Beware boasting about non-existent forecasting track records

To help me understand, would you endorse that "he claims to be better than most Metaculus predictors"?

(That said, I agree that Yudkowsky's sneering in the absence of a specific track record is infuriating; I strong-upvoted this post.)

In particular I am irritated that Yudkowsky is criticizing metaculus forecasters when he literally doesn't even have a metaculus account, at least one he posts. He's pro-bets in theory, but then will asymmetrically criticize the people who make their prediction track record quantifiable and public. The reputational risk of making regular metaculus predictions would be a lot more psychologically and socially relevant to him than losing a thousand dollars, so the fact that he's not doing so says a lot to me.

You're right that that context makes it make more sense.  One might even say it sounds impressive! But it's a real shame he's avoiding the format that could make these things a non-corrupt, meaningful forecasting track record.

Can someone explain to me why we don't see people with differing complex views on something placing bets in a similar fashion more often? 

asking about a Metaculus forecast of the Metaculus forecast 3 years later, implicitly predicts that Metaculus will update again within 3 years. [emphasis mine]

I feel like this is missing the key claim underlying this post: that verbal statements making implicit predictions are too hard to judge and too easy to hindsight bias about, and so aren't strong evidence about a person's foresight.

For instance, if Metaculus, did not, in fact, update again over the upcoming 3 years, and you were merely optimizing for the appearance of accuracy, you could claim that you weren't making a prediction, merely voicing a question.  And more likely, you and everyone else would just have forgotten about this tweet.

I don't particularly want to take a stance on whether verbal forecasts like that one ought to be treated as part of one's forecasting record. But insofar as the author of this post clearly doesn't think they should be, this comment is not addressing his objection.

These sorts of observations sound promising for someone's potential as a forecaster.  But by themselves, they are massively easier to cherry-pick, fudge, omit, or re-define things, versus proper forecasts.

When you see other people make non-specific "predictions", how do you score them? How do you know the scoring that you're doing is coherent, and isn't rationalizing? How do you avoid the various pitfalls that Tetlock wrote about? How do you *ducks stern glance* score yourself on any of that, in a way that you'll know isn't rationalizing?

For emphasis, in this comment you reinforce that you consider it a successful advance prediction.  This gives very little information about your forecasting accuracy.  We don't even know what your actual distribution is, and it's a long time before this resolves, we only know it went in your direction.  I claim that to critique other people's proper-scored forecasts, you should be transparent and give your own.

EDIT: Pasted from another comment I wrote:

Instead of that actual [future resolution] reality, and because of how abruptly the community ended up shifting, Eliezer seems to be interpreting that to mean that his position about that reality is not extreme enough.  Those 2 things are somewhat related but pretty weakly, so it seems like rationalizing for him to frame it as showing his forecast isn't extreme enough.

My first 'dunk' on April 18, about a 5-year shortening of Metaculus timelines in response to evidence that didn't move me at all, asking about a Metaculus forecast of the Metaculus forecast 3 years later, implicitly predicts that Metaculus will update again within 3 years.

I do however claim it as a successful advance prediction, if something of a meta one

Wait, unless I misunderstand you there’s a reasoning mistake here. You request epistemic credit for predicting implicitly that the Metaculus median was going to drop by five years at some point in the next three years. But that’s a prediction that the majority of Metaculites would also have made and it’s a given that it was going to happen, in an interval of time as long as three years. It’s a correct advance prediction, if you did make it (let’s assume so and not get into inferring implicit past predictions with retrospective text analysis), but it’s not one that is even slightly impressive at all.

As an example to explain why, I predict (with 80% probability) that there will be a five-year shortening in the median on the general AI question at some point in the next three years. And I also predict (with 85% probability) that there will be a five-year lengthening at some point in the next three years.

I’m predicting both that Metaculus timelines will shorten and that they will lengthen! What gives? Well, I’m predicting volatility… Should I be given much epistemic credit if I later turned out to be right on both predictions? No, it’s very predictable and you don’t need to be a good forecaster to anticipate it. If you think you should get some credit for your prediction, I should get much more from these two predictions. But it’s not the case that I should get much, nor that you should.

