Researcher at the Center on Long-Term Risk. All opinions my own.
(Due to time constraints I expect I can only give brief replies/clarifications, going forward. I hope a full read of the sequence will suffice, though I realize it's quite long, sorry!)
But you don't need to restrict yourself to concerns about the whole future lightcone to run into this problem - at the foundational level this is true of every statement. ... I don't see why we should do so with credences (which are of course usually non-foundational statements)
(See my last para for the "future lightcone" thing.)
I don't understand your Munchausen trilemma argument yet. You say credences are "of course usually non-foundational". Agreed! That's exactly why I think our choices of credences require deeper justification. (Whereas foundational things, like Huemer's "seemings", don't.[1])Â
forecasting 0.1234567% chance of rain if the extra precision was actually decision-relevant
The extra precision might be "decision-relevant" in the sense that: if you were justified in a credence of 0.1234567% + 0.0000001%, you should choose A, and if you were justified in a credence of 0.1234567% - 0.0000001%, you should choose B. But the whole question is why we'd be justified in the former vs. the latter, epistemically. ("I need to make a choice" isn't a justification for any particular option you choose.)
Your counterpoint seems to be that in some cases that feel sort-of- equal (and about which, in the cases you describe we actually have a lot of information), we might be inclined to give equal credence.Â
That's not what I'm saying, sorry â I'm denying we should give equal credence. Please see my reply to a similar comment here, and section 3.2.1 and 4.1.1 of the sequence (you might need to CTRL+F some terms defined earlier in the sequence). If it's still unclear, I'm happy to try to explain further if you could point to particular passages that need clarification.
The precise EV approach is well evidenced in short-term decision-making
I don't know what exactly this means. If you mean "we seem to be justified in using precise EVs in short term decision making":
That is, they don't require deeper justification prima facie. They're still defeasible.
Hi Arepo, thanks for sharing your cruxes here.
The argument I give against assigning precise credences is that it's arbitrary â literally, you pick one precise credence over many others for no reason. To me, "you have no reason to do this thing" is a pretty darn strong argument. :) (ETA: I like the intuition pump in this very short post, if it helps.)
doesn't say why this means we shouldn't/can't pick credences according to our best effort.
Why does "our best effort" need to be precise? Can you say more what exactly you mean? (If the intuition is that more precision = more information, I address that in the post.)
It also doesn't say why, if we can measure short term value, we shouldn't use that as a justification for our decisionmaking process and assume EV from events that we don't think we can assess is 0.
I address this in the unawareness sequence. I recommend reading the table in my summary post â the row with "Even if our impact is dominated by consequences weâre unaware of..." â for the high-level idea, and the links therein for details.
especially when we're not given an alternative
Isn't this privileging the hypothesis? My claim is that we don't have a positive argument in favor of doing what the precise EV approach recommends (or fuzzier "best guesses", either). If our best defense of that approach is "what else is there?", that seems rather damning.
taking your probability-weighted expectation of that range
I think you're misunderstanding the framework. The whole problem is that we can't assign a (non-arbitrary) "probability-weighted expectation". That's the motivation for representing with a range rather than a single expectation.
(ETA: By default I plan not to reply further.)
I address this objection here (Q3), if I understand what you're saying correctly. (I'd recommend first reading sec. 2.1 of the post for crucial background on the epistemology, though, as I noted in another comment.)
(In general, I think you should not expect this post to be a self-contained explanation of the argument by any means. It's a high-level summary.)
I'm not saying we have information that updates us in a particular direction about the bias. I'm saying we have information suggesting various different directions, and it's ambiguous what the update should be overall â which is fundamentally different from "no update". I strongly recommend reading sections 2.1 and 2.4 of this post, as well as 3.2.1 of this post, to understand the epistemology that's at play here.
(ETA: The final paragraphs of sec 4.1.1, linked right after the part you quoted, also discuss this point.)
(Edited for tone)
Sorry, I don't understand. The snippet I quoted â about acausal stuff and simulations â is what's at issue in this discussion.
Regardless, I'm still interested in where you object to my response to Extrapolation. Could you please say more on that?
they seem to argue more for "we're clueless about how much we should do ECL"?
I think they suggest that there's just a lot of subtlety in working out the implications of acausal decision theories in practice. Which is reason to expect more crucial considerations in this domain generally / reason to doubt your "by definition" argument.
but why should I expect their attempts to do so to backfire
Why should you expect them to be positive in expectation either? (The broader point of the unawareness sequence is that there's an ambiguous pile of positive and negative effects to weigh up.)
On the simulators, it just seems like its hard to think of possible simulator-motivations where us reaching good outcomes in the simulation would be bad for the base reality, and easy to think of ones where it would be neutral or good.
But then we're back to the Extrapolation argument, which you claimed you weren't committed to. I'm saying, even if the balance of effects we can think of looks good, we're looking at a super tiny sliver of the set of effects our fully aware selves would be weighing up â and it's a biased sample of such effects, so extrapolating from that sample is dubious.
Hmm, these arguments seem too anchored on what we happen to currently be aware of.
Hi Toby, glad it was helpful!Â
Fair question â the idea is:
I'll add a note on this to the post itself.