X is a random variable, E is expected value (a.k.a. average), P is probability. For example, if X is uniformly distributed between 0 and 1, then EX=0.5 and P(X>0.75)=0.25.
Sarunas is saying that some action might not affect the average value, but strongly affect the chances of getting a very high or very low value (“swing for the fences” so to speak). For example, if we define Y as X rounded to the nearest integer (i.e. Y=0 if X0.5), then EY=0.5 and P(Y>0.75)=0.5. The average of Y is the same as the average of X, but the probability of getting an extreme value is higher.
This is probably obvious for others, but it wasn’t obvious for me that by paying 0.1 to go from the first game to the second one you both decrease your average earnings and increase the probability of high earnings.
Yeah, that’s one part of it. Another part is that some irrational beliefs can be beneficial even on average, though of course you need to choose such beliefs carefully. Believing that the world makes sense, in the context of doing research, might be one such example. I don’t know if there are others. Eliezer’s view of Bayesianism (“yay, I’ve found the eternal laws of reasoning!”) might be related here.
Am I correct to paraphrase you this way: maximizing EX and maximizing P(X > a) are two different problems.
What are the meanings of these symbols “EX”, “P(X>a)”?
X is a random variable, E is expected value (a.k.a. average), P is probability. For example, if X is uniformly distributed between 0 and 1, then EX=0.5 and P(X>0.75)=0.25.
Sarunas is saying that some action might not affect the average value, but strongly affect the chances of getting a very high or very low value (“swing for the fences” so to speak). For example, if we define Y as X rounded to the nearest integer (i.e. Y=0 if X0.5), then EY=0.5 and P(Y>0.75)=0.5. The average of Y is the same as the average of X, but the probability of getting an extreme value is higher.
This is probably obvious for others, but it wasn’t obvious for me that by paying 0.1 to go from the first game to the second one you both decrease your average earnings and increase the probability of high earnings.
Yeah, that’s one part of it. Another part is that some irrational beliefs can be beneficial even on average, though of course you need to choose such beliefs carefully. Believing that the world makes sense, in the context of doing research, might be one such example. I don’t know if there are others. Eliezer’s view of Bayesianism (“yay, I’ve found the eternal laws of reasoning!”) might be related here.
Good point. It’s worth noting that you can use Markov’s inequality to relate the two.