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Heuristics that almost always work

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Re: Heuristics that almost always work

#491
post #258
post #199

Earlier quoted context omitted.

Which is the rub, right? How can a non-expert reasonably come to a conclusion of whether or not an expert's prediction is baseless or is actually solid/insightful?

I came up with the Goldilocks (meta?-)heuristic[1] for that: Only trust someone to say X is too high if they can also tell you when X would be too low. A corollary of which would be e.g. "Don't trust a skeptic that says 'X won't Change The World' unless they can tell you which developments would Change The World." [1] Or Scylla-Charybdis Heuristic if you prefer: http://blog.tyrannyofthemouse.com/2015/12/the-scylla-ch…

That is actually really useful.

Re: Heuristics that almost always work

#492

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…

Taleb also discussed this in his work.

Any payoff from a trade which has even a very tiny probablity of making you go bust is zero.

Because once you go bust you are not going to be doing trading anymore.

He calls these Uncle Points.

Re: Heuristics that almost always work

#493

Earlier quoted context omitted.

The expected value will be 6³ = 216 days or about 7 months. Where do you get the factor of two from? Also, “not really in a lot of danger”? Those odds are worse than that of a 100 year old in the USA (they have a life expectancy of over two years) Certainly, as an additional risk, it’s high.

You forget: once you roll three 6s in a row, you're dead, and you don't roll any more. Your expected calculation assumes that people keep rolling after they get 666. Though I'm not sure where they got their figure from, because there isn't an “expected time to live”; there's a 90% probability to live time, a 5% probability to live time…

There’s a difference between expected value of number of days you’ll survive and the number of days a given fraction of the subjects will survive, but I don’t see either supporting the claim “If you do it every day, you have about 15 months to live”.

  (215/216)^450 ≈ 0.124
, so about one in eight will survive for 15 months or more. The “5% probability to live” time is around day 645 (about 1¾ years):

  (215/216)^645 ≈ 0.0501
the “half will survive at least for” point is around 5 months:

  (215/216)^149 ≈ 0.501

Re: Heuristics that almost always work

#494

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…

What is his name? Is he, by any chance, from the biological faculty in Ceske Budejovice?

Re: Heuristics that almost always work

#495
post #61

Earlier quoted context omitted.

It's a great example. This is the very reason I have scaled back the amount of time I rock climb as I've gotten older -- not because any individual outing is dangerous, but there's an element of Russian roulette wherein the mere act of doing it more often dramatically changes the risk.

> the mere act of doing it more often dramatically changes the risk. Kind of. However, you already know that the first N outings didn't have a disaster. So those should be discarded from your analysis. Doing it N times more has a lot of risk, doing it the N+1th time has barely any.

The point is that they're changing their habits. Of course we ignore the n times they've gone before, now instead of their habits meaning they'd go m more times in the future, they're going to be going p times in the future for some p that is much less than m.

So it's not about how often they've done it over their lifetime so far, but about how many times they will be doing it over the rest of their life.

Re: Heuristics that almost always work

#496

I read them as sloppy caricatures that provide little value to the conversation. Let's take the security guard: "The only problem is: he now provides literally no value. He’s excluded by fiat the possibility of ever being useful in any way. He could be losslessly replaced by a rock with the words “THERE ARE NO ROBBERS” on it." That is blatantly not true, the guard provide value since the wanna-be robbers don't know w…

Are you reading the deeper lesson though? The individual examples aren't meant to be authoritative. He was trying to illustrate the very thing you are bringing up. Namely that lazy heuristics create information cascades. The information cascades can have positive effects, as you point out, but they can have profoundly negative consequences, which is the point of the whole article. We shouldn't use or intellectually t…

> Are you reading the deeper lesson though?

The "deeper" (?) lesson and subtext I'm hearing from the OP is that we should get excited like little children about each and every new fad, because, you know, this may just be the 0,01% when it actually matters, and we don't want to miss it.

Well, I don't mind using "lazy heuristics" and waiting around a little to see if something happens. No need to hurry or jump around. Plenty of time.

Re: Heuristics that almost always work

#497

Earlier quoted context omitted.

That's true, but usually when we are deciding which actions to take, we're not comparing "I take actionA" versus "I take actionB," rather than comparing "I take actionA" versus "some random other person takes actionA."

OK, the next 3 months are no more dangerous for you than if you hadn't spent the last 12 months doing it. What you did in the past has no bearing on the chances going forward. I'm not sure if it's more clear to say it like that or not. Clearly, humans have a lot of trouble speaking and thinking clearly about statistics. The next three months are no riskier than your first three months were. They don't become more ris…

For the dice roll example that is true. But other examples it isn’t. For example the MTBF of a device that has run for x hours approaching the MTBF is probably more likely to fall in the next x hours. Or if there is some cyclic behavior. Like waiting outside for a hot day.

Re: Heuristics that almost always work

#498

Earlier quoted context omitted.

Luckily newer cars won't stop beeping if you forget your seatbelt, so the problem is mitigated. Not so for parachutes, apparently.

To be honest, I never wear a parachute when driving!

Better not drive close to cliffs then!

Re: Heuristics that almost always work

#499
post #496

Earlier quoted context omitted.

Are you reading the deeper lesson though? The individual examples aren't meant to be authoritative. He was trying to illustrate the very thing you are bringing up. Namely that lazy heuristics create information cascades. The information cascades can have positive effects, as you point out, but they can have profoundly negative consequences, which is the point of the whole article. We shouldn't use or intellectually t…

> Are you reading the deeper lesson though? The "deeper" (?) lesson and subtext I'm hearing from the OP is that we should get excited like little children about each and every new fad, because, you know, this may just be the 0,01% when it actually matters, and we don't want to miss it. Well, I don't mind using "lazy heuristics" and waiting around a little to see if something happens. No need to hurry or jump around.…

...no the surface lesson is that lazy heuristics produce habits that provide the illusion of certainty without any rigour backing up those beliefs; the outcome may correspond with reality but the process getting you there isn't rational or dependable, because it always produces the same output regardless of input.

The "deeper lesson" if there is such a thing here is that experts are people too, and just as fallible, only in ways that are generally invisible to everyone but another expert.

Re: Heuristics that almost always work

#500

Earlier quoted context omitted.

That's the reason why I don't cycle in London. When I moved there, I thought I would be using my bike daily like I was used to. But over the span of a few years, I'm pretty sure the risk of serious injury becomes significant. For rock climbing, you're probably right. I remember training in a climbing hall, when I saw someone falling off the highest wall. The tenant of the hall didn't look surprised at all. Apparently…

You can contrast the odds of getting injured with the health benefits. The cardiovascular benefits would seem to outweigh the risks of getting injured from a mathematical point of view. See e.g. https://blogs.bmj.com/bjsm/2018/12/12/pedal-power-the-health...

Lots of ways to get even better cardio benefits with much less risk.
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