I'd be interested in hearing about jkaufman's method, as well
For some of the cases where I can look up data (chance of altzheimers, etc) I did so. For most of the other things I gave rough guesses.
Ok, that makes sense. I think it would be useful if you could annotate your list with references where possible, for things like the chance of Alzheimer's, cancer, etc. This way people who disagree with your probabilities have something to go on. As for the rough guesses, I'm still unclear what they're based on -- can you elaborate ?
In addition, many of the items on your list depend on the time span. To use a trivial example, the probability of "all people die" approaches 1.0 as time goes on, culminating in the heat death of the Universe. Thus, it would be helpful if you provided the rough amount of time you expect to spend frozen, along with an explanation of why you picked this time span in particular.
If an American signs up for cryonics and pays their ~$300/year, what are their odds of being revived? Talking to people at LessWrong meetups I've heard estimates of 1 in 2. My friend George Dahl, whose opinion I respect a lot, guesses "less than 1 in 10^6". Niether has given me reasons, those numbers are opaque. My estimate of these odds pretty much determines whether I should sign up. I could afford $300/year, and I would if I thought the odds were 1:2, but not if they were 1:10^6. [1]
In order to see how likely this is to work, we should look at the process. I would sign up with a cryonics company and for life insurance. I'd go on living, enjoying my life and the people around me, paying my annual fees, until some point when I died. After death they would drain my blood, replace it with something that doesn't rupture cell walls when it freezes, freeze me in liquid nitrogen, and leave me there for a long time. At some point, probably after the development of nanotechnology, people would revive me, probably as a computer program.
There's a lot of steps there, and it's easy to see ways they could go wrong. [3] Let's consider some cases and try to get probabilities [4]:
Update: the probabilities below are out of date, and only useful for understanding the comments. I've made a spreadsheet listing both my updated probabilities and those for as many other people as I can find: https://docs.google.com/spreadsheet/...
Combined Probability Of Failure: 99.82%
Odds of success: 1 in 567.
If you can think of other ways cryonics might fail, moving probability mass from "other" to something more quantifiable, that would be helpful. If you think my numbers are off for something, please let me know what a better number would be and why. This is not final.
Am I going about this right? Do people here who think it's rational to sign up for cryonics take a "the payoff is really high, so the small probability doesn't matter" view? Am I overly pessimistic about its chances of success?
Note: I originally posted this on my blog, and the version there has a silly javascript calculator for playing with the probabilities.
[1] To figure out what odds I would accept, I think the right approach is to treat this as if I were considering signing up for something certain and see how much I would pay, then see what odds bring this below $300/year. Even at 1:2 odds this is less effective than Village Reach at averting death [2], so this needs to come out of my 'money spent on me' budget. I think $10,000/year is about the most I'd be willing to spend. It's a lot, but not dying would be pretty nice. This means I'd need odds of 1:33 to sign up.
[2] Counter argument: you should care about quality adjusted life years and not deaths averted. Someone revived maybe should expect to have millenia of life at very high quality. This seems less likely to me than just the claim "will be revived". A lot less likely.
[3] In order to deal with independence issues, all my probability guesses are conditional on everything above them not happening. Each of these things must go right, so this works. For example, society collapsing and my cryonics organization going out of business are very much not independent. So the probability assigned to the latter is the chance that society won't collapse, but my organization goes out of business anyway. This means I can just multiply up the subelements to get probabilities for sections, and then multiply up sections to get an overall probability.
[4] This has a lot in common with the Warren formula, which was inspired by the Drake equation. Robin Hanson also has a breakdown. I also found a breakdown on LessWrong that seems really optimistic.
EDIT 2011-09-26: jsalvatier suggested an online spreadsheet, which is very sensible. Created
EDIT 2011-09-27: I've updated my probabilities some, and made the updates on the spreadsheet.