Are there inconsistencies in the AGI questions on Metaculus? Within the forecast timeline, with other questions, with the resolution criteria? Yes, there are plenty! Metaculus is full of glaring inconsistencies. The median on one question will contradict the median on another. An AI question with stronger operationalization will have a lower median than a question with weaker operationalization. The current median says there is a four percent chance that AGI was already developed. The resolution criteria on a question will say it can’t resolve at the upper bound and the median will have 14% for it resolving at the upper bound anyway.

It’s commendable to notice these inconsistencies and right to downgrade your opinion of Metaculus because of them. But it’s wrong to conclude (even with weak confidence), because you can observe such glaring inconsistencies frequently, and predict in advance that specific ones will happen, including changes over time in the median that are predictable even in expected value after accounting for skew, that you are a better forecaster on even just AGI questions (and the implicit claim of being “a slightly better Bayesian” actually seems far stronger and more general than that) than most of the Metaculites forecasting on these questions.

Why? Because Metaculites know there are glaring inconsistencies everywhere, they identify them often, they know that there are more, and they can find them, and fix most of them, easily. It’s not that you’re a better forecaster, just that you have unreasonable expectations of a community of forecasters who are almost all effectively unpaid volunteers.

It’s not surprising that the Metaculus median will change over time in specific and predictable ways that are inconsistent with good Bayesianism. That doesn’t mean they’re that bad: let us see you do better, after all. It’s because people’s energy and interest are scarce. The questions in tournaments with money prizes get more engagement, as do questions about things that are currently in the news. There are still glaring inconsistencies in these questions, because it’s still not enough engagement to fix them all. (Also because the tools are expensive in time to use for making and checking your distributions.)

There are only 601 forecasters who have more than 1000 points on Metaculus: that means only 601 forecasters who have done even a pretty basic amount of forecasting. One of the two forecasters with exactly 1000 points has made predictions on only six questions, for example. You can do that in less than one hour, so it’s really not a lot.

If 601 sounds like a lot, there are thousands of questions on the site, each one with a wall of text describing the background and the resolution criteria. Predictions need updated constantly! The most active predictors on the site burn out because it takes so much time.

It’s not reasonable to expect not to see inconsistencies, predictable changes in the median, and so on. It’s not that they’re bad forecasters. Of course you can do better on one or a few specific questions, but that doesn’t mean much. If you want even just a small but worthwhile amount of evidence, from correct advance predictions, that you are a better forecaster than other Metaculites, you need, for example, to go and win a tournament. One of the tournaments with money prizes that many people are participating in.

Evaluating forecasting track records in practice is hard and very dependent on the scoring rule you use (rankings for PredictionBook vary a lot with your methodology for evaluating relative performance, for example). You need a lot of data, and high quality, to get significant evidence. If you have low-quality data, and only a little, you just aren’t going to get a useful amount of evidence.

This is actually a testable claim: that forecasts ends up trailing things that Eliezer said 10 years later.

Not really, unless you accept corruptible-formats of forecasts with lots of wiggle room.  It isn't true that we can have a clear view of how he is forecasting if he skips proper forecasting.

I think you're right that it's impressive he alerted people to potential AI risks.  But if you think that's an informative forecasting track record, I don't think that heuristic is remotely workable in measuring forecasters.

Doing a precise prediction when you don't have the information I feel like there's been a lot of misunderstanding about why Eliezer doesn't want to give timeline predictions, when he said it repeatedly: he thinks there is just not enough bits of evidence for making a precise prediction. There is enough evidence to be pessimistic, and realize we're running out of time, but I think he would see giving a precise year like a strong epistemic sin. Realize when you have very little evidence, instead of inventing some to make your forecast more concrete.

To clarify, I'm not saying he should give a specific year that he thinks it happens, like such a 50% confidence interval of 12 months.  That would be nuts.  Per Tetlock, it just isn't true that you can't (or shouldn't) give specific numbers when you are uncertainty.  You just give a wider distribution.  And not giving that unambiguous distribution when you're very uncertain just obfuscates, and is the real epistemic sin.

As for the financial pundit example, there's a massive disanalogy: it's easy to predict that there will be a crash. Everybody does it, we have past examples to generalize from, and models and theories accepted by a lot of people for why they might be inevitable. On the other hand, when Eliezer started talking about AI Risks and investing himself fully in them, nobody gave a shit about it or took it seriously. This was not an obvious prediction that everyone was making, and he gave far more details than just saying "AI Risks, man".

