Agree UDT is a lot better than FDT.
I talk about the indexical uncertainty thing—but the simulation is supposed to see a bomb.
Bentham's Bulldog
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The Day Humanity Died (Parody of American Pie)
Tyler said in dms “Well FDT is wrong but less wrong than CDT.”
You are correct, thanks for the correction.Edit: wait actually this is wrong, Tyler said in dms “Well FDT is wrong but less wrong than CDT.”
A big chunk of philosophers one-box. These people generally adopt evidential decision theory. They also cooperate in PD with twin. So no, FDT isn’t just the same as one boxing. If it was, then all EDTers would be FDTers.
I don’t think you should program an AI to follow CDT. This is because decision theories are theories of which actions are rational, not the dispositions that you want to have. So I agree with Christiano—this obviously can’t be the criterion for being a functional decision theorist.
Here’s one test: there is not a single person, to the best of my knowledge, anywhere in the world who adopts FDT and has a Ph.D in philosophy. This fact is surprising if it’s the right view.
Who are the most accomplished and high impact philosophers who work in industry and adopt FDT?
Why is Newcomb’s any less fair than Newcomb’s revenge? https://www.umsu.de/blog/2022/772
“FDT outputs X” is importantly underspecified. If you just change what it says in your exact situation, then you have no account of how it changes the other algorithms like the simulator.
The bigger problem though isn’t the counterlogicals but analyzing how in the counterlogical world other algorithms would be different.
I address that. The point is, CDTers have a parallel claim to Newcomb’s problem being unfair.
The point isn’t just that FDT isn’t well-defined mathematically. I explain in-principle reasons why it can’t be.
There’s a lot of snark here but it’s all incorrect.
//No, it says to two-box in both cases for exactly that axiom of extensionality (“equivalent prediction principle”).//
I explain why this isn’t right. Only one algorithm is dependent on yours. The other is just correlated.
//This entire objection is a failure to recognize that 0% and 100% are not probabilities. Rather than saying, “are these the exact same?” which is always impossible to verify to 100% confidence, not just with algorithms, you should ask, “how similar are these policies?”//
This is wrong on a number of counts. First of all, measures of similarities are not the same as probabilities. So this doesn’t require any claim about similarity. Note that FDT wants to say that if you’re in prisoner’s dilemma against a perfect twin, your actions are correlated 100% with what they do (even if you don’t have a credence of 1 that that is so). Second, as I explain, measuring similarity is even more difficult.
Re calculator, whether they output the same thing depends on how you interpret their outputs, as explained in the post.
Re being able to determine what’s true of one algorithm from the other, that’s just looking at correlation which can’t be the relevant notion for the reasons I explain.
We imagine an agent who never messes up an accidentally picks the wrong one. By the lights of FDT, you get more expected utility timelessly if you’re always disposed not to pay. And it’s a stipulation of the thought experiment that the predictor is reliable—doesn’t matter if this could exist in the real world.
99.9% accurate in the sense that 99.9% of the time, the predictor guesses right. We additionally can imagine that his decision depends on what you do on the last moment, not just on what you’re pretending to do until then.
Yes that’s just a different thought experiment from the one I gave.
Why does CDT become incoherent if you’re indexically selfish?
Something can be a good predictor between you even if there is a noticeable difference between you and then. The standard Newcomb’s problem doesn’t assume that there’s a conscious organism running in the simulator’s mind.
I explain at length why you can’t just rely on correlations between two algorithms wrt their outputs.
I lean towards thinking you shouldn’t pay, but I’m somewhat uncertain about that. I lean causal, but am sympathetic both to EDT and some third undiscovered theory.
For what you should do in the problem. No one thinks you’ll fool the predictor. What we think is that it is irrational to take some action if, at the time you take it, you know it will simply result in you having less money than if you took a different action. We’re not under the illusion that such people on average leave with more money or that you should precommit to two-boxing or any such things.
Not following what you think I’m misunderstanding or what this has to do with the things I say. I grant, of course, that the average returns are higher if you’re disposed to one-box in transparent Newcomb. So if you’re just looking at timelessly beneficial dispositions, those are the same across transparent and opaque Newcomb. But the entire dispute is about whether those perfectly match up with rational choice.
(Let me know if I got your point right).
Functional Decision Theory: Not Even Wrong, Also Wrong
Strong Longtermism Is Simply Correct
That isn’t one of the options.
Sorry for the late reply, forgot that I’d posted this on LessWrong an don’t check regularly.
The view you have described—that you should follow deontic norms because it has good consequences—is not deontology. It is a kind of consequentialism of a kind that thinks a big part of producing good consequences is following good norms. This piece wasn’t arguing against that position, and I actually agree with that position! For more see https://utilitarianism.net/types-of-utilitarianism/#multi-level-utilitarianism-versus-single-level-utilitarianism
Deontology is distinct in that it says that even if you had a perfect guarantee that an action would have good consequences taking into account all second-order effects, you still shouldn’t do it sometimes if it violates rights. That’s what I was arguing against. The way LessWrong uses these terms is idiosyncratic.
So freaking good!