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Wei_Dai comments on Open Thread: January 2010 - Less Wrong
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The idea is that the status quo (i.e., the outcome if the AIs fail to cooperate) is N possible worlds of equal probability, each shaped according to the values of one individual/AI. The AIs would negotiate from this starting point and improve upon it. If all the AIs cooperate (which I presume would be the case), then which AI gets randomly selected to take over the world won't make any difference.
In this case the AIs start from an equal position, but you're right that their values might also figure into bargaining power. I think this is related to a point Eliezer made in the comment I linked to: a delegate may "threaten to adopt an extremely negative policy in order to gain negotiating leverage over other delegates." So if your values make you vulnerable to this kind of threat, then you might have less bargaining power than others. Is this what you had in mind?
Letting a bunch of AIs with given values resolve their disagreement is not the best way to merge values, just like letting the humanity go on as it is is not the best way to preserve human values. As extraction of preference shouldn't depend on the actual "power" or even stability of the given system, merging of preference could also possibly be done directly and more fairly when specific implementations and their "bargaining power" are abstracted away. Such implementation-independent composition/interaction of preference may turn out to be a central idea for the structure of preference.
There seems to be a bootstrapping problem: In order to figure out what the precise statement is that human preference makes, we need to know how to combine preferences from different systems; in order to know how preferences should combine, we need to know what human preference says about this.
If we already have a given preference, it will only retell itself as an answer to the query "What preference should result [from combining A and B]?", so that's not how the game is played. "What's a fair way of combining A and B?" may be more like it, but of questionable relevance. For now, I'm focusing on getting a better idea of what kind of mathematical structure preference should be, rather than on how to point to the particular object representing the given imperfect agent.
What is/are your approach(es) for attacking this problem, if you don't mind sharing?
In my UDT1 post I suggested that the mathematical structure of preference could be an ordering on all possible (vectors of) execution histories of all possible computations. This seems general enough to represent any conceivable kind of preference (except preferences about uncomputable universes), but also appears rather useless for answering the question of how preferences should be merged.
Since I don't have self-contained results, I can't describe what I'm searching for concisely, and the working hypotheses and hunches are too messy to summarize in a blog comment. I'll give some of the motivations I found towards the end of the current blog sequence, and possibly will elaborate in the next one if the ideas sufficiently mature.
Yes, this is not very helpful. Consider the question: what is the difference between (1) preference, (2) strategy that the agent will follow, and the (3) whole of agent's algorithm? Histories of the universe could play a role in semantics of (1), but they are problematic in principle, because we don't know, nor will ever know with certainty, the true laws of the universe. And what we really want is to get to (3), not (1), but with good understanding of (1) so that we know (3) to be based on our (1).
Thanks. I look forward to that.
I don't understand what you mean here, and I think maybe you misunderstood something I said earlier. Here's what I wrote in the UDT1 post:
(Note that of course this utility function has to be represented in a compressed/connotational form, otherwise it would be infinite in size.) If we consider the multiverse to be the execution of all possible programs, there is no uncertainty about the laws of the multiverse. There is uncertainty about "which universes, i.e., programs, we're in", but that's a problem we already have a handle on, I think.
So, I don't know what you're referring to by "true laws of the universe", and I can't find an interpretation of it where your quoted statement makes sense to me.
I don't believe that directly posing this "hypothesis" is a meaningful way to go, although computational paradigm can find its way into description of the environment for the AI that in its initial implementation works from within a digital computer.
Here is a revised way of asking the question I had in mind: If our preferences determine which extraction method is the correct one (the one that results in our actual preferences), and if we cannot know or use our preferences with precision until they are extracted, then how can we find the correct extraction method?
Asking it this way, I'm no longer sure it is a real problem. I can imagine that knowing what kind of object preference is would clarify what properties a correct extraction method needs to have.
Going meta and using the (potentially) available data such as humans in form of uploads, is a step made in attempt to minimize the amount of data (given explicitly by the programmers) to the process that reconstructs human preference. Sure, it's a bet (there are no universal preference-extraction methods that interpret every agent in a way it'd prefer to do itself, so we have to make a good enough guess), but there seems to be no other way to have a chance at preserving current preference. Also, there may turn out to be a good means of verification that the solution given by a particular preference-extraction procedure is the right one.
So you know how to divide the pie? There is no interpersonal "best way" to resolve directly conflicting values. (This is further than Eliezer went.) Sure, "divide equally" makes a big dent in the problem, but I find it much more likely any given AI will be a Zaire than a Yancy. As a simple case, say AI1 values X at 1, and AI2 values Y at 1, and X+Y must, empirically, equal 1. I mean, there are plenty of cases where there's more overlap and orthogonal values, but this kind of conflict is unavoidable between any reasonably complex utility functions.
I'm not suggesting an "interpersonal" way (as in, by a philosopher of perfect emptiness). The possibilities open for the search of "off-line" resolution of conflict (with abstract transformation of preference) are wider than those for the "on-line" method (with AIs fighting/arguing it over) and so the "best" option, for any given criterion of "best", is going to be better in "off-line" case.
[Edited] I agree that it is probably not the best way. Still, the idea of merging values by letting a bunch of AIs with given values resolve their disagreement seems better than previous proposed solutions, and perhaps gives a clue to what the real solution looks like.
BTW, I have a possible solution to the AI-extortion problem mentioned by Eliezer. We can set a lower bound for each delegate's utility function at the status quo outcome, (N possible worlds with equal probability, each shaped according to one individual's utility function). Then any threats to cause an "extremely negative" outcome will be ineffective since the "extremely negative" outcome will have utility equal to the status quo outcome.