I don't understand what you mean by the bolded part.  What do you mean everybody does it? No they don't.  Some people pretend to, though.  The analogy is relevant in the sense that Eliezer should show that he is calibrated at predicting AI risks, rather than only arguing so.  The details you mention don't work as a proper forecasting track record.

There are further shards of a track record strewn across the internet:

• The bets registry [? · GW] shows two bets lost by Eliezer Yudkowsky, none won
• The public figure profile on Metaculus has no resolved predictions yet

That's good, but it doesn't really add much to a forecasting track record.  Doesn't meet the criteria.  I do think he would be good, if he did proper forecasting.  EDIT 10 days later: I would be happy to hear from the downvoters why they think that example tells us much, OR why it's anyone's job other than Eliezer to curate his predictions into something accountable (instead of the stuff he said to Paul for example.)

A couple questions:

1. It's quite easy and common to insult groups of people.  And me and some other people found him very sneering in that post.  In order to count as "calling them excruciatingly predictable", it seems like you're suggesting Eliezer would have had to be naming specific people, and that it doesn't count if it's about a group (people who had placed forecasts in that question)? If yes, why?
2. For that post that I described as fearmongering, it's unrelated whether his "intention" is fearmongering or not.  I would like if you elaborated.  The post has a starkly doomsday attitude.  We could just say it's an April Fool's joke, but the problem with this retort is Eliezer has said quite a few things with a similar attitude.  And in the section "addressing" whether it's an April Fool's joke he first suggests that it is, but then implies that he intends for the reader to take the message very seriously so not really.
   
   Roughly, the post seems to imply a chance of imminent extinction that is, like, a factor of ~100x higher (in odds format) than what scored aggregated forecasters roughly give.  Such an extreme prediction could indeed be described as fearmongering.
   
   In order to count as "fearmongering", are you saying he would've had to meet the requirement of being motivated specifically for fearmongering? Because that's what your last sentence suggests.

"Bad faith" seems a bit strong. People usually don't realise their realise their inconsistencies.

I don't like this defense for two reasons. One, I don't se why the same argument doesn't apply to the role Eliezer has already adopted as an early and insistent voice of concern. Being deliberately vague on some types of predictions doesn't change the fact that his name is synonymous with AI doomsaying. Second, we're talking about a person whose whole brand is built around intellectual transparency and reflection; if Eliezer's predictive model of AI development contains relevant deficiencies, I wish to believe that Eliezer's predictive model of AI development contains relevant deficiencies. I recognize the incentives may well be aligned against him here, but it's frustrating that he seems to want to be taken seriously on the topic but isn't obviously equally open to being rebutted in good faith.

If you're right, you will all be dead, so it won't matter

Posting a concrete forecast might motivate some people to switch into working on the problem, work harder on it, or reduce work that increases risk (e.g. capabilities work). This might then make the forecast less accurate, but that seems like a small price to pay vs everyone being dead. (And you could always update in response to people's response).

This isn't a good description of being on Metaculus versus being a Bayesian.

How does one measure if they are "being a Bayesian"? The general point is you can't, unless you are being scored.  You find out by making forecasts -- if you aren't updating you get fewer points, or even lose points.  Otherwise you have people who are just saying things that thematically sound Bayesian but don't mean very much in terms of updated believes.  Partly I'm making an epistemic claim that Eliezer can't actually know if he's being a good Bayesian, without proper forecasting.  You can check out Tetlock's work if you're unsure why that would be the case, though I mention it in the post.

The more central epistemic claim I'm making in this essay: if someone says they are doing a better job of forecasting a topic than other people, but they aren't actually placing forecasts so we could empirically test if they are, then that person's forecasts should be held in high suspicion.  I'm claiming this would be the same in every other domain, and AI timelines are unlikely to be that special, and his eminence doesn't really buy a good justification why we would hold him to drastically lower standards about measuring his forecast accuracy.

I'm fond of "x percent of sun's energy used"-syle stuff because I would expect runaway superintelligence to probably go ahead and use that energy, and it has a decent shot at being resolvable.

