re: threats: I don't see how exactly a brain based AI can be even seen as a 'threat' to survival of humanity. I instead see it as about the only way that permits humanity to survive at all. First of all, the simbrain is a part of humanity itself precisely in the way in which from-scratch AI isn't, second, even if the simbrains are a little bit charitable towards the original humans, that's your FAI.
Also:
when you don't know if you have lesion and the probability of having lesion.
You would still have priors for all of these things.
Even if you do, how is knowing that the lesion causes cancer going to change anything about P(smokes|gets cancer) ? The issue is that you need to do two equations, one for case when you do have lesion, and other for when you don't have lesion. The EDT just confuses those together.
edit: ahh, wait, the EDT is some pretty naive theory that can not even process anything as complicated as evidence for causality working in our universe. Whatever then, a thoughtless approach leads to thoughtless results, end of story. The correct decision theory should be able to control for pre-existing lesion when it makes sense to do so.
I think you've got it. Pure EDT and CDT really just are that stupid - and irredeemably so because agents implementing them will not want to learn how to replace their decision strategy (beyond resolving themselves to their respective predetermined stable outcomes). Usually when people think either of them are a good idea it is because they have been incidentally supplementing and subverting them with a whole lot of their own common sense!
I propose a nonstupid decision theory then.
In the smoking lesion, I do two worlds: in one I have lesion, in other I don't, weighted with p and 1-p . That's just how i process uncertainties . Then I apply my predictions to both worlds, given my action, and I obtain the results which I weight by p and 1-p (i never seen the possible worlds interact) . Then I can decide on action assuming 0<p<1 . I don't even need to know the p, and updates to my estimate of p that result from my actions don't change the decisions.
In the newcomb's problem, i'm inclined to do exact same thing: let p is probability that the one-box was predicted, then onebox < twobox by 1000000 * p + 0 * (1-p) < 1001000 * p + 1000 * (1-p) . And I am totally going to do this if I am being predicted based on psychology test I took back in elementary school, or based on genetics. But I get told that the 1001000 * p and 0 * (1-p) never happens, i.e. I get told that the equation is wrong, and if i assign high enough confidence to that, higher than to my equation, I can strike out the 1001000 * p and 0 * (1-p) from the equation (and get some nonsense which i fix by removing the probabilities altogether), deciding to one-box as the best effort i can do when i'm told that my equation won't work, and I don't quite know why.
(The world model of mine being what it is, I'll also have to come up with some explanations for how the predictor works before i assign high enough probability to the predictor working correctly for me. E.g. I could say that the predictor is predicting using a quantum coin flip and then cutting off branches in MWI where it was wrong, or I could say, the predictor is working via mind simulation, or even that my actions somehow go into the past. )
Of course it is bloody hard to formalize an agent that got a world model of some kind, and which can correct it's equations if it is convinced with good enough evidence that the equation is somehow wrong (which is pretty much the premise of Newcomb's paradox).
edit: ahh, wait, the EDT is some pretty naive theory that can not even process anything as complicated as evidence for causality working in our universe.
Can you explain this?
EDT is described as $V(A) = \sum_{j} P(O_j | A) U(O_j)$. If you have knowledge about the mechanisms behind the how the lesion causes smoking, that would change $P(A | O_j)$ and therefore also $P(O_j | A)$.
I don't see how knowledge how the lesion works would affect the probabilities when you don't know if you have lesion and the probability of having lesion.
I would like to ask for help on how to use expected utility maximization, in practice, to maximally achieve my goals.
I think the best single-sentence answer is: don't.
(Quick comment before I go offline for today.)
Here is the problem. If I use expected utility maximization (EU) on big and unintuitive problems like existential risks and to decide what I should do about it; If I use EU to decide how to organize my life by and large; If I use EU to decide to pursue a terminal goal but then stop using it to decide what goals are instrumental in achieving the desired outcome, then how does it help to use EU at all? And otherwise, how do I decide where to draw the line?
People closely associated with SIAI/LW do use EU in support of their overall goals, yet ignore EU when it comes to flying to NY or writing a book about rationality:
[S]uppose you have a moral view that counts future people as being worth as much as present people. You might say that fundamentally it doesn't matter whether someone exists at the current time or at some future time, just as many people think that from a fundamental moral point of view, it doesn't matter where somebody is spatially---somebody isn't automatically worth less because you move them to the moon or to Africa or something. A human life is a human life. If you have that moral point of view that future generations matter in proportion to their population numbers, then you get this very stark implication that existential risk mitigation has a much higher utility than pretty much anything else that you could do.
-- Nick Bostrom
If you want to maximize your marginal expected utility you have to maximize on your choice of problem over the combination of high impact, high variance, possible points of leverage, and few other people working on it. The problem of stable goal systems in self-improving Artificial Intelligence has no realistic competitors under any three of these criteria, let alone all four.
In terms of expected utility maximization, even large probabilities of jumping the interval between a universe-history in which 95% of existing biological species survive Earth’s 21st century, versus a universe-history where 80% of species survive, are just about impossible to trade off against tiny probabilities of jumping the interval between interesting universe-histories, versus boring ones where intelligent life goes extinct, or the wrong sort of AI self-improves....with millions of people working on environmentalism, and major existential risks that are completely ignored… if you add a marginal resource that can, rarely, be steered by expected utilities instead of warm glows, devoting that resource to environmentalism does not make sense.
TBH i don't see how EU is being used with regards to the friendly AI.
