It’s pretty simple, I think; The cost of the problems of Google Doc fall on you, with a small cost on Google itself, and negligible cost on the decision makers in Google responsible.
PS: Couldn’t you just copy the code you wrote in an editor to the Doc? If not, this might be hidden upside: They can watch as people code on Google Doc (as far as I remember), but doing this with an editor is somewhat harder. (VSCode’s liveshare or using a TUI editor in a shared tmux session seem better solutions to me, but Google optimizes for the lowest common denominator.)
using it to identify non-productive employees can be very anti-social and discriminatory
using it to identify non-productive employees can be very anti-social and discriminatory
I believe the opposite is true; Not rewarding the productive ones and punishing the unproductive workers is clearly discriminating against the good people. Sure, giving everyone a UBI that doesn’t break the economy is a very humane thing to do, but forcefully making productive workers subsidize bad ones, without giving them social/economic credit, is plain evil.
But wouldn’t governments have a big incentive to do this? Even for private companies, it can bring them a lot of goodwill for presumably not that much money …
What do you mean by the advice “test your drugs”?
Which blood biomarkers do you measure for assessing the effectiveness of the supplements?
What’s your intuition on the expected life added by researching this stuff personally and in-depth?
My own suspicion in these cases is that these techniques don’t work and are unsustainable hacks that temporarily shift the equilibrium of my thought. Or perhaps they do work but the mind adapts to them (like drugs) and so they’ll lose their usefulness. After all, I don’t forget useful things that I commonly use. even when they become implicit knowledge, I can still feel that the implicit skill is there and see its results.
I recently got an email from JuliaCon, they had attached an ics file that contained all the events and I could just open it and my calendar would automatically import them and send me notifications. That’s a good practice for event organizers.
It might lead to new insights by showing that some properties are shared by all Turing-simulateable universes.
When the Coronavirus started in the winter, I spend quite a bit of time reading related info, mostly from the LW diaspora but some from elsewhere. After some time passed, I noticed that this seems to be low value and procrastinatory, so I have not read much more about the topic. Recently, my sibling (who has had contact with a known Coronavirus infected person) has been showing some cold symptoms, and I am wondering if there are any summary posts of the practical stuff?
I took a look at the practical advice thread, but I had already read the top posts before, and the thread is also quite old and scattered. Recent Coronavirus posts seem to be only from Zvi, who focuses more on epidemiological statistics, and not practical advice, as far as I have read. Hasn’t there been new actionable info in the recent months?
These caterpillars go dormant when frozen in the arctic, and come alive again.
I feel most people, including myself, don’t even use the aggregators already available. For example, there are lots of indices and statistics (ideally there should be much more, but anyways), but I rarely go out of my way to consume them. Some examples I just thought of:
Keeping a watch on new entries to and exits from Fortune 500
Looking at the stocks of the top 20 companies every quarter
There are several popular books that throw surprising statistics around, like Factfulness; This suggests a lot of us are disconnected from basic statistics, that we presumably could easily get by just googling.
I read Black Swan early in my introduction to heuristics and biases, in my teens. I remember that the book was quite illuminating for me, though I disliked Taleb’s narcissism and his disrespect for the truth. I don’t think it was so much “insightful” as helping me internalize a few big insights. The book’s content definitely overlaps a lot with beginner rationality, so you might not find it worthwhile after all. I read a bit of FbR and about half of Antifragile as well, but I found those much less interesting.
An aside: Taleb talks about general topics. It’s hard to say new things in that market (it’s saturated), and the best parts of his new insights have already become part of the common lexicon.
It’s not about excluding that case. It’s about not counting it twice. Search for the inclusion-exclusion principle to see the reasoning behind it.
You’re correct, but I still don’t find the scenario I am describing intuitive by my system 1. If I think about it (especially now that I have analyzed the problem rigorously), yes, I’ll feel that the probability should increase (though of course, with nowhere near the precision of the Bayes rule), but if you just asked me this problem yesterday, and I wasn’t watching for trap questions, I’d give you a wrong answer.
I just found Wikipedia has a whole page on this, named the girl and boy paradox. They cover lots of details there.