But I think we need to be careful about assuming all the crazy-ambitious milestones end up only a few months from each other.  You could have a situation where cosmic industrialization is explosively fast heading away from Earth, with every incentive to send out seed ships for a land-grab.  But it's plausible that could be going on despite here on Earth it's much slower, if there are some big incumbents that maintain control and develop more slowly.  I'm not super sure that'll happen but it's not obvious that all the big milestones happen within a few months of each other, if we assume local control is maintained and the runaway Foom goes elsewhere.

This is an example of why I think it does matter what milestone people pick, but it will often be for reasons that are very hard to foresee.

I like your list!

Definitely agree that narrow questions can lose the spirit of it.  The forecasting community can hedge against this by having a variety of questions that try to get at it from "different angles".

For example, that person in 1970 could set up a basket of questions:

1. Percent of GDP that would be computing-related instead of rocket-related.
2. Growth in the largest computer by computational power, versus the growth in the longest distance traveled by rocket, etc.
3. Growth in the number of people who had flown in a rocket, versus the number of people who own computers.
4. Changes in dollars per kilo of cargo hauled into space, versus changes in FLOPS-per-dollar.

Of course, I understand completely if people in 1970 didn't know about Tetlock's modern work.  But for big important questions, today, I don't see why we shouldn't just use modern proper forecasting technique.  Admittedly it is laborious! People have been struggling to write good AI timeline questions for years.

It tells us essentially nothing.  How are you going to score the degree to which it turned out to be "a sign of real progress towards AGI"? I understand it feels impressive but it's far too nebulous to work as a forecasting track record.

I think this is an unreasonable characterization of the situation and my position, especially the claim:

Eliezer hasn't seen a big list of prediction successes from Paul about this thing Paul claims to be unusually good at (whereas, again, EY makes no claim of being unusually good at timing arbitrary narrow-AI advances)

I responded to a long thread of Eliezer trash-talking me in particular (here [? · GW]), including making apparent claims about how this is not the kind of methodology that makes good forecasts. He writes:

It just seems very clear to me that the sort of person who is taken in by this essay is the same sort of person who gets taken in by Hanson's arguments in 2008 and gets caught flatfooted by AlphaGo and GPT-3 and AlphaFold 2 [... the kind of person who is] going "Huh?" when AlphaGo or GPT-3 debuts^[1]

He also writes posts like this one [LW · GW]. Saying "the trick that never works" sure seems like it's making a claim that something has a worse track record than whatever Eliezer is doing.

Overall it looks to me that Eliezer is saying, not once but many times, that he is better at predicting things than other people and that this should be taken as a reason to dismiss various kinds of argument.

I'm not claiming to be exceptional at making predictions. I'm claiming that Eliezer is mediocre at it and overconfident about it.

I'm glad we were able to make one bet, which will give one single bit of evidence for Eliezer's position if he wins and a a measly 1/8th of a bit against if he loses. But I felt that Eliezer was unwilling to state almost any concrete predictions about anything (even one that was just "Paul is overconfident about X"). In light of that, I think Eliezer probably shouldn't be ragging so hard on how other people are "caught flatfooted" (in contrast with his superior intuition).

If you want to say "X doesn't work for forecasting" (and have it actually mean something rather than being mood affiliation) I think you basically need to finish the sentence by saying "...as well as Y". And if you want anyone to take that seriously you should be willing to stick your neck out on some X vs Y comparisons rather than just saying "how about the proponents of X go make some forecasts that I will cherry-pick and deride later."

1. ^{^}

   This is particularly frustrating to me because in 2013 I already expected beating the best human go players in the next few years based on the trend extrapolation in this document. As far as I know Eliezer appears to have had a smaller probability on human-level go performance soon (believing it would require some new insight instead of just extrapolating the curve out to expert performance in 2017-2018), and to have been more confident that the match would be either 0-5 or 5-0.
   
   Likewise, I'm pretty confident that I had a higher probability on GPT-3 than Eliezer did. All of his public statements about language modeling suggests skepticism for getting GPT-3 like competencies at this point in the tech tree or producing it by stacking more layers, whereas in internal OpenAI discussions I was giving 25%+ probabilities for LM scaling working this well (admittedly not as high as some other even truer believers in stack more layers).
   
