Max Kaye

Karma: 35

Max Kaye 4 Apr 2026 23:46 UTC
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in reply to: Myron Hedderson’s comment on: Is Bayesianism Susceptible to the Mail-Order Prophet Scam?
Heh, I know what you mean.

I’d suggest picking something you think we disagree about to focus on if we want to make some progress (helps keep discussion tree width small). But you’re also welcome to write down your thoughts with less structure—I’m still interested in that and I get that it can be easier sometimes. If you do, it might be good to, at the end, point out what you think the strongest or most important point / disagreement is, and I’ll focus on that and/or suggest something of my own.

FWIW, I’m already familiar-in-passing with more modern retreats from like hardcore bayesianism. IMO it’s a bit unprincipled but necessary because bayesianism isn’t complete (eg hypothesis generation, evidence modelling, etc). One thing I don’t like about the state of bayesianism is everyone seems to have their pet theory about how to handle the problems. IMO this is a sign that bayesianism is failing (but doesn’t mean it’s irredeemable). If b-ism weren’t failing, we’d know of a more consistent integrated position that people point to and say ‘see X’s book/essays for the gold standard’.

If there is one thing in particularly that I take issue with, it’s the idea that Bayesianism is the logic of science. I disagree with that wholeheartedly. The problem is the leap from applying a statistics method epistemologically. Bayes has no epistemic insights that aren’t covered elsewhere, and the domains where it works aren’t useful for getting to the truth and understanding the world proper. It doesn’t help us to explain how and why scientific progress happens and is possible.

Edit/Addendum: to (loosely and reductively) analogize to pythagoras: bayesianism is to bayes what pyramid power is to pythagoras.

This isn’t exactly a fair analogy, but the point I want to make is that the belief that bayes’ theorem applies to epistemological matters is a massive leap. I can see how it’s tempting and it’s much easier to see how intelligent people would fall into the trap. I don’t mean to be insulting or offensive btw, and I’m sorry if I am, but I don’t want to lie about what I think and am a little short on time.

Max Kaye 4 Apr 2026 23:32 UTC
−1 points
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in reply to: JBlack’s comment on: Is Bayesianism Susceptible to the Mail-Order Prophet Scam?
I agree with lots of what you said, but, to focus:

The main point is that we don’t know anything better, and pretty much everything else that we do know looks worse.

This, I think, is wrong. Not a little bit wrong, but outright wrong, and has been wrong for decades. If you want to believe and repeat this, I can provide some standards I think you should meet before being so confident. I think you should stop claiming it (unless you can answer about why other contenders are wrong, which would be big news philosophically if you could).

That’s a big claim on my part, so I will make a point and then give you some alternatives:

Claim: There is no one who can put forward a specific, integrated version of Bayesianism that will: take responsibility for defending it, put the best and strongest arguments forward, and debate with any philosopher who disagrees.

(Integrated here means it comes with all necessary parts for it to work; e.g., if one needs a model for hypothesis generation, then at the very least there are known fleshed out ways of doing that. Also, debates don’t need to happen twice, we can simply point to an argument made in the ongoing (academic and non-academic) literature and check whether the argument is resolved or not.)

Alternatives:
1. Critical Rationalism (Karl Popper). CR gave us the basis of modern science (last 100yrs or so) so should be taken as a serious option. Popper tried to engage with bayesians and inductivists but some of his criticisms never received answers.
2. Critical Fallibilism (Elliot Temple). CF is descended from CR and some other philosophies. It has original and important contributions from Elliot which solve some problems with CR, like eliminating credences completely (Popper tried and failed to get rid of ‘strong’ and ‘weak’ arguments fully, which is one of CF’s criticisms of CR).
Elliot has been critical of LessWrong for a decade plus FWIW and even though points like the one I made above (not original to me) have been brought up to LW for years, there is little-to-no engagement.

Max Kaye 3 Apr 2026 16:19 UTC
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in reply to: ChristianKl’s comment on: Is Bayesianism Susceptible to the Mail-Order Prophet Scam?

You seem to have some idea that epistemology is supposed to be “objective”. It’s supposed to give you the answer from God’s view.

