Strong upvote. I’m glad that I found your posts as I was myself annoyed by the mainstream antropic reasoning for similar reasons.
However, I believe not all self-locating probabilities are made equal. I think it makes sense to say 1⁄2 in fission problem just for regular probability theoretic reasoning.
Suppose a coin was tossed. What is the probability for heads?
50%.
But what if the coin was unfair, though you don’t know how exactly?
Still 50%. The information regarding the unfairness of a coin doesn’t give me any new information, unless I know the direction. So I still use the equiprobable prior.
Thank you for the kind words. I understand the stance about self-locating probability. That’s the part I get most disagreements.
To me the difference is for the unfair coin, you can treat the reference class as all tosses from unfair coins that you don’t know how. Then the symmetry between Head\Tail holds, and you can say in this kind of tosses the relative frequency would be 50%. But for the self-locating probabilities in the fission problem, there really is nothing pointing to any number. That is, unless we take the average of all agents and discard the “self”. It requires taking the immaterial viewpoint and transcoding “I” by some assumption.
And remember, if you validate self-locating probability in anthropics, then the paradoxical conclusions are only a Bayesian update away.
I don’t think that I need to think about referential classes at all. I can just notice that I’m in a state of uncertanity between two outcomes and as there is no reason to think that any specific one is more likely than the other I use the equiprobable prior.
I believe the ridiculousness of antropics comes when the model assumes that I’m randomly selected from a distribution, while in reality it’s not actually the case. But sometimes it may still be true. So there are situations when self-locating probability is valid and situations when it’s not.
I think my intuition pump is this:
If I’m separated in ten people 9 of whom are going to wake up in the red room while 1 is going to wake up in the blue room it’s correct to have 9:1 odds in favour of red for my expected experience. Because I would actually be one of these 10 people.
But if a fair coin is tossed and I’m separated in 9 people who will wake up in red rooms if its heads or I’ll wake up in a blue room if it’s tails then there odds are 1:1 because the causal process is completely different. I am either one of nine people or one of one based on the results of the coin toss, not the equiprobable distribution.
Also none of these cases include “updating from existence/waking up”. I was expected to be existing anyway and got no new information.
Strong upvote. I’m glad that I found your posts as I was myself annoyed by the mainstream antropic reasoning for similar reasons.
However, I believe not all self-locating probabilities are made equal. I think it makes sense to say 1⁄2 in fission problem just for regular probability theoretic reasoning.
Suppose a coin was tossed. What is the probability for heads?
50%.
But what if the coin was unfair, though you don’t know how exactly?
Still 50%. The information regarding the unfairness of a coin doesn’t give me any new information, unless I know the direction. So I still use the equiprobable prior.
Thank you for the kind words. I understand the stance about self-locating probability. That’s the part I get most disagreements.
To me the difference is for the unfair coin, you can treat the reference class as all tosses from unfair coins that you don’t know how. Then the symmetry between Head\Tail holds, and you can say in this kind of tosses the relative frequency would be 50%. But for the self-locating probabilities in the fission problem, there really is nothing pointing to any number. That is, unless we take the average of all agents and discard the “self”. It requires taking the immaterial viewpoint and transcoding “I” by some assumption.
And remember, if you validate self-locating probability in anthropics, then the paradoxical conclusions are only a Bayesian update away.
I don’t think that I need to think about referential classes at all. I can just notice that I’m in a state of uncertanity between two outcomes and as there is no reason to think that any specific one is more likely than the other I use the equiprobable prior.
I believe the ridiculousness of antropics comes when the model assumes that I’m randomly selected from a distribution, while in reality it’s not actually the case. But sometimes it may still be true. So there are situations when self-locating probability is valid and situations when it’s not.
I think my intuition pump is this:
If I’m separated in ten people 9 of whom are going to wake up in the red room while 1 is going to wake up in the blue room it’s correct to have 9:1 odds in favour of red for my expected experience. Because I would actually be one of these 10 people.
But if a fair coin is tossed and I’m separated in 9 people who will wake up in red rooms if its heads or I’ll wake up in a blue room if it’s tails then there odds are 1:1 because the causal process is completely different. I am either one of nine people or one of one based on the results of the coin toss, not the equiprobable distribution.
Also none of these cases include “updating from existence/waking up”. I was expected to be existing anyway and got no new information.