My position is that either (1) my brain is computationally stable, in the sense that what I think, how I think it and what I decide to do after thinking is fundamentally about my algorithm (personality/mind), and that tiny changes in the conditions (a random thermal fluctuation), are usually not important. Alternatively (2) my brain is not a reliable/robust machine, and my behaviour is very sensitive to the random thermal fluctuations of atoms in my brain.
In the first case, we wouldn’t expect small errors (for some value of small) in the uploaded brain to result in significant divergence from the real person (stability). In the second case I am left wondering why I would particularly care. Are the random thermal fluctuations pushing me around somehow better than the equally random measurement errors pushing my soft-copy around?
So, I don’t think uploaded brains can be ruled out a priori on precision grounds. There exists a non-infinite amount of precision that suffices, the necessary precision is upper bounded by the thermal randomness in a body temperature brain.
Surely both (1) and (2) are true, each to a certain extent.
Are the random thermal fluctuations pushing me around somehow better than the equally random measurement errors pushing my soft-copy around?
It depends. We know from experience how meat brains change over time. We have no idea how software brains change over time; it surely depends on the details of the technology used. The changes might be comparable, but they might be bizarre. The longer you run the program, the more extreme the changes are likely to be.
I can’t rule it out either. Nor can I rule it in. It’s conceivable, but there are enough issues that I’m highly skeptical.
I might be misunderstanding your point. My opinion is that software brains are extremely difficult (possibly impossibly difficult) because brains are complicated. Your position, as I understand it, is that they are extremely difficult (possibly impossibly difficult) because brains are chaotic.
If its the former (complexity) then there exists a sufficiently advanced model of the human brain that can work (where “sufficiently advanced” here means “probably always science fiction”). If brains are assumed to be chaotic then a lot of what people think and do is random, and the simulated brains will necessarily end up with a different random seed due to measurement errors. This would be important in some brain simulating contexts, for example it would make predicting someone’s future behaviour based on a simulation of their brain impossible. (Omega from Newcomb’s paradox would struggle to predict whether people would two-box or not.) However, from the point of view of chasing immortality for yourself or a loved one the chaos doesn’t seem to be an immediate problem. If my decision to one-box was fundamentally random (down to thermal fluctuations) and trivial changes on the day could have changed my mind, then it couldn’t have been part of my personality. My point was, from the immortality point of view, we only really care about preserving the signal, and can accept different noise.
I think part of the difference is that I’m considering the uploading process; it seems to me that you’re skipping past it, which amounts to assuming it works perfectly.
Consider the upload of Bob the volunteer. The idea that software = Bob is based on the idea that Bob’s connectome of roughly 100 trillion synapses is accurately captured by the upload process. It seems fairly obvious to me that this process will not capture every single synapse with no errors (at least in early versions). It will miss a percentage and probably also invent some that meat-Bob doesn’t have.
This raises the question of how good a copy is good enough. If brains are chaotic, and I would expect them to be, even small error rates would have large consequences for the output of the simulation. In short, I would expect that for semi-realistic upload accuracy (whatever that means in this context), simulated Bob wouldn’t think or behave much like actual Bob.
My position is that either (1) my brain is computationally stable, in the sense that what I think, how I think it and what I decide to do after thinking is fundamentally about my algorithm (personality/mind), and that tiny changes in the conditions (a random thermal fluctuation), are usually not important. Alternatively (2) my brain is not a reliable/robust machine, and my behaviour is very sensitive to the random thermal fluctuations of atoms in my brain.
In the first case, we wouldn’t expect small errors (for some value of small) in the uploaded brain to result in significant divergence from the real person (stability). In the second case I am left wondering why I would particularly care. Are the random thermal fluctuations pushing me around somehow better than the equally random measurement errors pushing my soft-copy around?
So, I don’t think uploaded brains can be ruled out a priori on precision grounds. There exists a non-infinite amount of precision that suffices, the necessary precision is upper bounded by the thermal randomness in a body temperature brain.
Surely both (1) and (2) are true, each to a certain extent.
Are the random thermal fluctuations pushing me around somehow better than the equally random measurement errors pushing my soft-copy around?
It depends. We know from experience how meat brains change over time. We have no idea how software brains change over time; it surely depends on the details of the technology used. The changes might be comparable, but they might be bizarre. The longer you run the program, the more extreme the changes are likely to be.
I can’t rule it out either. Nor can I rule it in. It’s conceivable, but there are enough issues that I’m highly skeptical.
I might be misunderstanding your point. My opinion is that software brains are extremely difficult (possibly impossibly difficult) because brains are complicated. Your position, as I understand it, is that they are extremely difficult (possibly impossibly difficult) because brains are chaotic.
If its the former (complexity) then there exists a sufficiently advanced model of the human brain that can work (where “sufficiently advanced” here means “probably always science fiction”). If brains are assumed to be chaotic then a lot of what people think and do is random, and the simulated brains will necessarily end up with a different random seed due to measurement errors. This would be important in some brain simulating contexts, for example it would make predicting someone’s future behaviour based on a simulation of their brain impossible. (Omega from Newcomb’s paradox would struggle to predict whether people would two-box or not.) However, from the point of view of chasing immortality for yourself or a loved one the chaos doesn’t seem to be an immediate problem. If my decision to one-box was fundamentally random (down to thermal fluctuations) and trivial changes on the day could have changed my mind, then it couldn’t have been part of my personality. My point was, from the immortality point of view, we only really care about preserving the signal, and can accept different noise.
I certainly agree that brains are complicated.
I think part of the difference is that I’m considering the uploading process; it seems to me that you’re skipping past it, which amounts to assuming it works perfectly.
Consider the upload of Bob the volunteer. The idea that software = Bob is based on the idea that Bob’s connectome of roughly 100 trillion synapses is accurately captured by the upload process. It seems fairly obvious to me that this process will not capture every single synapse with no errors (at least in early versions). It will miss a percentage and probably also invent some that meat-Bob doesn’t have.
This raises the question of how good a copy is good enough. If brains are chaotic, and I would expect them to be, even small error rates would have large consequences for the output of the simulation. In short, I would expect that for semi-realistic upload accuracy (whatever that means in this context), simulated Bob wouldn’t think or behave much like actual Bob.