Objective in a sense, but I’m not sure how I’ve given you the ‘God’s view’ impression. I think epistemology should be objective in that it should work universally via the same rules, and that people can discuss both ideas and the world (evidence) in such a way to reach agreement in an objective sense. But they can be wrong, there’s no infallible method of getting to the truth. They can also objectively agree on each other’s subjective states.

The reason to bother with Bayesianism is not because it helps you to see the world from God’s view but because it has practical utility in applied epistemology with FDA drug approval and Superforcasting being two examples.

Putting aside superforecasting because I don’t know much about it, using bayesian statistics for statistical analysis is fine.

But that’s not what’s happening on LW. When people on LW talk about their priors and updating them, they’re not talking about bayesian statistics, they’re talking about epistemology, about what ideas are true. I think those are fundamentally different things and they work in different ways (and it seems like you do, too). I’m here because LW is the largest bayesian forum (or if not the largest it’s better than reddit for discussion, point is, it’s the best option for talking to bayesians).

The idea that we should apply bayesian statistics to epistemic tasks is what I’m interested in discussing.

If superforecasting is important to discuss, can you link me to something that represents what you mean by it?

Max Kaye 3 Apr 2026 15:54 UTC
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in reply to: Richard_Kennaway’s comment on: Is Bayesianism Susceptible to the Mail-Order Prophet Scam?

I don’t think P(my epistemology) is a practically useful concept.

This is surprising to me—I’ve always thought that whatever our understanding of knowledge was should apply to itself. If it doesn’t, how do you know that your epistemology is right? An epistemology is the thing that’s meant to give you the answer to the question. So it seems like a problem if an epistemology can’t apply to itself.

One response might be ‘Bayesianism is about science, not philosophy’, but then on what basis are you adopting bayesianism? if that decision is supported by some other epistemology, then why not use that instead? (it seems like it might be more powerful because it can do something bayesianism can’t)

Does critical fallibilism have anything to say about itself? If it gives itself a full bill of health, that’s no more useful than the statement “This sentence is true”, which can consistently be assigned any truth value.

Yeah it does, though a ‘full bill of health’ might mean something different. CF says that we should use the best ideas we have access to. “Best” means that it works to achieve a goal and is unrefuted (no unanswered decisive criticisms). CF claims it has no decisive criticisms (at least insofar as the epistemology is concerned), but does not claim such criticisms are impossible (it’s fallibilist after all). CF is Elliot Temple’s school and he is very willing to debate (which means a forum discussion).

From Debate Policies Introduction, he says:

Debate is important because it enables errors to be corrected. If an intellectual is wrong, and a critic has an important correction, then refusing to debate is one of the common ways the intellectual can stay wrong.

One of goals of CF-ists is to find and debate people who disagree with you because that’s the best way to get criticisms, which are an integral part of error correction and improvement.

But also the world isn’t very good for debate, at least not at a high level. It’s hard to find people and forums who will continue a discussion to it’s conclusion. So maybe CF isn’t as good as it could be if there was more debate.

If someone knew of a criticism of CF, then Elliot would want to know. If he disagreed, he’d want a public discussion about it.

I can expand on anything if you have questions.

Max Kaye 2 Apr 2026 15:09 UTC
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in reply to: ChristianKl’s comment on: Is Bayesianism Susceptible to the Mail-Order Prophet Scam?
Are you responding to this? (which I said above)

why bother with Bayesianism at all?

If so, I think we might be talking cross-purposes. I’m asking about bayesian epistemology particularly, not statistics. (Nor about estimations based on other people’s beliefs since that doesn’t seem like an epistemology except maybe JTB with more steps)

If not, I’m not sure what your point is particularly.

Sorry for the delayed replay. My comments are being held for review.

Max Kaye 2 Apr 2026 14:59 UTC
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in reply to: Myron Hedderson’s comment on: Is Bayesianism Susceptible to the Mail-Order Prophet Scam?
Isn’t this just solved with priors about you making a mistake? If you arrive at 1=2 or some other contradiction, it makes sense that such a prior would increase which in turn updates priors about whether the next action should be error checking, etc.

Even if I’m wrong about the bayesian way to handle this kind of case, this kind of thing doesn’t feel generally or broadly incompatible with bayesianism.

