Live data from Hacker News

Heuristics that almost always work

astralcodexten.substack.com

241–250 of 541 posts

Re: Heuristics that almost always work

#241
Reading through the comments shows that basic understanding of probability is crucial. If an outcome of an event is labeled with a probability of 1/10, what that really translates to is that if the event happens 10 times, you can expect the outcome to occur once.

The whole talk about N+1 gives the same probability as N is not right.

Re: Heuristics that almost always work

#242
post #208

Earlier quoted context omitted.

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.

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 pointing out that a reasonable person, understanding independence of events and not falling prey to any fallacy, could reasonably make this decision based on their personal risk tolerance

Re: Heuristics that almost always work

#243

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…

[deleted]

Re: Heuristics that almost always work

#244
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.

Don't know about Papa New Guinea, but where I live we have had lots of healthy trees fall over from a bit of wind when the ground is soaked.

Re: Heuristics that almost always work

#245

Earlier quoted context omitted.

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

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.

When accounting for human psychology it does have validity: doing an enjoyable activity "one more time" has a risk of a habit forming, which has a non-zero probability. It is indeed possible.

The argument can certainly be used in a fallacious manner (e.g. by greatly exaggerating the probability of the further steps, saying they are inevitable if the first step is taken, etc.). It's logically valid to say that the first step enables subsequent steps to be taken.

Edit: I'd say that the slippery slope is perfectly valid rule of thumb in a lot of 'adversarial' situations. Once one side makes an error or fails somehow, the balance between the two sides can be disrupted leading to one 'side' gaining momentum. Just as between people, a similar 'adversarial' process can occur within the minds of individuals: between two ideas or patterns of thought/behaviour, one idea can gain momentum after a decision has been reached. Precedence is a strong force.

Re: Heuristics that almost always work

#246
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.

Remember that the relevant set isn't the set of all trees, but the set of trees old enough to be large enough to sleep under. That means the average lifetime would be: (number of years it takes for a tree to become big enough to sleep under) + 13.7.

I would still guess that the number is wrong, I suspect that trees have a longer life on average from becoming what we would consider "big" until they fall over. But it's still an important detail.

Re: Heuristics that almost always work

#247
post #208

Earlier quoted context omitted.

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.

I think it the argument is to make a lifetime risk assessment, opposed to an individual event risk assessment.

If your tolerance is X% death/life, you can calculate the climbing frequency that falls below the threshold.

On the plus side, if you assume the events are independent, you can recalculate and increase the frequency after each climb.

Re: Heuristics that almost always work

#248
post #76

Earlier quoted context omitted.

A coworker and I were once stuck in an office building for an hour or two. We were working as consultants at a client's building and ended up working rather late. Not particularly late by software programmer standards, but clearly exceptionally late by the culture of the client company. At some point in the evening all the exit doors, including the front door, became armed, and this was conspicuously noted as when we…

That security guard was performing the important function of allowing the management to legally tick the "we have a security guard" box on the insurance form.

This is what happens when we allow proxies for truth fill in for truth. Or another way to think of it when metrics become the goal.

Re: Heuristics that almost always work

#249
post #208

Earlier quoted context omitted.

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.

I don't know how you can make this claim objectively without knowing that individual's preferences.

If an individual decides their risk tolerance is that they will not accept a one in a million chance of injury from rock climbing, how is their analysis incorrect?

Re: Heuristics that almost always work

#250
Does he really not understand how Brier scores work? If you are unable to distinguish between more risky and non-risky instances (e.g. specify when it's only 99% not happening, vs. usually when it's 99.99% not happening) then of course you aren't adding any value above and beyond the heuristic.

Additionally, getting the base rate right is important when considering lifetime risk and the costs vs. benefits of taking action or engaging in further screening - e.g. missing two or three cancer patients might be worth the benefits of not subjecting large numbers of patients to secondary screening.

Post reply on HN