Live data from Hacker News

Heuristics that almost always work

astralcodexten.substack.com

251–260 of 541 posts

Re: Heuristics that almost always work

#251
post #115
post #87

Earlier quoted context omitted.

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.

1:5000 would suggest an average lifetime of 13.7 years for a grown tree (i.e. not counting the years where it's too young to sleep under), and that's before the ability to avoid trees that look more likely to fallover. I don't know anything about trees around there, maybe they're really short-lived? For forests around here, it's a gross overestimate.

Even if you multiple by ten this still means you'll end up with one dead hunter every few decades (depending on how often they hunt and how many hunters there are exactly). That seems like quite a high risk for a small self-sustained community.

Also, I bet it's not just the tree you're sleeping under that poses a risk, but also other trees in the vicinity that might fall on you. In a forest there are probably a bunch of trees "in range".

All of that said, I've often camped and slept in forests, as have many of my friends, and I've never heard of anyone being killed or injured by a falling tree, or ever heard or seen any "don't sleep under a tree, it might kill you"-advice, so I don't know...

Re: Heuristics that almost always work

#252

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…

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.

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, it happens frequently.

That being said, if you serious about security, I'm sure the risk can be minimal.

Re: Heuristics that almost always work

#253
post #131

The doctor rings true. I had 3 separate doctors on 3 separate occasions diagnose my 21 month old son with an ear infection, instead of the plum-sized malignant brain tumour that it was. From their point of view, pediatric brain tumours are very rare and ear infections are common. Their 99% heuristic almost killed him. That was 2010. He survived and is now a vibrant 13 year old, but only because of one curious intern/…

That is amazing, and congratulations! Do you mind sharing some more info on the cancer type? I thought most malignant brain tumors didn't have outcomes like this.

Re: Heuristics that almost always work

#254
post #87

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.

If the story is based on Jared Diamond’s story, the tree was dead, and the estimate was 1:1000. https://www.openculture.com/2015/08/jared-diamond-underscore...

Re: Heuristics that almost always work

#255
post #208

Earlier quoted context omitted.

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.

I think what you're missing is that they are not avoiding "going rock climbing one more time"; they are avoiding "being a person who habitually rock climbs", because while each excursion is low-risk the aggregate effect will be high risk. It's like smoking -- one cigarette won't appreciably impact your health, but "being a smoker" will. None of this intended to cast aspersions on rock climbing in particular, just poi…

Yes, or more accurately there is a frequency of climbing outings at which the marginal increase in satisfaction from an extra climbing is no longer sufficient to justify the increased risk.

Re: Heuristics that almost always work

#256

Earlier quoted context omitted.

The "slippery slope" principle applies here though: N+1 enables N+2, which enables N+3 and so on.

but the risk is independent. so once you do the N+1 time safely, you are back to N and your next time is _also_ just an N+1.

The risk is independent but the marginal enjoyment isn't. You don't get double the satisfaction from climbing twice as much.

Re: Heuristics that almost always work

#257
post #87

Earlier quoted context omitted.

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.

You could calculate it by taking the average lifetime of a tree and dividing by the length of time slept and the number of trees in squashing distance.

Only if tree death is uniformly distributed over a tree's lifetime for some bizarre reason. And it isn't.

The logic in the story is BS. First, you would never, ever get into a car with that logic. Second, trees just aren't that ephemeral. People who live in a forest would be very aware of when they do or don't fall (or more problematically, drop large branches.) It's not as straightforward as just avoiding storms or dead-looking trees. Sustained wet weather, especially after a period of dry weather, is a common cause. As is the opposite for some trees (eg oak trees drop limbs in sustained hot dry weather.) As for disease or other causes, an experienced hunter in a familiar area could tell at a glance.

The message I got from the story is that they probably did have a very good reason. They either thought it would be too hard to communicate, or they were themselves cargo-culting the falling tree excuse when the reality was more likely to be... I dunno, snakes or nasty bugs or annoying sticky sap or whatever.

Re: Heuristics that almost always work

#258
post #199

The last sentence of the edit the author provides is the key insight of this piece. > the existence of experts using heuristics causes predictable over-updates towards those heuristics. That's the essence of this piece. If you expect that consultation with experts will leave you with a more accurate picture of things than before consultation, you should first be sure that their heuristics are not equivalent to readin…

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-charybd...

Re: Heuristics that almost always work

#259
Agree with the point the author is making, but here's an added question – is it wrong to always trust these heuristics regardless?

To use the doctor example, over-diagnosing symptoms is as harmful as under-diagnosing them. You cannot prescribe an MRI and other advanced tests to every patient who walks into your door, since (1) they are expensive and capacity is limited and (2) there is a chance you will get a false positive and end up in a worse condition than you started from. Maybe always sending patents home with an aspirin until the symptoms get worse is the right thing to do?

In more generic terms, betting on the 0.1% outcome is a risk, and one that you may not be able to afford to take.

Re: Heuristics that almost always work

#260

I don't understand how articles like this get upvoted. Who is getting value from this? This reads like some generic LinkedIn CEO post that sounds deep on the surface but actually means nothing.

I'm with you. SSC posts are high on rhetoric and low on actual conceptual knowledge/insights. The examples are ridiculously long and somewhat contrived. s.
Post reply on HN