An idealized Bayesian reasoner could reason perfectly every time and be certain that they had done so, [...]

For what it’s worth, I think an epistemology needs to work in the real world—a noisy, dirty, perplexing place—in part because it is used by fallible people! If an epistemology is only reliable by invoking a perfect oracle or deduction engine or the like, then I think the argument is an admission that the epistemology can’t do error correction, in which case the epistemology would be incomplete at best and broken at worst.

Sorry for the delayed replay. My comments are being held for review.

Max Kaye 2 Apr 2026 4:09 UTC
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in reply to: JBlack’s comment on: Is Bayesianism Susceptible to the Mail-Order Prophet Scam?
So if we’re not ideal bayesian reasoners, how do we make progress? It seems like things need to come from outside bayesianism somehow. Or is it just a lottery that we can’t ever do better at except by having more people actively do bayesian reasoning about stuff? If there is something outside bayesian reasoning/epistemology and new ideas come from there, then it seems like it does things bayesianism does not, or is better at it. And such a thing would either contradict bayesianism at worst or make it (partially) obsolete at best.

Sorry for the delayed replay. My comments are being held for review.

Max Kaye 2 Apr 2026 3:54 UTC
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in reply to: Alex A’s comment on: Is Bayesianism Susceptible to the Mail-Order Prophet Scam?

If we were to keep experimenting and observing, we would find some data that would have essentially 0 likelihood showing up under .

I’m not sure this is true in general. Sometimes we only figure out what data to look for to disprove theory 1 after someone comes up with theory 2. So before that, a bayesian might be gathering lots of data and updating theory 1′s prior towards P=1, but they’d be being mislead with no way to know they were being mislead. But also, where does theory 2 come from? Either it was something the bayesian could have thought up themselves (in which case why were they updating in the wrong direction?), or bayesianism is incomplete and theory 2 was generated in a non-bayesian way (and in this case it’s hard to see bayesianism as anything but inferior to this other method; at the very least the sum of both methods is definitely better than bayesianism alone).

(Granted, if there are other hypotheses within that line up with reality, then you should split those out as well.)

There are an infinite number of those, though. Putting that aside, there are other mathematical constructions distinct from GR that are in , but we don’t know what they are yet (just like GR prior to publication).

And it seems like in order to split sensibly we’d need to know the distribution of probabilities over these unknown hypotheses in the hypothesis space. If we used a rule like always split in half, then our result is dependent on which order we learn the theories in (which seems illogical).

Then you can compare which specific predictions makes that does not.

But UG_other makes all possible predictions (since it’s a group of many hypotheses). Or close to ‘all’, at least.

Any hypotheses in that inconsistent under that new data also get ruled out, effectively increasing the probability assigned to .

Oh and I think I just saw an issue with your original reasoning:

When new evidence comes in that falsifies NMP, P(O) jumps up to 0.5.

The evidence that falsified NMP also falsified some hypotheses of O (but not GR). So would not be 0.5.

Sorry for the delayed replay. My comments are being held for review.

Max Kaye 2 Apr 2026 3:34 UTC
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in reply to: Myron Hedderson’s comment on: Is Bayesianism Susceptible to the Mail-Order Prophet Scam?
Doesn’t that mean we should expect that Bayesians often disagree and they have no way to resolve it except consulting reality (i.e., an experiment)?

Short answer: Yes.

Okay.

FWIW, CF says that two people should be able to use discussion to resolve most disagreements. Some disagreements do require experiments, but only when we have multiple contradictory theories that otherwise agree. (e.g., UG and GR mostly agree so it’s reasonable that two scientists might disagree on which is correct but they should be able to agree on a decisive experiment.) When such discussions fail there are ways to deal with that, too (so you can go address the reason for failure then resume the original discussion).

[...] that is, if one reasoner (A)‘s prior probability that (for example) General Relativity is true was high, while another (B)’s was low, then when an experiment is run which provides evidence for general relativity, A’s estimates of General Relativity’s likelihood of being true will change less than B’s (because B’s priors were more wrong) [...]