The arguments are so much based on pure guessing, that their external probabilities are very low, and the differences in the utilities really could be so low that someone could conceivably say 'I wouldn't give up $1 of mine to provide $1 million for an attempt to mitigate risk of UFAI, even if you argue that UFAI tortures every possible human mind-state'. [note: i presume literal $, not resources, so the global utility of creation of 1 million $ is zero]
The only way EU comes into play is the appeal to the purely intuitive feeling we get, that the efficacy of the FAI effort can't possibly be so low as to degrade such giant utility to the trivial level of "should i chew gum or not", or even unimaginably less than that. Unfortunately, though, it can. The AI design space is multi-dimensional and very huge. The intuitive feeling may be correct, or may be entirely wrong. There's a lot of fallacies - being graded for effort in education contributes to one, the just world fallacy contributes to another - which may throw the intuitive feeling way off.
That part is correct, but opting not to smoke for the purpose of avoiding this increase in probability s an error.
I still don't see how it is. If the agent has no other information, all he knows is that if he decides to smoke it is more likely that he has the lesion. His decision itself doesn't influence whether he has the lesion, of course. But he desires to not have the lesion, and therefore should desire to decide not to smoke.
The way the lesion influences deciding to smoke will be through the utility function or the decision theory. With no other information, the agent can't trust that his decision will outsmart the lesion.
Ahh, I guess we are talking about same thing. My point is that given more information - and making more conclusions - EDT should smoke. The CDT gets around requirement for more information by cheating - we wrote some of that information implicitly into CDT - we thought CDT is a good idea because we know our world is causal. Whenever EDT can reason that CDT will work better - based on evidence in support of causality, the model of how lesions work, et cetera - the EDT will act like CDT. And whenever CDT reasons that EDT will work better - the CDT self modifies to be EDT, except that CDT can't do it on spot and has to do it in advance. The advanced decision theories try to 'hardcode' more of our conclusions about the world into the decision theory. This is very silly.
If you test humans, I think it is pretty clear that humans work like EDT + evidence for causality. Take away evidence for causality, and people can believe that deciding to smoke retroactively introduces the lesion.
edit: ahh, wait, the EDT is some pretty naive theory that can not even process anything as complicated as evidence for causality working in our universe. Whatever then, a thoughtless approach leads to thoughtless results, end of story. The correct decision theory should be able to control for pre-existing lesion when it makes sense to do so.
Some thinking on what to think about is very important, unfortunately it is also very hard to get it right. For example here we can discuss optimal decisions involving probability, entirely forgetting the limited runtime and the effect of introducing risk on the efficacy of bounded calculations in the future. When you take risks, for example, you double the size of the expected-utility-calculating tree, meaning that in limited time you cut down on depth.
Then there's this: you can think how to optimize your behaviour by single digit percentage, for example, by trying to do nonbiased estimates of your utility, which you won't be doing very well anyway because the world is hard to predict. Or you can spend that runtime e.g. learning to program, then coming up and writing some popular application, putting it up on a relevant store, and getting way more than enough money for papering over your inefficiencies.
re: pill.
The important thing is that you should expect, with very good confidence, to have found the toxic effects of the drug if there were any. If it is so, then not having found such effects is good evidence. You do not expect to have a proof that ghosts do not exist, if they don't, that's what makes 'because' be a fallacy. You do not expect to have a proof the pills are unsafe, before you did proper testing, either; and even after testing it may easily be unsafe and there's certain risk remaining. The reasoning about pills used to be every bit as fallacious as the reasoning about ghosts - and far more deadly, before the mid 20th century or so, from which point we arranged the testing as to expect to find most of the toxic effects before approving drugs.
re: circularity
Well, if there weren't any other claims about electrons or god, those two claims would not even be claims but simply word definitions. The 'entity we think we seen everywhere and call electrons leaves tracks because of such and such' is the real argument, and 'god the creator of the universe personally wrote the bible' is the real argument. If we actually expected bible to be less likely to exist without God, then the bible would have been evidence, but as such I'd say the likehood of bible-like-religious-text is at very best entirely unrelated to existence or non-existence of god.
That's btw the way my atheism is, except other way around: nothing in religion is coupled in any way what so ever to existence or non-existence of god; i don't need to know if god exists or not to entirely reject religion and be strongly anti-religious. If anything, existence of multiple religions and the evil things that religions did and how they clashed with each other, would seem like a kind of thing that would be less likely in universe that has the creator god who watches over it, and constitute a (weak) evidence against existence of god (and fairly strong evidence against existence of god that intervenes etc). For me the existence of religions (the way they are) is a weak evidence that God does not exist.
I agree with you. I don't think that EDT is wrong on the Smoking Lesion. Suppose that, in the world of this problem, you see someone else decide to smoke. What do you conclude from that? Your posterior probability of that person having the lesion goes up over the prior. Now what if that person is you? I think the same logic should apply.
That part is correct, but opting not to smoke for the purpose of avoiding this increase in probability s an error.
An error that an evidence based decision theory needs not make if it can process the evidence that causality works and that it is actually the pre-existing lesion that causes smoking, and control for the pre-existing lesion when comparing the outcomes of actions. (And if the agent is ignorant of the way world works - then we shouldn't benchmark it against an agent into which we coded the way our world works)
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Many people on Less Wrong see Judea Pearl's work as the right approach to formalizing causality and getting the right conditional probabilities. But if it was simple to formally specify the right causal model of the world given sensory information, we'd probably have AGI already.
Sitting and figuring out how exactly causality works, is the kind of thing we want the AGI to be able to do on it's own. We don't seem to be born with any advanced expectations of the world, such as notion of causality; we even learn to see; the causality took a while to invent, and great many people have superstitions which are poorly compatible with causality; yet even my cats seem to, in their lives, have learnt some understanding of causality.