Okay, but I’ve also seen rationalists use point estimates for probability in a way that led them to mess up Bayes, and such that it would be clear if they recognized the probability was uncertain (e.g., I saw this a few times related to covid predictions). I feel like it’s weird to use “frequency” for something that will only happen (or not happen) once, like whether the first AGI will lead to human extinction, though ultimately I don’t really care what word people are using for which concept.

# Daniel_Eth

# [Question] What does Functional Decision Theory say to do in imperfect Newcomb situations?

How common is it for transposon count to increase in a cell? If it’s a generally uncommon event for any one cell, then it could simply be that clones from a large portion of cells will only start off with marginally more (if any) extra transposons, while those that do start off with a fair bit more don’t make it past the early development process.

A perhaps even easier (though somewhat less informative) experiment would be to Crispr/CAS9 a bunch of extra transposons into an organism and see if that leads to accelerated aging.

Play with GPT-3 for long, and you’ll see it fall hard too.

...

This sample is a failure. No one would have written this, not even as satire or surrealism or experimental literature. Taken as a joke, it’s a nonsensical one. Taken as a plot for a film, it can’t even keep track of who’s alive and who’s dead. It contains three recognizable genres of writing that would never appear together in this particular way, with no delineations whatsoever.This sample seems pretty similar to the sort of thing that a human might dream, or that a human might say during/immediately after a stroke, a seizure, or certain types of migraines. It’s clear that the AI is failing here, but I’m not sure that humans don’t also sometimes fail in somewhat similar ways, or that there’s a fundamental limitation here that needs to be overcome in order to reach AGI.

The first time you see it, it surprises you, a crack in the floor… Eventually, you no longer picture of a floor with cracks in it. You picture a roiling chaos which randomly, but regularly, coalesces into ephemeral structures possessing randomly selected subsets of the properties of floors.

^I guess the corollary here would be that human minds may also be roiling chaos which randomly coalesce into ephemeral structures possessing properties of floors, but just are statistically much more likely to do so than current language models.

# Modeling Failure Modes of High-Level Machine Intelligence

FWIW, Hanson has elsewhere promoted the idea that algorithmic progress is primarily due to hardware progress. Relevant passage:

Maybe there are always lots of decent ideas for better algorithms, but most are hard to explore because of limited computer hardware. As hardware gets better, more new ideas can be explored, and some of them turn out to improve on the prior best algorithms. This story seems to at least roughly fit what I’ve heard about the process of algorithm design.

So he presumably would endorse the claim that HLMI will likely requires several tens of OOM more compute than we currently have, but that a plateauing in other inputs (such as AI researchers) won’t be as relevant. (Here’s also another post of Hanson where he endorses a somewhat related claim that we should expect exponential increases in hardware to translate to ~linear social impact and rate of automation.)

“uranium, copper, lithium, oil”

These are commodities, not equities (unless OP meant invested in companies in those industries?)

So again, I wasn’t referring to the expected value of the number of steps, but instead how we should update after learning about the time – that is, I wasn’t talking about but instead for various .

Let’s dig into this. From Bayes, we have: . As you say, ~ kt^(k-1). We have the pesky term, but we can note that for any value of , this will yield a constant, so we can discard it and recognize that now we don’t get a value for the update, but instead just a relative value (we can’t say how large the update is at any individual , but we can compare the updates for different ). We are now left with ~ kt^(k-1), holding constant. Using the empirical value on Earth of , we get ~ k*0.82^(k-1).

If we graph this, we get:

which apparently has its maximum at 5. That is, whatever the expected value for the number of steps is after considering the time, if we do update on the time, the largest update is in favor of there having been 5 steps. Compared to other plausible numbers for , the update is weak, though – this partiuclar piece of evidence is a <2x update on there having been 5 steps compared to there having been 2 steps or 10 steps; the relative update for 5 steps is only even ~5x the size of the update for 20 steps.

Considering the general case (where we don’t know ), we can find the maximum of the update by setting the derivative of kt^(k-1) equal to zero. This derivative is (k ln(t) + 1)t^(k-1), and so we need , or . If we replace with , such that corresponds to the naive number of steps as I was calculating before, then that’s . Here’s what we get if we graph that:

This is almost exactly my original guess (though weirdly, ~all values for are ~0.5 higher than the corresponding values of ).

