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Heuristics that almost always work

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Re: Heuristics that almost always work

#31
One way to solve this is that instead of asking for a yes - no answer, you ask for a ranking, and you disallow equally likely. Is bigfoot more or less likely than telepathy? Is telepathy more ore less likely than the vaccines being dangerous? Are the vaccines being dangeroues more or less likely than some guy achieving cold fusion in his garage?

A ranking forcibly brings the metric away from accuracy (which the heuristic can score well on) to something based around precision-recall (which it cannot).

Re: Heuristics that almost always work

#32

One could add: The Barking Dog Barks at everything all the time, people learn to ignore it. Then, when there's real danger, no one cares, providing literally no value and becoming only an annoyance. It's kind of like a dual for the security guard one.

That's only true if the burglar knows that the owners ignore the dog's barking.

Re: Heuristics that almost always work

#34

This is where Bayesian inference really signs. For the security guard, hearing a single noise is likely to be nothing. However, what if you heard two noises, and the sound of tires outside? Same thing with the doctor. Most good doctor's I know have a sixth sense, about when something is off and needs further tests beyond just take an aspirin. So maybe the person had a stomach ache, and they had lost some weight, and…

You would think Bayesian inference is good at integrating multiple information sources but practically you have to model the dependencies between different information sources and even doing a good job of that doesn't save you away from logical fallacies such as "Explaining away". In real life people use Naive Bayes a lot because properly modelling a Bayesian network is hard and trying to learn the network gets you in all sorts of problems -- allow arbitrary dependencies between N inputs and you are talking eᴺ coefficients in your model and you'll never solve it.

This is one of the reasons why people got frustrated with Expert Systems as real-life reasoning requires reasoning with uncertainty and we don't have a satisfactory general way to do it.

Re: Heuristics that almost always work

#35

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.

Re: Heuristics that almost always work

#36

This is what Nassim Nicholas Taleb has been writing books about. He calls them black swan events, because if you took a sample of 1000 swans, chances are you'd conclude that all swans are white, but it just isn't so. People tend to round down the probability of very rare events to zero, even when the upside of them is small and the downside is catastrophically bad. Examples: the 2008 housing crisis, Fukushima, and ou…

Maybe you’re right but I don’t see why this addresses the reply to (at least when I loaded it) the first comment on the post which claims the same thing and is disagreed with by the author.

Re: Heuristics that almost always work

#37

This is what Nassim Nicholas Taleb has been writing books about. He calls them black swan events, because if you took a sample of 1000 swans, chances are you'd conclude that all swans are white, but it just isn't so. People tend to round down the probability of very rare events to zero, even when the upside of them is small and the downside is catastrophically bad. Examples: the 2008 housing crisis, Fukushima, and ou…

If you get to the end of the article, the author explains why black swan events are not what he is talking about.

Re: Heuristics that almost always work

#38
My favourite one is seeing IT admins plan for “this almost always won’t fail.”

Substitute “this” for SAN array, core switch, or entire data centre.

I’ve had someone argue with me at length that simultaneous multi disk failures in a RAID5 never happen.

Two weeks later it did and the main SAN disk array went up in smoke.

Re: Heuristics that almost always work

#40

This is what Nassim Nicholas Taleb has been writing books about. He calls them black swan events, because if you took a sample of 1000 swans, chances are you'd conclude that all swans are white, but it just isn't so. People tend to round down the probability of very rare events to zero, even when the upside of them is small and the downside is catastrophically bad. Examples: the 2008 housing crisis, Fukushima, and ou…

These are NOT black swan events. These are probably all White Swan events (possibly grey swan events, but i'd have to review stuff that i don't want to right now). E.g. High certainty, just low predictability. From the book, when you know the statistics of a rare event, and then the even occurs, it's absolutely not a black swan event.

For an event to be a Black Swan event, you literally need to have no possibly for the event in your deductive framework (e.g. the problem of induction which is what the book is actually about). In every single one of these examples, the possibly of the event occurring is accepted by everyone.

This is why Taleb lost his mind when people started calling the Covid Pandemic a "black swan event," which it was absolutely not. We know pandemics happen, we know about what power law they happen at. The fact we were not prepared at all is a problem of not being prepared for something we know will happen with certainty.

https://medium.com/incerto/corporate-socialism-the-governmen...

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