   I'm not presenting these as explicit predictions that should be particularly convincing to others. But I do hope it explains why I disagree with Eliezer's implications, and at least makes it plausible that his track record claim is backwards.

Elizabeth van Nostrand comments in private chat:

Can everyone agree that:

1. there are many forms of prediction, of which narrow, precise forecasting of the kind found on prediction markets is only one
2. narrow forecasting is only viable for a small subset of problems, and often the most important problems aren’t amenable to narrow forecasting
3. narrow forecasting is much harder to fake than the other kinds. Making vague predictions and taking credit for whatever happens to happen is a misallocation of truthseeking credit.
4. It is possible to have valuable models without being good at narrow predictions- black swans is a useful concept but it’s very annoying how the media give Nassim Taleb credit everytime something unexpected happens.
5. It is possible to have models that are true but not narrow-predictive enough to be valuable [added: you can have a strong, correct model that a stock is overpriced, but unless you have a model for when it will correct it’s ~impossible to make money off that information]

? 

I like this addition, and endorse 1-5!

But still without being transparent about his own forecasts, preventing a fair comparison.

I think it's a fair comparison, in that we can do at least a weak subjective-Bayesian update on the information -- it's useful and not cherry-picked, at least insofar as we can compare the AGI/TAI construct Eliezer was talking about in December, to the things Metaculus is making predictions about.

I agree that it's way harder to do a Bayesian update on data points like 'EY predicted AGI well before 2050, then Metaculus updated from 2052 to 2035' when we don't have a full EY probability distribution over years.

I mostly just respond by making a smaller subjective update and then going on with my day, rather than treating this as revelatory. I'm better off with the information in hand, but it's a very small update in the grand scheme of things. Almost all of my knowledge is built out of small updates in the first place, rather than huge revelatory ones.

If I understand your views, Jotto, three big claims you're making are:

1. It's rude to be as harsh to other futurists as Eliezer was toward Metaculus, and if you're going to be that harsh then at minimum you should clearly be sticking your neck out as much as the people you're criticizing. (Analogy: it would be rude, and harmful to pro-quantified-forecasting norms, to loudly criticize Matt Yglesias for having an off year without at minimum having made a similar number of similarly risky, easy-to-resolve public predictions.)
2. Metaculus-style forecasting is the gold standard for reasoning about the physical world, and is the only game in town when it comes to 'remotely reasonable methods to try to predict anything about future technology'. Specifically:
   • Anyone who claims to know anything relevant to the future should have an account on Metaculus (or a similar site), and people should overwhelmingly base their beliefs about the future on (a) what Metaculus says, and (b) what the people with the highest Metaculus scores say...
   • ... rather than basing their beliefs on their own inside-view models of anything, personal attempts to do explicit quantified Bayesian updates in response to not-fully-quantitative data (e.g., 'how surprised would my gut be if something like CYC turned out to be more important than ML to future AI progress, a la Hanson's claims? in how many worlds do I expect to see that, compared to worlds where I don't see it?') , or attempts to shift their implicit strength of belief about things without routing through explicit Bayesian calculations.
3. If you aren't a top Metaculus forecaster and aren't just repeating the current Metaculus consensus using the reasoning 'X is my belief state because Metaculus thinks it', then you should shut up rather than poisoning the epistemic commons with your unvalidated inside-view models, hard-to-quickly-quantitatively-evaluate claims about reality, etc.

(Correct me if I'm misstating any of your views.)

I don't have a strong view on whether folks should be friendlier/nicer in general -- there are obvious benefits to letting people be blunt, but also obvious costs. Seems hard to resolve. I think it's healthy that the EA Forum and LW have chosen different tradeoff points here, so we can test the effects of different norms and attract people who favor different tradeoffs. (Though I think there should be more 'cultural exchange' between the EA Forum and LW.)

The more specific question 'has Eliezer stuck his neck out enough?' seems to me to turn on 2. Likewise, 3 depends on the truth of 2.

I think 2 is false -- Metaculus strikes me as a good tool to have in the toolbox, and a really cool resource overall, but I don't see it as a replacement for inside-view reasoning, building your own models of the world, or doing implicit updating and intuition-honing.

