
Antonin Scalia (in)famously commented in one of the Supreme Court's dog-sniff 4th Amendment cases that obviously the police would want dogs that didn't produce false positive alerts, since they wouldn't want to waste their time searching where there were no drugs. The resulting caselaw sets up a situation where a dog can be wrong over half the time and still be used.
The concept that "probable cause on four legs" would be used simply in order to get to search where they otherwise couldn't was apparently unthinkable.
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The parent comment talks about scaling back the amount of rock climbing they do in order to reduce risk.. And now you are saying that they should go one more time, because a single climb is low risk?
Yes. I am saying their analysis of risk is incorrect, and therefore if that's the only reason they aren't climbing then they should climb more often.
After a long life of rock climbing, there's no significant risk of doing it one last time or 10 last times (ignoring the effect of old age itself and whatever).
But when you're in earlier stages of your life, you're asking a different question: You're asking, is this something I want to do hundreds or thousands of times in my life, knowing that each of those times has a small chance of ending my life? This becomes a completely different question.
If I'm 35, maybe I will climb 30 times per year on average for 30 years until I'm 65. That's 900 climbs in total. If my goal is to not die or experience serious injury from rock climbing even once in my life, I have to consider the chance that any one of those 900 climbs will result in serious injury or death. I don't know the numbers for the risks involved, but it seems reasonable to be cautious.
Maybe I don't want to give up on rock climbing altogether, but maybe I can scale it back. If I limit myself to 1 climb per year, that's 30 climbs in total. Much lower risk than with 900 climbs.
This is not a logical fallacy.
"Fifty thousand years ago there were these three guys spread out across the plain and they each heard something rustling in the grass. The first one thought it was a tiger, and he ran like hell, and it was a tiger but the guy got away. The second one thought the rustling was a tiger and he ran like hell, but it was only the wind and his friends all laughed at him for being such a chickenshit. But the third guy though…
"Yes, the VIX is overpriced. Although you can't make a living by shorting it. Both statements are true at the same time."
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Slippery slope is a fallacy, not a principle. Just because you took N steps, that doesn't necessarily mean you will take N+1 steps. It's a convincing fallacy because sometimes you do take N+1 steps. But just like in the article, heuristics aren't always right.
Slippery slope arguments aren't inherently fallacious. If you can justify one more climb on the grounds that probability of injury or death is very low then you will be able to justify every subsequent climb on the same basis.
Just because you can justify the next climb on the same basis, that doesn't mean you will. You could decide that you've already tested the odds one too many times.
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If you'll die if a roll of three dice comes up sixes, you're not really in a lot of danger. If you do it every day, you have about 15 months to live.
If you've already done it for 12 months without it happening though, the next 3 months are no more dangerous for you than for someone starting from scratch.
This story reminded me of a story written by a Czech biologist who studied animals in Papua-New Guinea and went to a hunt with a group of local tribesmen. The dusk was approaching, they were still in the forest and he proposed that they could sleep under a tree. The hunters were adamant in their refusal: no, this is dangerous, a tree might fall on you in your sleep and kill you . He relented, but silently considered…
Is 1:5000 an actually good assessment? I'd suspect it's very much not, especially if you avoid obviously dead trees and maybe move if a storm comes.
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Legitimate futurists are objecting to some pop-culture nonsense with NFT's, cryptocurrency, etc., often describing such things as scams. I suspect that the author may've had that in mind there. It may be sorta like the problem with science: there's real science and pop-culture science-flavored junk, and pop-culture audiences may perceive real scientists as dismissive because they're always so critical of the latest p…
> It may be sorta like the problem with science: there's real science and pop-culture science-flavored junk It's kind of an aside, but I think a lot of people (most?) who strongly identify with "science" really identify with science fiction.
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"There are bold X, and old X, but no old, bold X." Replace X with any practitioners subject to sufficient risk as a result of their practice. I first heard it in the context of mushroom foraging.
The risks are highest when learners are at a beginner to intermediate stage. They know the basics, and have gained some confidence, but don't know enough to get themselves out of trouble. This is called Stage 1 in the Gordon Model of learning: unconscious incompetence.