To elaborate on this, the odds of cryonics succeeding are estimated to be between .23% in the pessimistic scenario and 15% in the optimistic. Contrast this with the 1 in quadrillion (or a similarly high number) chance of the mugger being honest in Pascal’s mugging.
That analysis didn’t include a factor for “the nanotechnology of the future actually has a cure for what ails you in the present”
That analysis is wrong on one point that I could research in 10 minutes: From https://www.cdc.gov/nchs/fastats/deaths.htm 25% of deaths from major causes (not counting suicide) are of a type that would significantly risk the cryo process (accident, stroke, Alzheimer’s) so the optimistic “I die in a way that doesn’t hurt my chances for cryo” would be 75%, not 95%, and the lower bound would be ?. Having a clear error in one place casts doubt on the other numbers.
Like almost all fermi/drake estimates, that one was bounded by the human tendency to assign whole number percentages to estimates. It is entirely plausible that the person doing the estimations thought “this is unlikely” and wrote down “20%” instead of the actual value of .000000001%.
The cost is also significantly higher than the Mugging scenario—talking tens of thousands of dollars and hours of time and significant personal life constraints (eg living near a facility)
I examined point 2 in this section of my cost-benefit analysis. I collect estimates of revival probability here (I subjectively judge thesetwo metaculus estimates to be most trustworthy on the forecast, due to the track-record of performance).
As for point 3: Functional fixedness in assuming dependencies might make estimates too pessimistic. Think about the Manhattan or Apollo project: doing a linked conditional probabilities estimate would have put the probabilities of these two succeeding at far far lower than 1%, yet they still happened (this is a very high-compression summary of the linked text). Here is EY talking about that kind of argument, and why it might sometimes fail.
Cryogenics may be low probability, but it’s certainly not very low in the way Pascal’s mugging is.
To elaborate on this, the odds of cryonics succeeding are estimated to be between .23% in the pessimistic scenario and 15% in the optimistic. Contrast this with the 1 in quadrillion (or a similarly high number) chance of the mugger being honest in Pascal’s mugging.
That analysis didn’t include a factor for “the nanotechnology of the future actually has a cure for what ails you in the present”
That analysis is wrong on one point that I could research in 10 minutes: From https://www.cdc.gov/nchs/fastats/deaths.htm 25% of deaths from major causes (not counting suicide) are of a type that would significantly risk the cryo process (accident, stroke, Alzheimer’s) so the optimistic “I die in a way that doesn’t hurt my chances for cryo” would be 75%, not 95%, and the lower bound would be ?. Having a clear error in one place casts doubt on the other numbers.
Like almost all fermi/drake estimates, that one was bounded by the human tendency to assign whole number percentages to estimates. It is entirely plausible that the person doing the estimations thought “this is unlikely” and wrote down “20%” instead of the actual value of .000000001%.
The cost is also significantly higher than the Mugging scenario—talking tens of thousands of dollars and hours of time and significant personal life constraints (eg living near a facility)
I examined point 2 in this section of my cost-benefit analysis. I collect estimates of revival probability here (I subjectively judge these two metaculus estimates to be most trustworthy on the forecast, due to the track-record of performance).
As for point 3: Functional fixedness in assuming dependencies might make estimates too pessimistic. Think about the Manhattan or Apollo project: doing a linked conditional probabilities estimate would have put the probabilities of these two succeeding at far far lower than 1%, yet they still happened (this is a very high-compression summary of the linked text). Here is EY talking about that kind of argument, and why it might sometimes fail.