Here's my program, with my probability estimates removed to avoid bias. If anyone wants to use it, feel free. It calculates the probablilty a person will be revived after X years. If you want a final probability, plug in some priors, including a distribution over how long you think it will take you to be revived.
#lang scheme (require plot)
(define (cycle-to-chance cycle-length) (/ 1 cycle-length))
(define business-failure-cycle-length XXX) ;How often will a cryonics agency go out of business?
(define dark-age-cycle-length XXX) ;How often will a technical/ethical/economic dark age happen?
(define depression-cycle-length XXX) ;How often will a great depression hit North America?
(define Pnd XXX) ;Probability of a natural distaster
(define Pr XXX) ;Chance a corpse will be revived when cryogenic tech is available
(define Pbd XXX) ;Chance the information needed to revive a corpse is present
(define Pdh XXX) ;Chance humanity is destroyed (considered as a single time-indepenent factor)
(define Pcif (cycle-to-chance business-failure-cycle-length)) ;Chance the cryonics institute fails in a reasonable economy, per year
(define Pcif-cc XXX) ;Chance the corpse unfreezes if the cryonics institute fails in a reasonable economy
(define Pgef (cycle-to-chance depression-cycle-length)) ;Chance of a great depression in north america, per year
(define Pgef-cc XXX) ;Chance the corpse unfreezes in a great depression
(define Pda (cycle-to-chance dark-age-cycle-length)) ;Chance of a dark age, per year
(define Pda-cc XXX) ;Change the corpse unfreezes in a dark age
(define Pvc XXX) ;Probability a corpse is viable for freezing on death
(define Pst XXX) ;Probability a corpse is safely transported and frozen
(define entry-shock-pass-chance (* Pst Pvc (- 1 Pdh)))
(define exit-shock-pass-chance (* Pr Pbd))
(define yearly-pass-chance (min (- 1 ( Pcif Pcif-cc )) (- 1 ( Pgef Pgef-cc)) (- 1 (* Pda Pda-cc))))
(define (success-distribution time) (* entry-shock-pass-chance exit-shock-pass-chance (expt yearly-pass-chance time)))
(define (approx-integrate f start end step-size)
(apply +
(map (lambda (inc-start) (* (/ (+ (f inc-start) (f (+ inc-start step-size))) 2) step-size)) (for/list ((i (in-range start (- end step-size) step-size))) i))))
Here is my final probability, rot13ed: Gur cebonovyvgl V'yy or erivirq va svsgl, bar uhaqerq lrnef ner svir-cbvag-guerr-creprag, gjb-cbvag-guerr-creprag erfcrpgviryl.
Edit: I'm having a hard time getting this program source to display properly, but it should run fine with some line breaks.
Okay, so I updated my chance that the correct information is present in the brain - from 75% to 99% after seeing this talk by Brian Wowk, with the team that preserved a rabbit liver. My estimates went down, not up. There was an error in my program, which I've corrected above. Even with this correction, I strongly recommend against using it without checking it yourself first.
My probability estimates are now nearly ten times higher, and I will sign up for cryonics. I guess I should either not stake my life on my programming skills, or program better.
Cryonics scales very well. People who argue from the perspective that cryonics is costly are probably not aware of this fact. Even assuming you needed to come up with the lump sum all at once rather than steadily pay into life insurance, the fact is that most people would be able to afford it if most people wanted it. There are some basic physical reasons why this is the case.
So long as you keep the shape constant, for any given container the surface area is based on a square law while the volume is calculated as a cube law. For example with a simple cube shaped object, one side squared times 6 is the surface area; one side cubed is the volume. Spheres, domes, and cylinders are just more efficient variants on this theme. For any constant shape, if volume is multiplied by 1000, surface area only goes up by 100 times.
Surface area is where heat gains entry. Thus if you have a huge container holding cryogenic goods (humans in this case) it costs less per unit volume (human) than is the case with a smaller container that is equally well insulated. A way to understand why this works is to realize that you only have to insulate and cool the outside edge -- the inside does not collect any new heat. In short, by multiplying by a thousand patients, you can have a tenth of the thermal transfer to overcome per patient with no change in r-value.
But you aren't limited to using equal thickness of insulation. You can use thicker insulation, but get a much smaller proportional effect on total surface area when you use bigger container volumes. Imagine the difference between a marble sized freezer and a house-sized freezer. What happens when you add an extra foot of insulation to the surface of each? Surface area is impacted much as diameter is -- i.e. more significantly in the case of the smaller freezer than the larger one. The outer edge of the insulation is where it begins collecting heat. With a truly gigantic freezer, you could add an entire meter (or more) of insulation without it having a significant proportional impact on surface area, compared to how much surface area it already has. (This is one reason cheaper materials can be used to construct large tanks -- they can be applied in thicker layers.)
Another factor to take into account is that liquid nitrogen, the super-cheap coolant used by cryonics facilities around the world, is vastly cheaper (more than a factor of 10) when purchased in huge quantities of several tons. The scaling factors for storage tanks and high-capacity tanker trucks are a big part of the reason for this. CI has used bulk purchasing as a mechanism for getting their prices down to $100 per patient per year for their newer tanks. They are actually storing 3,000 gallons of the stuff and using it slowly over time, which implies there is a boiloff rate associated with the 3,000 gallon tank in addition to the tanks.
The conclusion I get from this is that there is a very strong self-interested case (as well as the altruistic case) to be made for the promotion of megascale cryonics towards the mainstream, as opposed to small independently run units for a few of us die-hard futurists. People who say they won't sign up for cost reasons may actually (if they are sincere) be reachable at a later date. To deal with such people's objections and make sure they remain reachable, it might be smart to get them to agree with some particular hypothetical price point at which they would feel it is justified. In large enough quantities, it is conceivable that indefinite storage costs would be as low as $50 per person, or 50 cents per year.
That is much cheaper than saving a life any other way. Of course there's still the risk that it might not work. However, given a sufficient chance of it working it could still be morally superior to other life saving strategies that cost more money. It also has inherent ecological advantages over other forms of life-saving in that it temporarily reduces the active population, giving the environment a chance to recover and green tech more time to take hold so that they can be supported sustainably and comfortably. And we might consider the advent of life-health extension in the future to be a reason to think it a qualitatively better form of life-saving.
Note: This article only looks directly at cooling energy costs; construction and ongoing maintenance do not necessarily scale as dramatically. The same goes for stabilization (which I view as a separate though indispensable enterprise). Both of these do have obvious scaling factors however. Other issues to consider are defense and reliability. Given the large storage mass involved, preventing temperature fluctuations without being at the exact boiling temperature of LN2 is feasible; it could be both highly failsafe and use the ideal cryonics temperature of -135C rather than the -196C that LN2 boiloff as a temperature regulation mechanism requires. Feel free to raise further issues in the comments.