TBH, I don’t particularly think it’s one of the most important projects right now, due to several issues:
There’s no reason to assume that we could motivate them any better than what we already do, unless we are in the business of changing personality, which carries it’s own problems, or we are willing to use it on a massive scale, which simply cannot be done currently.
We are running out of time. The likely upper bound for AI that will automate basically everything is 15-20 years from Rafael Harth and Cole Wyeth, and unfortunately there’s a real possibility that the powerful AI comes in 5-10 years, if we make plausible assumptions about scaling continuing to work, and given that there’s no real way to transfer any breakthroughs to the somatic side of gene editing, it will be irrelevant by the time AI comes.
Thus, human intelligence augmentation is quite poor from a reducing X-risk perspective.
On EV grounds, “2/3 chance it’s irrelevant because of AGI in the next 20 years” is not a huge contributor to the EV of this. Because, ok, maybe it reduces the EV by 3x compared to what it would otherwise have been. But there are much bigger than 3x factors that are relevant. Such as, probability of success, magnitude of success, cost effectiveness.
Then you can take the overall cost effectiveness estimate (by combining various factors including probability it’s irrelevant due to AGI being too soon) and compare it to other interventions. Here, you’re not offering a specific alternative that is expected to pay off in worlds with AGI in the next 20 years. So it’s unclear how “it might be irrelevant if AGI is in the next 20 years” is all that relevant as a consideration.
Usually, the other interventions I compare it to are preparing for AI automation of AI safety by doing preliminary work to control/align those AIs, or AI governance interventions that are hopefully stable for a very long time, and at least for the automation of AI safety, I assign much higher magnitudes of success, conditioning on success, like multiple OOMs combined with moderately better cost effectiveness and quite larger chances of success than the genetic engineering approach.
To be clear, the key variable is conditional on success, the magnitude of that success is very, very high in a way that no other proposal really has, such that even with quite a lot lower probabilities for success than me, I’d still consider preparing for AI automation of AI safety and doing preliminary work such that we can trust/control these AIs to be the highest value alignment target by a mile.
Oh, to be clear I do think that AI safery automation is a well targeted x risk effort conditioned on the AI timelines you are presenting. (Related to Paul Christiano alignment ideas, which are important conditional on prosaic AI)
EY is known for considering humanity almost doomed. He may think that the idea of human intelligence augmentation is likely to fail. But it’s the only hope. Of course, many will disagree with this.
The problem is that from a relative perspective, human augmentation is probably more doomed than AI safety automation, which in turn is more doomed than AI governance interventions, though I may have gotten the relative ordering of AI safety automation and I think the crux is I do not believe in the timeline for human genetic augmentation in adults being only 5 years, even given a well-funded effort, and I’d expect it to take 15-20 years, minimum for large increases in adult intelligence, which basically rules out the approach given the very likely timelines to advanced AI either killing us all or being aligned to someone.
Yudkowsky may think that the plan ‘Avert all creation of superintelligence in the near and medium term — augment human intelligence’ has <5% chance of success, but your plan has <<1% chance. Obviously, you and he disagree not only on conclusions, but also on models.
If somehow international cooperation gives us a pause on going full AGI or at least no ASI—what then?
Just hope it never happens, like nuke wars?
The answer now is to set later generations up to be more able.
This could mean doing fundamental research (whether in AI alignment or international game theory or something else), it could mean building institutions to enable it, and it could mean making them actually smarter.
Genes might be the cheapest/easist way to affect marginal chances given the talent already involved in alignment and the amount of resources required to get involved politically or in building institutions
If somehow international cooperation gives us a pause on going full AGI or at least no ASI—what then?
Just hope it never happens, like nuke wars?
The answer is no, but this might have to happen under certain circumstances.
The usual case (assuming that the government bans or restricts compute resources, and/or limits algorithimic research), is to use this time to either let the government fund AI alignment research, or go for a direct project to make AIs that are safe to automate AI safety research, and given that we don’t have to race against other countries, we could afford far more safety taxes than usual to make AI safe.
I think the key crux is I don’t particularly think genetic editing is the cheapest/easiest way to affect marginal chances of doom, because of time lag plus needing to reorient the entire political system, which is not cheap, and the cheapest/easiest strategy to me to affect doom probabilities is to do preparatory AI alignment/control schemes such that we can safely hand off the bulk of the alignment work to the AIs, which then solve the alignment problem fully.
Your direction sounds great—but how well can $4M move the needle there? How well can genesmith move the needle with his time and energy?
I think you’re correct about the cheapest/easist strategy in general, but completely off in regards to marginal advantages.
Major labs will already be pouring massive amounts of money and human capital into direct AI alignment and using AIs to align AGI if we get to a freeze, and the further along in capabilities we get the more impactful such research would be.
