We essentially have this already occurring in the form of fantasy football leagues, which itself has gone from basically being gambling to basically being an e-sport. If you haven't considered it already, perhaps you should look into some of the ways that the NFL is making use of fantasy football for both marketing and information gathering purposes.
I like to imagine that eventually we will be able to boil the counter-intuitive parts of quantum physics away into something more elegant. I keep coming back to the idea that every current interaction could theoretically be modeled as the interactions of variously polarized electromagnetic waves. Such as mass being caused by rotational acceleration of light, and charge being emergent from the cross-interactions of polarized photons. I doubt the idea really carves reality at the joints, but I think it's probably closer to accurate than the standard model, which is functional but patchworked, much like the predictive models used by astrologers prior to the acceptance of heliocentrism.
I seem to have explained myself poorly. You are effectively restating the commonly held (on LessWrong) views that I was attempting to originally address, so I will try to be more clear.
I don't understand why you would use a particular fixed standard for "human level". It seems to be arbitrary, and it would be more sensible to use the level of human at the time when a given AGI was developed. You yourself say as much in your second paragraph ("more capable than its creators at the time of its inception"). Since IA rate determines the capabilities of the AIs creators, then a faster rate of IA than AI would mean that the event of a more capable AGI would never occur.
If a self-modifying AGI is less capable than its creators at the time of its inception, then it will be unable to FOOM, from the perspective of its creators, both because they would be able to develop a better AI in a shorter time than an AI could improve itself, and because if they were developing IA at a greater pace they would advance faster than the AGI that they had developed. Given the same intelligence and rate of work, an easier problem will see more progress. Therefore, if IA is given equal or greater rate of work than AI, and it happens to be an easier problem, then humans would FOOM before AI did. A FOOM doesn't feel like a FOOM from the perspective of the one experiencing it though.
Your final point makes sense, in that it address the point that the probability of the first fast takeoff being in the AI field may be larger than the IA field, or in that AI is an easier problem. I fail to see why a software problem is inherently easier than a biology or engineering problem though. A fundamental breakthrough in software is just as unlikely as a hardware, and there are more paths to success for IA than AI that are currently being pursued, only one of which is a man-machine interface.
I considered being a bit snarky and posting each of your statements as direct opposites (IE all that matters is if a self modifying human becomes more capable than an AI at the time of its augmentation), but I feel like that would convey the wrong message. The dismissive response genuinely confuses me, but I'm making the assumption that my poor organization has made my point too vague.
I have been mulling around a rough and mostly unformed idea in my head regarding AI-first vs IA-first strategies, but I was loathe to try and put it into words until I saw this post, and noticed that one of the scenarios that I consider highly probable was completely absent.
On the basis that subhuman AGI poses minimal risk to humanity, and that IA increases the level of optimization ability required of an AI to be considered human level or above, it seems that there is a substantial probability that an IA-first strategy could lead to a scenario in which no superhuman AGI can be developed because it is economically infeasible to research that field as opposed to optimizing accelerating returns from IA creation and implementation. Development of AI whether friendly or not would certainly occur at a faster pace, but if IA proves to simply be easier than AI, which given our poor ability estimate the difficulty of both approaches may be true, development in that field would continue to outpace it. It could certainly instigate either a fast or slow takeoff event from our current perspective, but from the perspective of enhanced humans it would be simply an extension of existing trends.
A similar argument could be made in regard to Hanson's WBEM based scenarios, through the implication that given the ability to store a mind to some hardware system, it would be more economically efficient to emulate that mind at a faster pace than to parallel process multiple copies of that mind in the same hardware space, and likewise hardware design would trend toward rapid emulation of single workers rather than multiple instances in order to reduce costs accrued by redundancy and increase gains in efficiency accrued by experience. This would imply that mind enhancement of a few high efficiency minds would occur much earlier and that exceptional numbers of emulated workers would be unlikely to be created, but rather that a few high value workers would occupy a large majority of relevant hardware very soon after the creation of such technology.
An IA field with greater pace than AI does of course present its own problems, and I'm not trying to endorse moving towards an IA-first approach with my ramblings. I suppose I'm simply trying to express the belief that discussion of IA as an alternative to AI rather than an instrument toward AI is rather lacking in this forum and I find myself confused as to why.
I'm not sure why you phrased your comment as a parenthetical, could you explain that? Also, while I agree with your statement, appearing competent to engage in discussion is quite important for enabling one to take part in discussion. I don't like seeing someone who is genuinely curious get downvoted into oblivion.
That question is basically the hard question at the root of the difficulty of friendly AI. Building an AI that would optimize to increase or decrease a value through its actions is comparably easy, but determining how to evaluate actions into a scale that measures results in a comparison with human values is incredibly difficult. Determining and evaluating AI friendliness is a very hard problem, and you should consider reading more about the issue so that you don't come off as naive.
While personal identification with a label can be constraining, I find that the use of labels for signalling are tremendous. Not only does a label work in the same way as jargon, expressing a complex data set with a simple phrase, but because most labels carry tribal consequences it acts as a somewhat costly signal in terms of identifying alliances. Admittedly, one could develop a habit of using labels which becomes a personal identification, but being aware of such risk is the best way to combat the effects thereof.
I certainly agree with that statement. It was merely my interpretation that violating the intentions of the developer by not "following it's programming" is functionally identical to poor design and therefore failure.
Of course this is something that only a poorly designed AI would do. But we're talking about AI failure modes and this is a valid concern.
Doesn't this, by extension, seem to more directly lead to a cost-benefit problem of coalitions?
At some point the marginal cost of additional votes leads will be greater than the marginal cost of influencing other voters, either via direct collusion, or via altering their opinions through alternative incentives, such as by subsidizing voters who agree but care less, or by offering payments or commitments that mitigate the reasons opponents care about the issue.
I'm not sure that's necessarily a bad thing, but there are lots more ways to influence other voters with resources than just colluding to vote to eachother's advantage.