Doesn’t that require some assumptions about their hypothesis spaces? You assume that B’s priors are more wrong, but we don’t know that from just saying that ^[1] . We need to know about all their other priors, too.

I agree the update can be predictable to one another if they specify and communicate the necessary constants / weightings / etc. re specification and communication: For something that seems important to bayesians I’m surprised that I don’t see more of that.

As they see more and more of the same evidence, their models of the world should converge.

I’m not convinced of this but I agree it seems that intuitively, most of the time at least, they should.

This is all assuming an ideal Bayesian reasoner with practically-unlimited computing power who doesn’t cheat or decide not to reason according to Bayesian rules when it becomes inconvenient.

This surprised me to read and I have some immediate questions.
- When is Bayesian reasoning inconvenient?
- Do you think there’s other valid ways to reason?
  - If so, why do we need bayesianism? Is Bayesianism incomplete?
  - Or if not, how would an ideal Bayesian reasoner ever be fooled into using bad/broken/misleading methods of reasoning?
- Are there other more energy efficient ways of reasoning to get to the same answers reliably? Why use bayesianism at all in that case?
- Is cheating ever consistent with bayesianism?
Which is (one reason) why bother with Bayesianism at all. It’s a method of approaching consensus when working under uncertainty.

Sure, but so is “do whatever Max says”. Consensus on its own has nothing to do with truth. Now, I guess you mean something a little more specific but I don’t want to put words in your mouth.

Here’s an example of how Bayesianism fails to produce consensus (or it seems like that to me):

Two aliens (A1, A2) who do not know about relativity are communicating. A1 observes an event E1 happens before E2, but A2 observes E2 before E1. They will each update in different directions.

Is there a Bayesian way to resolve this?

[...] if you’re not very confident, [...]

How does Bayesianism deal with confidence? Do all priors have errors attached? If so, how are errors handled in the maths?

Also, if the error bars are large enough, is convergence still guaranteed? Or what if our errors are off due to things like overconfidence?

[...] you can argue over whether b% likelihood is reasonable [...]

I’m not sure how this would help Bayesians, what does a successful discussion of this kind look like?

The reason I’m not sure is unanswered questions like what are they observing to cause updates? and which priors are being updated?

Sorry for the delayed replay. My comments are being held for review.
1. ↩︎
  even if we assume GR is absolutely 100% correct, and IRL we know that GR isn’t 100% correct.

Max Kaye 2 Apr 2026 2:41 UTC
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in reply to: ChristianKl’s comment on: Is Bayesianism Susceptible to the Mail-Order Prophet Scam?
[Unsure] The probability of GR being true is independent of whether the Bayesian knows about it or not

In Bayesanism probabilities are not independent of the model of the observer the same way that frequentism has a notion of observer independent probabilities.

Sure, but that’s not exactly what I’m asking about.

From your perspective, you have a prior P(bayesianism). I’ll call this P(B) for short. There’s also some prior P(not bayesianism) that covers all other epistemologies, both those which you know about and those you do not. Does P(B) change:
- when you learn of other epistemologies? (I think this breaks up a bayesian’s hypothesis space but there’s no new data)
- when you learn about other epistemologies? (Like details about how they work)
- when you learn that you had an obstructive misunderstanding about other epistemologies? (Like, you thought it worked like X but actually it was Y)
- other events?
You can replace P(B) with P(GR) if you like and ‘epistemologies’ with ‘theories of gravity’. The underlying thing I’m unsure about is where the update to the prior happens and why. If it is when you learn about the new theory, then it seems like an admission that the P(other) option is just outright wrong, so working backwards I guess bayesianism stays consistent by not updating the prior in response to learning a new idea.

Sorry for the delayed replay. My comments are being held for review.

Max Kaye 2 Apr 2026 2:20 UTC
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in reply to: Myron Hedderson’s comment on: Is Bayesianism Susceptible to the Mail-Order Prophet Scam?

I haven’t read about CF (I skimmed your link extremely rapidly, which doesn’t count) but it sounds pretty binary. Bayesian thinking is not that.

re: binary. Yes… well you could argue that technically it’s ternary in that ‘unsure’ is an option, but CF says there’s always a way to get from ‘unsure’ to yes/no.