The intuition, I assume, is that this is the inverse function of the previous estimator.

So the estimate for the number of hard steps doesn’t make sense in the absence of some prior. Starting with a prior distribution for the likelihood of the number of hard steps, and applying bayes rule based on the time passed and remaining, we will update towards more mass on k = t/(T–t) (basically, we go from P( t | k) to P( k | t)).

By “gives us reason to expect” I didn’t mean “this will be the expected value”, but instead “we should update in this direction”.

Having a model for the dynamics at play is valuable for making progress on further questions. For instance, knowing that the expected hard-step time is ~identical to the expected remaining time gives us reason to expect that the number of hard steps passed on Earth already is perhaps ~4.5 (given that the remaining time in Earth’s habitability window appears to be ~1 billion years). Admittedly, this is a weak update, and there are caveats here, but it’s not nothing.

Additionally, the fact that the expected time for hard steps is ~independent of the difficulty of those steps tells us that, among other things, the fact that abiogenesis was early in Earth’s history (perhaps ~400 MY after Earth formed) is not good evidence that abiogenesis is easy, as this is arguably around what we’d expect from the hard-step model (astrobiologists have previously argued that early abiogenesis on Earth is strong evidence for life being easy and thus common in the universe, and that if it was hard/rare that we’d expect abiogenesis to have occurred around halfway through Earth’s lifetime).

Of course, this model doesn’t help solve the latter two questions you raised, as it doesn’t touch on future steps. A separate line of research that made progress on those questions (or a different angle of attack on the questions that this model can address) would also be a valuable contribution to the field.

I like this comment, though I don’t have a clear-eyed view of what sort of research makes (A) or (B) more likely. Is there a concrete agenda here (either that you could link to, or in your head), or is the work more in the exploratory phase?

# Great-Filter Hard-Step Math, Explained Intuitively

Yeah, that also triggered my “probably false or very misleading” alarm. People are making all sorts of wild claims about covid online for political points, and I don’t even know who the random person on twitter making that claim was.

Yeah, I’m not trying to say that the point is invalid, just that phrasing may give the point more appeal than is warranted from being somewhat in the direction of a deepity. Hmm, I’m not sure what better phrasing would be.

The statement seems almost tautological – couldn’t we somewhat similarly claim that we’ll understand NNs in roughly the same ways that we understand houses, except where we have reasons to think otherwise? The “except where we have reasons to think otherwise” bit seems to be doing a lot of work.

Thanks. I feel like for me the amount of attention for a marginal daily pill is negligibly small (I’m already taking a couple supplements, and I leave the bottles all on the kitchen table, so this would just mean taking one more pill with the others), but I suppose this depends on the person, and also the calculus is a bit different for people who aren’t taking any supplements now.

“the protocol I analyze later requires a specific form of niacin”

What’s the form? Also, do you know what sort of dosage is used here?If niacin is helpful for long covid, I wonder if taking it decreases the chances of getting long covid to begin with. Given how well tolerated it is, it might be worth taking just in case.

“at least nanotech and nano-scale manufacturing at a societal scale would require

*much more energy*than we have been willing to provide it”

Maybe, but:

1) If we could build APM on a small scale now we would2) We can’t

3) This has nothing to do with energy limits

(My sense is also that advanced APM would be incredibly energy efficient and also would give us very cheap energy – Drexler provides arguments for why in Radical Abundance.)

I don’t think regulatory issues have hurt APM either (agree they have in biotech, though). Academic power struggles have hurt nanotech (and also biotech), though this seems to be the case in every academic field and not particularly related to creeping institutional sclerosis (over the past several hundred years, new scientific ideas have often had trouble breaking in through established paradigms, and we seem less bad on this front than we used to be). Regardless, neither of these issues would be solved with more energy, and academic power struggles would still exist even in the libertarian state Hall wants.

Hmm, does this not depend on how the Oracle is making its decision? I feel like there might be versions of this that look more like the smoking lesion problem – for instance, what if the Oracle is simply using a (highly predictive) proxy to determine whether you’ll 1-box or 2-box? (Say, imagine if people from cities 1-box 99% of the time, and people from the country 2-box 99% of the time, and the Oracle is just looking at where you’re from).