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Algorithms to Live By – The Computer Science of Human Decisions

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Re: Algorithms to Live By – The Computer Science of Human Decisions

#11
post #2

I’m curious to know if anyone has “implemented” any of these approaches in their own life…

I’ve read years ago, and became my comfortable keeping my inbox or my files become messier, relying more on the search. I wish Google Desktop would still exist, however.

Re: Algorithms to Live By – The Computer Science of Human Decisions

#12
post #9
post #2

I’m curious to know if anyone has “implemented” any of these approaches in their own life…

I often make estimations based on the heuristic that if we don’t know much about how long something will remain, then we’re most likely half way currently. For example, McDonalds was founded 82 years ago and if we have to guess how long it will still exist then probably around 82 years (until 2104). This also works great, for example, to answer whether you should make plans for Christmas 2023 with the girl you have b…

What is your heuristics based on?

Quite often though, you know a little about some thing. How do you adjust your heuristics then? What about the job that I started two months ago, should I expect to work there by December 2023? If the US was founded in 1776, how long will it still exist?

Re: Algorithms to Live By – The Computer Science of Human Decisions

#13
post #2

I’m curious to know if anyone has “implemented” any of these approaches in their own life…

When dealing with particularly toxic people I find the exponential backoff to be an excellent strategy.

In my case, I hate cutting people off because I know people can change. What I do to manage relationships is run a forgiving version of exponential backoff. Start off friendly and forgiving. If someone becomes transgressive, increase the latency between interactions. If the transgressions continue, double the latency. If bad interactions persist, the time latency can go on to months or even years which means you'll probably never interact with that person again. Conversely, if an interaction goes well, reduce the delay for when you're willing to meet again. E.g. say an irritating individual causes the latency to go to once a month. If you have an interaction that goes well then the latency drops to 2 weeks. If interactions continue to go well they drop further to say no latency, i.e. you're willing to meet this person whenever. Obviously it's not perfect but it suites my needs quite well.

I also found his chapter on "overfitting" excellent. I like to think of it as "smart person disease." Big idea is that having more data can actually hamper decision making instead of enhance it because you winde up solving the wrong problem.

Re: Algorithms to Live By – The Computer Science of Human Decisions

#14
> Other animal behavior also evokes TCP flow control, with its characteristic sawtooth. Squirrels and pigeons going after human food scraps will creep forward a step at a time, occasionally leap back, then steadily creep forward again.

> Caching gives us the language to understand what’s happening. We say “brain fart” when we should really say “cache miss”.

Sorry, but how can anyone find this book insightful? Doesn't it sound dumb to anyone else? Seems as if the author made list of bunch of algorithms and filled up hundreds of pages with lazy analogies. Having read a bunch of similar books (classic self-help crap), I must say that these books are a giant waste of time. It reminds me of mental models. Reading about mental models isn't going to magically make you smarter, you'll likely develop on your own from experience. But hey, if it helps you, awesome. Just giving my two cents as a person who has largely become disillusioned with books like these.

Re: Algorithms to Live By – The Computer Science of Human Decisions

#15

> Other animal behavior also evokes TCP flow control, with its characteristic sawtooth. Squirrels and pigeons going after human food scraps will creep forward a step at a time, occasionally leap back, then steadily creep forward again. > Caching gives us the language to understand what’s happening. We say “brain fart” when we should really say “cache miss”. Sorry, but how can anyone find this book insightful? Doesn't…

[deleted]

Re: Algorithms to Live By – The Computer Science of Human Decisions

#16
post #6
post #3

Earlier quoted context omitted.

I read the book a while back and realized I do the caching one automatically. I have a pretty messy work bench where I build rockets and play around with microcontrollers. I purposely didn’t try to organize it because, over time, it organizes itself. All the stuff that has my attention gradually drifts to arms reach where the stuff I don’t currently need gradually drifts to the back of the workbench. Edit: the stoppi…

I do the same. My other rule is that wherever I look for it when I've lost it is where it belongs. It causes a fair amount of friction with housemates, though. Have you figured out any way to alleviate that when it comes to areas used by multiple people?

In some sense you have a race condition. By taking the item and misplacing it, you've caused a deadlock. Solutions are kinda the same: have a copy of the item for every person that might use it, or be strict about freeing all locked resources.

Re: Algorithms to Live By – The Computer Science of Human Decisions

#18

> Other animal behavior also evokes TCP flow control, with its characteristic sawtooth. Squirrels and pigeons going after human food scraps will creep forward a step at a time, occasionally leap back, then steadily creep forward again. > Caching gives us the language to understand what’s happening. We say “brain fart” when we should really say “cache miss”. Sorry, but how can anyone find this book insightful? Doesn't…

If you read it, you'll find it full of useful strategies to leverage in making better decisions in your life. It's also amusing for CS-educated folks because it's a fun application of the material to everyday life.

Re: Algorithms to Live By – The Computer Science of Human Decisions

#19
post #9

Earlier quoted context omitted.

I often make estimations based on the heuristic that if we don’t know much about how long something will remain, then we’re most likely half way currently. For example, McDonalds was founded 82 years ago and if we have to guess how long it will still exist then probably around 82 years (until 2104). This also works great, for example, to answer whether you should make plans for Christmas 2023 with the girl you have b…

What is your heuristics based on? Quite often though, you know a little about some thing. How do you adjust your heuristics then? What about the job that I started two months ago, should I expect to work there by December 2023? If the US was founded in 1776, how long will it still exist?

Not OP and haven't read the book, but maybe this is more about survival, if McDonald's survived 82 years, then we can assume it can survive another 82, if you've been at the job for 2 months and there are no signs of trouble, then you can assume you'll survive another 2, reevaluate then to conclude that you can survive another 4...

Re: Algorithms to Live By – The Computer Science of Human Decisions

#20
post #6
post #3

Earlier quoted context omitted.

I read the book a while back and realized I do the caching one automatically. I have a pretty messy work bench where I build rockets and play around with microcontrollers. I purposely didn’t try to organize it because, over time, it organizes itself. All the stuff that has my attention gradually drifts to arms reach where the stuff I don’t currently need gradually drifts to the back of the workbench. Edit: the stoppi…

I do the same. My other rule is that wherever I look for it when I've lost it is where it belongs. It causes a fair amount of friction with housemates, though. Have you figured out any way to alleviate that when it comes to areas used by multiple people?

That sounds like something I do; if I can't find something I don't think "where should it be" but rather "if I were going to put it down right now, where would I put it"

Honestly, I'm still pretty shit at finding things, but this strategy has helped considerably.

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