It’s similar to critical rationalism (CR) but removes all degrees for beliefs. CR was already pretty light on degrees/credence/weights (pun not intended), CF removes them entirely. CF also integrates some ideas from other schools (so it’s not a pure descendant of CR).

Bayesianism says that if you have strong priors about a particular matter, you should be surprised with corresponding strength if something your priors said shouldn’t happen, happens.

What kind of event would cause you to update your prior about bayesianism?

Does bayesianism say anything about things that cannot be observed directly?

e.g., many moral arguments are about what is right/wrong to do, and we often don’t see consequences, and even if we do see consequences, those aren’t outputs of an experiment in the same way science experiments work. So it’s not clear to me that (from bayesian pov) we even should use our observations about the world to update our ideas about morality.

(note: we don’t need to focus on morality particularly, it was just an example I thought we’d both agree involves things we can’t observe directly)

Sorry for the delayed replay. My comments are being held for review.

Max Kaye 2 Apr 2026 2:03 UTC
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in reply to: MichaelDickens’s comment on: Is Bayesianism Susceptible to the Mail-Order Prophet Scam?
I think I understand why frequentist-ism is clearly separated from bayesianism broadly speaking, but it also seems to me that in the absence of anything better, taking a frequency is not a bad way to get a starting point.

Is that common/accepted as part of bayesianism? Because if it’s not, I don’t know where priors would come from besides random allocation or evenly split between all hypotheses (which is problematic because there are many).

Sorry for the delayed replay. My comments are being held for review.

Max Kaye 2 Apr 2026 1:58 UTC
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in reply to: Cole Wyeth’s comment on: Is Bayesianism Susceptible to the Mail-Order Prophet Scam?

Arguably, using Bayesianism to evaluate schools of epistemology (which may not be Bayesian) is a type error.

If it’s a type error is that because bayesianism’s domain does not extend to all knowledge?

If bayesianism doesn’t cover all knowledge that would make it an incomplete epistemology. This is problematic for a few reasons (so I’m not sure this is what you mean); one is that it becomes unreliable for any knowledge because it cannot tell you what you are missing or how that missing part is involved in meaningful judgements.

If bayesianism does cover all knowledge than either epistemology (and bayesianism) seemingly doesn’t count as knowledge or we have a contradiction.

Or maybe I’m misunderstanding what you mean?

Personally, I’ve long thought that an epistemology should be able to evaluate itself (and other epistemic schools/ideas). This belief was quite formative for me and is one reason that I gravitated to fallibilism (broadly) since it seemed like any ‘true’ theory of epistemology would have this quality.

While I’m asking this to demonstrate that bad priors and naivety are the default state, I’m also genuinely interested in the answer.

It’s not quite clear to me what you’re getting at.

All bayesian answers to the original question (that I’ve seen in this thread) assume the bayesian already has good priors and isn’t naive. But that isn’t how we find ourselves in the world. We start from bad priors (random or worse) and naivety. So, while I agree real-world bayesians can avoid being scammed, I am not sure that bayesianism avoids it since the way of avoiding it is to have already obtained the knowledge you need to avoid it. I’m trying to see if there’s something more fundamental. That real-world bayesians don’t get scammed isn’t really a surprise, one doesn’t need a correct understanding of epistemology to reason about the world—e.g., we were able to do science and make progress before we understood science—but if we are concerned about whether bayesianism is correct or not, then it does matter.

I’m interested in how these kinds of issues (novel unintuitive systems) are dealt with when one doesn’t have obvious crutches like a known good state to start from.

The reason for asking about using Bayesianism to evaluate schools of epistemology is because epistemology is notoriously hard to make progress in. I was hoping that the idea we start with bad priors and naivety was more obvious in this context.

Hope that helps explain what I’m getting at.

Sorry for the delayed replay. My comments are being held for review.

Max Kaye 2 Apr 2026 1:34 UTC
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in reply to: Richard_Kennaway’s comment on: Is Bayesianism Susceptible to the Mail-Order Prophet Scam?
Okay, so what events or things do you pay attention to for updates relating to Bayesianism? Like say I’m a Bayesian with random priors, except for P(Bayesianism) which is say 0.51 currently. What kind of things do you observe that cause updates and why/how?

