dankane
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Unless you can explain to me how prediction markets are going to break the pattern that two different shares of the same stock have correlated prices.
I'm actually not sure how prediction markets are supposed to have an effect on this issue. My issue is not that people have too much difficulty recognizing patterns. My issue is that some patterns once recognized do not provide incentives to make that pattern disappear. Unless you can tell me how prediction markets might fix this problem, your response seems like a bit of a non-sequitur.
This seems like too general a principle. I agree that in many circumstances, public knowledge of a pattern in pricing will lead to effects causing that pattern to disappear. However, it is not clear to me that this is always to case, or that the size of the effect will be sufficient to complete cancel out the original observation.
For example, I observe that two different units of Google stock have prices that are highly correlated with each other. I doubt that this observation will cause separate markets to spring up giving wildly divergent prices to different shares of the same stock. I also note that stock prices are always non-negative. I also... (read more)
We probably couldn't even talk ourselves out of this box.
I don't know... That sounds a lot like what an AI trying to talk itself out of a box would say.
Hmm... I would probably explain the threshold for staying in the house not as an implicit expected probability computation, but an evaluation of the price of the discomfort associated with staying in a location that you find spooky. At least for me, I think that the part of my mind that knows that ghosts do not exist would have no trouble controlling whether or not I remain in the house or not. However, it might well decide that it is not worth the $10 that I would receive to spend the entire night in a place where some other piece of my mind is constantly yelling at me to run away screaming.
It's just that such self-referential criteria as reflective equilibrium are a necessary condition
Why? The only example of adequately friendly intelligent systems that we have (i.e. us) don't meet this condition. Why should reflective equilibrium be a necessary condition for FAI?
That may be true (at least to the degree to which it is sensible to assign a specific cause to a given util). However, it is not very good evidence that investment in first world economies is the most effective way to generate utils in Africa.
OK. So suppose that I grant your claim that donations to sub-Saharan Africa will not substantially affect the size of the future economic pie, but that other investments will. I claim that there may still be reason to donate there.
I grant that such a donation will produce fewer dollars of value than investing in capitol infrastructure. On the other hand dollars is not the objective, utils are. We can reasonably assume that marginal utility of an extra dollar for a given person is decreasing as that person's wealth increases. We can reasonably expect that world GDP per capita will be much higher in 100 years, and know that GDP per capita is much higher in the US than in sub-Saharan Africa. Thus, even if an investment in first-world infrastructure produces more total dollars of value, these dollars are going to much wealthier people than dollars donated to people today in sub-Saharan Africa, and thus might well produce fewer total utils.
[I realize that I missed the train and probably very few people will read this, but here goes]
So in non-iterated prisoner's dilemma, defect is a dominant strategy. No matter what the opponent is doing, defecting will always give you the best possible outcome. In iterated prisoner's dilemma, there is no longer a dominant strategy. If my opponent is playing Tit-for-Tat, I get the best outcome by cooperating in all rounds but the last. If my opponent ignores what I do, I get the best outcome by always defecting. It is true that all defects is the unique Nash equilibrium strategy, but this is a much weaker reason for playing it, especially given... (read more)
I think that the way that humans predict other humans is the wrong way to look at this, and instead consider how humans would reason about the behavior of an AI that they build. I'm not proposing simply "don't use formal systems", or even "don't limit yourself exclusively to a single formal system". I am actually alluding to a far more specific procedure:
Now it turns out that... (read more)
I feel like your discussion of predictors makes a few not-necessarily-warranted assumptions about how the predictor deals with self-reference. Then again, I guess anything that doesn't do this fails as a predictor in a wide range of useful cases. It predicts a massive fire will kill 100 people, and so naturally this prediction is used to invalidate the original prediction.
But there is a simple-ish fix. What if you simply ask it to make predictions about what would happen if it (and say all similar predictors) suddenly stopped functioning immediately before this prediction was returned?