I don’t think your analysis is right; For one, if you know that the random variable D is Monday, your problem reduces to mine; In the simulation, you have set D incorrectly ( D=Y1in the case both are boys. This makes no sense. You are ignoring the case where the first boy is not born on Monday, but the second one is.), and it is not a simulation of the probability you have written.
The second example; I’m not sure what your conclusion on it is. It seems like the Monty Hall problem to me, i.e., Alice is still having a chance of 1⁄3, but Charlie now has 2⁄3 chance to die. Because:
P(Bob | Alice) = 1⁄2
P(Bob | Charlie) = 1
This is really a rather subjective thing, so the only thing I can do is produce some examples that are somewhat true for myself. Let’s name my desirability function for a mate f.
I have f( x | x is male) near zero, while I think that if my mind was architectured ideally according to my values, it’d be much higher. True, there are strong statistical differences between the sexes that make being female a good heuristic of things I like in a mate, and also there are very rare males I’d find sexy, but still, if I know a male M who has my desired characteristic, even if he is not sexy, f(M) should be much higher than zero.
I find young people more attractive, usually the younger the better. I might have a strong inclination to not even consider someone 5 years older than me for a mate. But when I think about the things I value, much of them are mental characteristics which are very rare in the population, and some of them correlate positively with age, plus the fact that older people are probably more unwanted by other people, it seems a dumb move for me to ignore them.
It’s not easy for me to produce examples for dating, because I feel my interests there are already mostly aligned. But let me give an example that feels more salient to me. I really enjoy playing civilization. When I’m playing, I always want to reach the next Schelling point of that important milestone before quitting. When I analyze my feelings and intuition though, through their evolutionary context, it’s clear to me that I am mistaking my “core” activities. My brain is categorizing something truly important like studying as a religious chore that does not produce value, while thinking of Civilization as the core activity that brings us status and power in the tribe. Of course, this is quite a fatal mistake, so I try to align myself by reminding myself that no, it is the studying that brings me status and stuff, and I should convert my “One more turns” energies into “One more pages.” This is somewhat of a successful endeavor for me; My subagents find the argument convincing and become somewhat better aligned, though they do need lots of reminding not to revert.
I think evpsy is general enough that a socially savvy person won’t gain much by learning about it (e.g., to a first approximation, people love sex and status and their morality is merely virtue signalling), but a less worldly person might. I personally learned about evpsy early in my childhood (probably around 4th grade), so it helped me a lot (especially since I am a damned idealist). Epistemically speaking, it’s also very satisfying to know WHY the hell people love, say, power instead of an infinity of other things that some mind can like.
Another example; Why do non-famous people waste so much time on Twitter? A normal answer might be that people are very social. Evpsy can enhance this answer by providing the reason people are so social, and also telling you that in this instance their behavior is maladaptive and they are executing the wrong heuristic. The normal answer can not give you this, because if people are just inherently social, that’s their personal characteristic that can’t be ‘wrong.’ I.e., evpsy can help us recognize which of our own values are suspect and misaligned with our core values.
In your own example of dating, this last technique can help you see that your desirability function for women probably is quite disaligned with your actual values, and you’ll gain a lot by meditating on what you really value and fixing your desirability function. The technique can be quite helpful in fixing your nutrition as well.
You’re not stating what probability rules (theorems/axioms) you are using (you’re probably going by intuition), and you have made mistakes. p(one brother born on Tuesday in a in two-boy family) is not 2⁄7; It’s 1/7 + 1/7 - (1/7)(1/7) because you’re counting the two children both being born on Tuesday twice. The same mistake has been made in calculating p(out of all two person families, having one be a boy born on Tuesday); The correct answer is (1/2)(1/7) + (1/2)(1/7) - (1/2)(1/7)(1/2)(1/7).
p(one brother born on Tuesday in a in two-boy family)
1/7 + 1/7 - (1/7)(1/7)
p(out of all two person families, having one be a boy born on Tuesday)
(1/2)(1/7) + (1/2)(1/7) - (1/2)(1/7)(1/2)(1/7)
The rule you’re not following is:
P(A or B) = P(A) + P(B) - P(A and B)
When these mistakes are corrected, the correct answer comes out:
((1/7 + 1/7 - (1/7)*(1/7))*1/4)/((1/2)*(1/7) + (1/2)*(1/7) - (1/2)*(1/7)*(1/2)*(1/7)) = 13/27 =~ 0.4814