Genesmith’s strategy benefits much more from starting now and has way less human talent and capital involved, hence higher marginal value
TBH, I don’t particularly think it’s one of the most important projects right now, due to several issues:
There’s no reason to assume that we could motivate them any better than what we already do, unless we are in the business of changing personality, which carries it’s own problems, or we are willing to use it on a massive scale, which simply cannot be done currently.
We are running out of time. The likely upper bound for AI that will automate basically everything is 15-20 years from Rafael Harth and Cole Wyeth, and unfortunately there’s a real possibility that the powerful AI comes in 5-10 years, if we make plausible assumptions about scaling continuing to work, and given that there’s no real way to transfer any breakthroughs to the somatic side of gene editing, it will be irrelevant by the time AI comes.
Thus, human intelligence augmentation is quite poor from a reducing X-risk perspective.
On EV grounds, “2/3 chance it’s irrelevant because of AGI in the next 20 years” is not a huge contributor to the EV of this. Because, ok, maybe it reduces the EV by 3x compared to what it would otherwise have been. But there are much bigger than 3x factors that are relevant. Such as, probability of success, magnitude of success, cost effectiveness.
Then you can take the overall cost effectiveness estimate (by combining various factors including probability it’s irrelevant due to AGI being too soon) and compare it to other interventions. Here, you’re not offering a specific alternative that is expected to pay off in worlds with AGI in the next 20 years. So it’s unclear how “it might be irrelevant if AGI is in the next 20 years” is all that relevant as a consideration.
Usually, the other interventions I compare it to are preparing for AI automation of AI safety by doing preliminary work to control/align those AIs, or AI governance interventions that are hopefully stable for a very long time, and at least for the automation of AI safety, I assign much higher magnitudes of success, conditioning on success, like multiple OOMs combined with moderately better cost effectiveness and quite larger chances of success than the genetic engineering approach.
To be clear, the key variable is conditional on success, the magnitude of that success is very, very high in a way that no other proposal really has, such that even with quite a lot lower probabilities for success than me, I’d still consider preparing for AI automation of AI safety and doing preliminary work such that we can trust/control these AIs to be the highest value alignment target by a mile.
Oh, to be clear I do think that AI safery automation is a well targeted x risk effort conditioned on the AI timelines you are presenting. (Related to Paul Christiano alignment ideas, which are important conditional on prosaic AI)
EY is known for considering humanity almost doomed.
He may think that the idea of human intelligence augmentation is likely to fail. But it’s the only hope. Of course, many will disagree with this.
He writes more about it here or here.
The problem is that from a relative perspective, human augmentation is probably more doomed than AI safety automation, which in turn is more doomed than AI governance interventions, though I may have gotten the relative ordering of AI safety automation and I think the crux is I do not believe in the timeline for human genetic augmentation in adults being only 5 years, even given a well-funded effort, and I’d expect it to take 15-20 years, minimum for large increases in adult intelligence, which basically rules out the approach given the very likely timelines to advanced AI either killing us all or being aligned to someone.
Yudkowsky may think that the plan ‘Avert all creation of superintelligence in the near and medium term — augment human intelligence’ has <5% chance of success, but your plan has <<1% chance. Obviously, you and he disagree not only on conclusions, but also on models.
He already addressed this.
If somehow international cooperation gives us a pause on going full AGI or at least no ASI—what then?
Just hope it never happens, like nuke wars?
The answer now is to set later generations up to be more able.
This could mean doing fundamental research (whether in AI alignment or international game theory or something else), it could mean building institutions to enable it, and it could mean making them actually smarter.
Genes might be the cheapest/easist way to affect marginal chances given the talent already involved in alignment and the amount of resources required to get involved politically or in building institutions
The answer is no, but this might have to happen under certain circumstances.
The usual case (assuming that the government bans or restricts compute resources, and/or limits algorithimic research), is to use this time to either let the government fund AI alignment research, or go for a direct project to make AIs that are safe to automate AI safety research, and given that we don’t have to race against other countries, we could afford far more safety taxes than usual to make AI safe.
I think the key crux is I don’t particularly think genetic editing is the cheapest/easiest way to affect marginal chances of doom, because of time lag plus needing to reorient the entire political system, which is not cheap, and the cheapest/easiest strategy to me to affect doom probabilities is to do preparatory AI alignment/control schemes such that we can safely hand off the bulk of the alignment work to the AIs, which then solve the alignment problem fully.
Your direction sounds great—but how well can $4M move the needle there? How well can genesmith move the needle with his time and energy?
I think you’re correct about the cheapest/easist strategy in general, but completely off in regards to marginal advantages.
Major labs will already be pouring massive amounts of money and human capital into direct AI alignment and using AIs to align AGI if we get to a freeze, and the further along in capabilities we get the more impactful such research would be.
Genesmith’s strategy benefits much more from starting now and has way less human talent and capital involved, hence higher marginal value