I am skeptical that it is possible to estimate the chances of cryonics working in a rigorous quantitative way. There’s no way to know what technical hurdles are actually involved to make it work. How can you estimate your chances of success when you have no information about the difficulty of the problem?
Um...there is quite a bit of information. For instance, one major hurdle was ice crystal formation, which has been overcome—but at the price of toxicity (currently unspecified, but—in my moderately informed guesstimate—likely to be related to protein misfolding and membrane distortion).
We also have quite a bit of knowledge of synaptic structure and physiology. I can make a pretty good guess at some of the problems. There are likely many others (many more problems that I cannot predict), but the ones I can are pretty daunting.
I was unclear, I didn’t mean that there’s no information, just that there’s potentially no information on specific areas that are critical for a meaningful prediction:
New technologies and ideas that bypass, rather than solve previously defined obstacles- thus making them far easier than anticipated
Newly discovered obstacles which are far more difficult to overcome than any of the previously defined obstacles, making the problem much more difficult than anticipated
Given that both of these types of events are common when developing new technology, attempting to predict how long it will take and how well it will work is basically a waste of time. Even if you synthesize all of the data you have in a rigorous way and come up with a number, I expect that the number would have error bars so large that it’s merely a quantitative expression of the impossibility of accurately predicting such events with the data you have.
I am curious about what are the biggest obstacles you see that cause you to give 20 order of magnitude lower an estimate than I do. If that is accurate, thinking about and working on cryonics is a pointless waste of time.
I agree with you on both points. And also about the error bars—I don’t think I can “prove” cryonics to be pointless.
But one has to make decisions based on something. I would rather build a school in Africa than have my body frozen (even though, to reiterate, I’m all for living longer, and I do not believe that death has inherent value).
Biggest obstacles are membrane distortions, solvent replacement and signalling event interruptions. Mind is not so much written into the structure of the brain as into the structure+dynamic activity. In a sense, in order to reconstruct the mind within a frozen brain, you would have to already know what that mind looks like when it’s active. Then you need molecular tools which appear impossible from the fundamental principles of physics (uncertainty principle, molecular noise, molecular drift...).
My view of cryonics is that it is akin to mercuric antibiotics of the late 19th century. Didn’t really work, but they were the only game in town. So perhaps with further research, new generation of mercuric substances will be developed which will solve all the problems, right? In reality, a much better solution was discovered. I believe this is also the case with life extension—cryonics will fade away, and we’ll move in with a combination of stem cell treatments, technologies to eliminate certain accumulated toxins (primarily insoluble protein aggregates and lipid peroxidation byproducts), and methods to eliminate or constrain cellular senescence (I’m actually willing to bet ~$5 that these are going to be the first treatments to hit the market).
I agree with you that the enormous cost is probably not worth it, when you start thinking what else could be accomplished with the money in the context of it’s low probability of success.
However, those technologies that increase human lifespan are really something entirely different than cryonics, not a replacement for it.
Even if we increase lifespan significantly, as long as we still have a lifespan cryonics would allow us to remain frozen until even more life extension technologies come about. It’s also a potentially viable method for keeping people alive for long distance space travel at sub-relativistic speeds.
I’d look forward to seeing a more detailed post (or even a journal article) from you going into the biochemistry specifics of the problems with cryonics you mention in this post, and your other posts in this thread. I am particularly curious why rehydration would denature proteins which are naturally stable in water? And what sort of membrane distortions would occur that aren’t reversible?
The questions you ask are very complex. The short answers (and then I’m really leaving the question at that point until a longer article is ready):
Rehydration involves pulling off the stabilizer molecules (glycerol, trehalose) and replacing them dynamically with water. This can induce folding changes, some of which are irreversible. This is not theoretical: many biochemists have to deal with this in their daily work.
Membrane distortions also distort relative position of proteins within that membrane (and the structure of synaptic scaffold, a complex protein structure that underlies the synaptic membrane). Regenerating the membrane and returning it to the original shape and position doesn’t necessarily return membrane-bound molecules to their original position.
Mine was also just an off-the-cuff “guesstimate.”