Nor do I think that only the top n% of EAs or rationalists should try to do their own model-building like this; I think nearly every EA and every rationalist should do it, just trying to guard against the obvious pitfalls -- and learning via experience, to some degree, where those pitfalls tend to be for them personally.

Quoting another recent thing I wrote on Twitter:

At the borderlands of EA and non-EA, I find that the main argument I tend to want to cite is Bayes:

'Yep, A seems possible. But if not-A were true instead, what would you expect to see differently? How well does not-A retrodict the data, compared to A?'

And relatedly, 'What are the future predictions of A versus not-A, and how soon can we get data that provides nontrivial evidence for one side versus the other?' But that's a more standard part of the non-EA college-educated person's toolbox.

And there's a sense in which almost all of the cognitive resources available to a human look like retrodiction, rather than prediction.

If you hear a new Q and only trust your pre-registered predictions, then that means your whole lifetime of past knowledge is useless to you.

We have in fact adopted the norm "give disproportionate weight to explicit written-down predictions", to guard against hindsight bias and lying.

But it's still the case that almost all the cognitive work is being done at any time by "how does this fit my past experience?".

I guess there's another, subtler reason we give extra weight to predictions: there's a social norm against acknowledging gaps in individual ability.

If you only discuss observables and objective facts, never priors, then it's easier to just-not-talk-about individuals' judgment.

Whatever the rationale, it's essential that we in fact get better at retrodiction (i.e., reasoning about the things we already know), because we can't do without it. We need to be able to talk about our knowledge, and we need deliberate practice at manipulating it.

The big mistake isn't "give more weight to pre-registered predictions"; it's "... and then make it taboo to say that you're basing any conclusions on anything else".

Predictions are the gold standard, but man cannot live on gold alone.

To explain more of my view, here's a thing I wrote in response to some Qs on the 18th:

I think there are two different topics here:

1. Should we talk a bunch publicly about the fastest path to AGI?

2. To what extent should we try to explicate and quantify our *other* predictions, and publish those predictions?

I think the answer to 1 is an obvious "no".

But 'what is your AGI timeline?', 'when do you expect a Gato-like thing to be developed?', etc. seems basically fine to me, because it doesn't say much about how you expect AGI to be developed. (Especially if your timeline is long.)

The Metaculus folks criticizing EY for saying 'Metaculus updated toward my view' apparently didn't realize that he did make a public prediction proving this: (link)

He didn't make a Gato-specific public prediction, but it's also not apparent to me that EY's making a strong claim like 'I predicted a system exactly like Gato would be built exactly now'; he's just saying it's the broad sort of thing his intuitive models of AI progress allow.

Translating an intuitive, unstable, preverbal sense of 'which events are likelier to happen when?' into a bunch of quantified predictions, without falling victim to issues like framing and salience effects, seems pretty hard to me.

EY is on the record as saying that it's hard to get much mileage out of thinking about timelines, and that it's even harder if you try to switch away from your brain's native format for representing the probabilities (emotional surprise, concrete anticipations, etc.).

I could easily imagine that there's some individual variation about how people best do tech forecasting, and I also think it's reasonable for folks to disagree about the best norms here. So, I think 2 is a more complicated Q than 1, and I don't have a strong view on it. [...]

"I don't have the same inside-view models as you, and you haven't given me an explicit argument to convince me, so I don't believe you" is a good and normal response here.

In most of the world this reads as kind of offensive, or as an affront, or as inciting conflict, which makes having this thought in the first place hard, which is one of the contributors to modest epistemology.

I wish that we had better social norms for distinguishing between 

1. Claims that I am making and justifying based on legible info and reasoning. ie "Not only do I think that X is true, I think that any right thinking person who examines the evidence should come to conclude X," and if you disagree with me about that we should debate it.
2. Claims that I am making based on my own private or illegible info and reasoning. ie "Given my own read of the evidence, I happen to think X. But I don't think that the arguments that I've offered are necessarily sufficient to convince a third party." I'm not claiming that you should believe this, I'm merely providing you the true information that I believe it.

I think clearly making this distinction would be helpful for giving space for people to think. I think lots of folks implicitly feel like they can't have an opinion about something unless it is of the first type, which means they have to be prepared to defend their view from attack. 

