I sincerely hope that if anyone has a concrete, actionable answer to this question, that they're smart enough not to share it publicly, for what I hope are obvious reasons.
But aside from that caveat, I think you are making several incorrect assumptions.
True, but I think in this case there's at least no risk of an infinite regress. At one end, yes, it bottoms out in an extremely vague and inefficient but general hyperprior. I would guess from the little I've read that in humans these are the layers that govern how we learn from even before we're born. I would imagine an ASI would have at least one layer more fundamental than this, which enable it to change various fixed-in-humans assumptions about things.
At the other end would be the most specific or most abstracted layer of priors that has proven useful to date. Somewhere in the stack are your current best processes for deciding whether particular priors or layers of priors are useful or worth keeping or if you need a new one.
I am actually not sure whether 'prior' is quite the right term here? Some of it feels like the distinction between thingspace and conceptspace, where the priors might be more about the expectations what things exist and where natural concept boundaries lie and how to evaluate and re-evaluate those?
I equally hope to write "life in the day of" posts for each category soon as a better visualisation of what each of these worlds entails.
I think this would be really interesting and useful! For me, just reading the flowchart and seeing the list laid out makes me assume most people would seriously underestimate how broad these categories could actually be.
Exact placement would of course involve a number of value judgment calls. For example, I would probably characterize something like the outcome in Friendship is Optimal as an example of #7, but it could also be considered 8/10/11.
I'm also curious about your thoughts on the relative stability of each of these categories. To me, #6 seems metastable at best, for example, while #9 is an event, not a trajectory. AKA it is at least theoretically recoverable to some of the other states (or else declines into 10/11).
The ability to get to consciously decide when to discard or rewrite or call on the simple programs is a superpower evolution didn't give humans. One that it seems would be the obvious solution for an AI that gets to call on an external, updatable set of tools. Or an ASI got got to rewrite the parts of itself that call the tools or notice (what it previously thought were) edge cases.
AKA, an ASI can go ahead and have a human-specific prior. It can choose to apply it until it meets entities that are alien, then stop applying it. Humans can't really do that, in the same way that we can't turn off our visual heuristics when encountering things we consciously know are weirdly constructed adversarial examples, even if we can sometimes override them with enough effort. The ASI, presumably, would further react to encountering aliens by reasoning from more basic principles (recurse as needed) as it learns enough to create 1) a new prior specific to those aliens, 2) a new prior specific to those aliens' species, culture, world, etc.
Or at least, that's my <4 minute human-level single attempt at guessing a lower bound on an ASI's solution.
America would have to pay the subsidies off.
This is not necessarily true. At least not on any currently-human-relevant timescale. The ballooning can be a problem, especially when the money is spent very poorly. But if a reasonable fraction of it is spent on productive assets and other forms of growth, debt can grow for a long time. Longer than the typical lifespan of a country or currency.
The part of the reasoning where others use the AI to generate value does seem to underexplore the possibility that the AI companies themselves use the AI for that first.
What would you say to the idea that other kinds of capital retain value post-AGI? Like land, or mineral rights, or electricity generating capacity? I think those are also unlikely, but I do come across them once in a while.
Let's consider the set of worlds where developing AGI does not destroy or permanently disempower humanity.
You have a good point, that in many such scenarios the investors in AI labs, or the AI companies, may not be able to capture more than a tiny fraction of the value they generate.
Does this make the investment a mistake?
Personally, I don't think so. The people making these investments generally have a level of wealth where no amount of additional money can make more than a small additional improvement to their well being. In contrast, AGI and ASI could plausibly (within their lifetimes) render the world as a whole many OOMs richer, with capabilities that seem centuries or millennia away in a non-AI future. Not being able to claim all of that wealth may cost them status/dominance/control, but they would also gain the status/prestige of having enabled such radical improvement. And in any case, they might (very reasonably, IMO) be willing to trade status for immortality + godlike technological powers.
Also, in the proportion of worlds where the AI labs or those funding them do manage to retain control of the wealth created or to obtain and hold other forms of power, that's quite the high payoff even at these valuations.
Yeah, my own instinct is to just see if the results are interesting in such a way that if I believed them, it would meaningfully change what I thought was the best strategy. In this case, don't think so. Even what I see as a very optimistic set of assumptions still results in what I see as an unacceptably high risk of very bad outcomes. I do find the exploration itself interesting, though.
Strictly speaking I only presupposed an AI could reach close to the limits of human intelligence in terms of thinking ability, but with the inherent speed and parallelizability and memory advantages of a digital mind.
In small ways (aka sized appropriately for current AI capabilities) this kind of thing shows up all the time in chains of thought in response to all kinds of prompts, to the point that no, I don't have specific examples, because I wouldn't know how to pick one. The one that first comes to mind, I guess, was using AI to help me develop a personalized nutrition/supplement/weight loss/training regimen.
That's fair, and a reasonable thing to discuss. After all, the fundamental claim of the book's title is about a conditional probability: IF it turns out that the anything like our current methods scale to superintelligent agents, we'd all be screwed.