I am skeptical that it is possible to estimate the chances of cryonics working in a rigorous quantitative way. There’s no way to know what technical hurdles are actually involved to make it work. How can you estimate your chances of success when you have no information about the difficulty of the problem?
Um...there is quite a bit of information. For instance, one major hurdle was ice crystal formation, which has been overcome—but at the price of toxicity (currently unspecified, but—in my moderately informed guesstimate—likely to be related to protein misfolding and membrane distortion).
We also have quite a bit of knowledge of synaptic structure and physiology. I can make a pretty good guess at some of the problems. There are likely many others (many more problems that I cannot predict), but the ones I can are pretty daunting.
I was unclear, I didn’t mean that there’s no information, just that there’s potentially no information on specific areas that are critical for a meaningful prediction:
New technologies and ideas that bypass, rather than solve previously defined obstacles- thus making them far easier than anticipated
Newly discovered obstacles which are far more difficult to overcome than any of the previously defined obstacles, making the problem much more difficult than anticipated
Given that both of these types of events are common when developing new technology, attempting to predict how long it will take and how well it will work is basically a waste of time. Even if you synthesize all of the data you have in a rigorous way and come up with a number, I expect that the number would have error bars so large that it’s merely a quantitative expression of the impossibility of accurately predicting such events with the data you have.
I am curious about what are the biggest obstacles you see that cause you to give 20 order of magnitude lower an estimate than I do. If that is accurate, thinking about and working on cryonics is a pointless waste of time.
I agree with you on both points. And also about the error bars—I don’t think I can “prove” cryonics to be pointless.
But one has to make decisions based on something. I would rather build a school in Africa than have my body frozen (even though, to reiterate, I’m all for living longer, and I do not believe that death has inherent value).
Biggest obstacles are membrane distortions, solvent replacement and signalling event interruptions. Mind is not so much written into the structure of the brain as into the structure+dynamic activity. In a sense, in order to reconstruct the mind within a frozen brain, you would have to already know what that mind looks like when it’s active. Then you need molecular tools which appear impossible from the fundamental principles of physics (uncertainty principle, molecular noise, molecular drift...).
My view of cryonics is that it is akin to mercuric antibiotics of the late 19th century. Didn’t really work, but they were the only game in town. So perhaps with further research, new generation of mercuric substances will be developed which will solve all the problems, right? In reality, a much better solution was discovered. I believe this is also the case with life extension—cryonics will fade away, and we’ll move in with a combination of stem cell treatments, technologies to eliminate certain accumulated toxins (primarily insoluble protein aggregates and lipid peroxidation byproducts), and methods to eliminate or constrain cellular senescence (I’m actually willing to bet ~$5 that these are going to be the first treatments to hit the market).
I agree with you that the enormous cost is probably not worth it, when you start thinking what else could be accomplished with the money in the context of it’s low probability of success.
However, those technologies that increase human lifespan are really something entirely different than cryonics, not a replacement for it.
Even if we increase lifespan significantly, as long as we still have a lifespan cryonics would allow us to remain frozen until even more life extension technologies come about. It’s also a potentially viable method for keeping people alive for long distance space travel at sub-relativistic speeds.
I’d look forward to seeing a more detailed post (or even a journal article) from you going into the biochemistry specifics of the problems with cryonics you mention in this post, and your other posts in this thread. I am particularly curious why rehydration would denature proteins which are naturally stable in water? And what sort of membrane distortions would occur that aren’t reversible?
All good reason to keep working on it.
The questions you ask are very complex. The short answers (and then I’m really leaving the question at that point until a longer article is ready):
Rehydration involves pulling off the stabilizer molecules (glycerol, trehalose) and replacing them dynamically with water. This can induce folding changes, some of which are irreversible. This is not theoretical: many biochemists have to deal with this in their daily work.
Membrane distortions also distort relative position of proteins within that membrane (and the structure of synaptic scaffold, a complex protein structure that underlies the synaptic membrane). Regenerating the membrane and returning it to the original shape and position doesn’t necessarily return membrane-bound molecules to their original position.