Sorry for the delayed replay. My comments are being held for review.

Max Kaye 1 Apr 2026 1:59 UTC
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in reply to: Myron Hedderson’s comment on: Is Bayesianism Susceptible to the Mail-Order Prophet Scam?
Keep in mind that these “probabilities” are subjective assessments of probability based on an individual’s prior knowledge, not facts about reality. Two Bayesians with different prior experience may disagree about how probable something is (/seems to them),

Doesn’t that mean we should expect that Bayesians often disagree and they have no way to resolve it except consulting reality (i.e., an experiment)?

If that’s the case, why bother with Bayesianism at all? It seems like any situation where people needed to agree on the truth of something, Bayesianism wouldn’t help:
1. They already agree (‘scientific consensus’ and similar situations) -- Bayesianism doesn’t offer anything here.
2. One person disagrees, everyone else agrees—without more data no progress is possible, so either we know a decisive experiment that will resolve the issue (in which case we don’t need Bayesianism), or we don’t, in which case Bayesianism can’t help.
3. Lots of disagreement—similar to above but more chaotic.
Also say there is an experiment, is there any standard or agreement among bayesians about how to weight credence? (when should it be weak or strong? etc) Because if there isn’t, they might not even be able to agree on what experiment to do or if it will matter.

Max Kaye 1 Apr 2026 1:47 UTC
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in reply to: Cole Wyeth’s comment on: Is Bayesianism Susceptible to the Mail-Order Prophet Scam?
I’m not actually that interested in the scam, more how Bayesianism handles the problem. If we assume the Bayesian has reasonable priors and isn’t naive, then your answer makes sense. But when we are talking about science and the frontier of knowledge, we don’t have that luxury.

I think I can demonstrate this with a much more abstract problem: how can I use Bayesianism to evaluate multiple schools of epistemology to find the best one? Can Bayesianism come to a definitive answer or will there always be a non-zero probability that any of the schools are the correct one? (assuming any of them are)

While I’m asking this to demonstrate that bad priors and naivety are the default state, I’m also genuinely interested in the answer.

Max Kaye 1 Apr 2026 1:23 UTC
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in reply to: Francis Rhys Ward’s comment on: Is Bayesianism Susceptible to the Mail-Order Prophet Scam?
Okay that sounds reasonable (to me, a non-bayesian) but where do the new hypotheses come from, or the ideas for how to reformulate the space? If they came from Bayesianism, why is reformulation ever necessary?

Max Kaye 1 Apr 2026 1:19 UTC
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in reply to: Alex A’s comment on: Is Bayesianism Susceptible to the Mail-Order Prophet Scam?
Okay I see, thanks.

When new evidence comes in that falsifies NMP, P(O) jumps up to 0.5.

Is that because we only have and left, and they both started equal? Did you have a reason for setting ?

Also, I guess the is removed because we have right? (Though IRL I understand it’s bayesian convention to choose a very small value rather than 0)

Also, do you know how things change after GR is published? (assuming no new data in the mean time)

Max Kaye 1 Apr 2026 1:11 UTC
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in reply to: Myron Hedderson’s comment on: Is Bayesianism Susceptible to the Mail-Order Prophet Scam?

If you have weak/uncertain priors, the thing to do is run low-cost experiments that differentiate between your different hypotheses of what’s going on.

CF kind of agrees here. CF says that any contradiction between theories can be used to create meaningful hypotheses that will refute one or both theories; and CF doesn’t have a concept of weak or strong arguments, instead it uses decisive criticisms and claims are either refuted or unrefuted.

What does Bayesianism say if you have strong priors? Is there an objective breakpoint that separates weak from strong priors? (e.g., P < 0.5?)

Max Kaye 31 Mar 2026 23:17 UTC
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in reply to: romeostevensit’s comment on: Is Bayesianism Susceptible to the Mail-Order Prophet Scam?
That seems reasonable, but how can the Bayesian tell in the scam example? (if there’s a selection effect at play or not) What about in the real world? We do have selection effects like this in nature (eg evolution / natural selection), so it seems like Bayesianism should be able to handle it.