Accordingly, they have a very high bar for letting themselves believe something, or at least to say it out loud. Which, at least, impoverishes the discourse, but might also hobble their own internal ability to reason about the world.

On the flip side, I think sometimes people in our community come off as arrogant, because they're making claims of the second type, and others assume that they're making claims of the second type, without providing much supporting argument at all.

(And sometimes, folks around here DO make claims of the first type, without providing supporting arguments. eg "I was convinced by the empty string, I don't know strange inputs others need to be convinced" implying "I think all right thinking people would reach this conclusion, but none of you are right thinking.")

First I commend the effort you're putting into responding to me, and I probably can't reciprocate as much.

But here is a major point I suspect you are misunderstanding:

It seems like you're interpreting EY as claiming 'I have a crystal ball that gives me unique power to precisely time AGI', whereas I interpret EY as saying that one particular Metaculus estimate is wrong.

This is neither necessary for my argument, nor at any point have I thought he's saying he can "precisely time AGI".

If he thought it was going to happen earlier than the community, it would be easy to show an example distribution of his, without high precision (nor much effort).  Literally just add a distribution into the box on the question page, click and drag the sliders so it's somewhere that seems reasonable to him, and submit it.  He could then screenshot it.  Even just copypasting the confidence interval figures.

Note that this doesn't mean making the date range very narrow (confident), that's unrelated.  He can still be quite uncertain about specific times.  Here's an example of me somewhat disagreeing with the community.  Of course now the community has updated to earlier, but he can still do these things, and should.  Doesn't even need to be screenshotted really, just posting it in the Metaculus thread works.

And further, this point you make here:

Eliezer hasn't said he thinks he can do better than Metaculus on arbitrary questions. He's just said he thinks Metaculus is wrong on one specific question.

My argument doesn't need him to necessarily be better at "arbitrary questions".  If Eliezer believes Metaculus is wrong on one specific question, he can trivially show a better answer.  If he does this on a few questions and it gets properly scored, that's a track record.

You mentioned other things, such as how much it would transfer to broader, longer-term questions.  That isn't known and I can't stay up late typing about this, but at the very minimum people can demonstrate they are calibrated, even if you believe there is zero knowledge transfer from narrower/shorter questions to broader/longer ones.

Going to have to stop it there for today, but I would end this comment with a feeling: it feels like I'm mostly debating people who think they can predict when Tetlock's findings don't apply, and so reliably that it's unnecessary to forecast properly nor transparently, and it seems like they don't understand.

Upvoted -- I agree that that bet they made should be included in the post, around when I'm mentioning how Eliezer told Paul he doesn't have "a track record like this".  He did decline to bet Paul in that comment I am quoting, claiming Paul "didn't need to bet him".  But you are right that it's wrong not to include the bet they do have going, and not just the one with Bryan Caplan.  I've made some edits to include it.

Ah by the way, I think the link you posted accidentally links to this post.

You're absolutely right, that bet with Bryan gives very little information! Definitely doesn't compare at all to a proper track record of many questions.

I think your explanation for his behavior is good.  I don't think it's justified, or at least, I am deeply suspicious of him thinking anything thematically similar to "I have to obfuscate my forecasting competence, for the good of the world, but I'll still tell people I'm good at it".  The more likely prior is just that people don't want to lose influence/prestige.  It's like a Nobel laureate making predictions, and then not seeming so special after.

Giving precise forecasts would give people who are invested in AI progress a chance to dunk on him and undermine his credibility by being able to point out precisely when and how he was wrong, while neglecting the gigantic consequences if they themselves are wrong about the consequences of continued AI capabilities research. Until the incentives he faces chance, I expect his behavior to remain roughly the same.

But then anyone who makes a precise bet could lose out in the same way. I assume you don't believe that getting in general is wrong, so where does the asymmetry come from? Yudkowsky is excused betting because he's actually right?

That might be possible, but it would take a lot of effort to make resolvable.  Who is "similar to Eliezer", and how do we define that in advance? Which forecasting questions are we going to check their Brier score on? Which not-like-Eliezer forecasters are we going to compare them to (since scores are much more informative for ranking forecasters, than in isolation)? Etc.  I'd rather people like Eliezer just placed their forecasts properly!