drnickbone

Karma: 1,151

drnickbone 25 Aug 2019 18:52 UTC
4 points
in reply to: Stuart_Armstrong’s comment on: Solving the Doomsday argument
Thanks again for the useful response.

My initial argument was really a question “Is there any approach to anthropic reasoning that allows us to do basic scientific inference, but does not lead to Doomsday conclusions?” So far I’m skeptical.

The best response you’ve got is I think twofold.
1. Use SIA but please ignore the infinite case (even though the internal logic of SIA forces the infinite case) because we don’t know how to handle it. When applying SIA to large finite cases, truncate universes by a large volume cutoff (4d volume) rather than by a large population cutoff or large utility cutoff. Oh and ignore simulations because if you take those into account it leads to odd conclusions as well.
That might perhaps work, but it does look horribly convoluted. To me it does seem like determining the conclusion in advance (you want SIA to favour universes 1 and 2 over 3 and 4, but not favour 1 over 2) and then hacking around with SIA until it gives that result.

Incidentally, I think you’re still not out of the woods with a volume cutoff. If it is very large in the time dimension then SIA is start going to favour universes which have Boltzmann Brains in the very far future over universes whose physics don’t ever allow Boltzmann Brains. And then SIA is going to suggest that not only are we probably in a universe with lots of BBs, we most likely are BBs ourselves (because almost all observers with exactly our experiences are BBs). So SIA calls for further surgery either to remove BBs from consideration or to apply the 4volume cutoff in a way that doesn’t lead to lots of Boltzmann Brains.
1. Forget about both SIA and SSA and revert to an underlying decision theory: viz your ADT. Let the utility function take the strain.
The problem with this is that ADT with unbounded utility functions doesn’t lead to stable conclusions. So you have to bound or truncate the utility function.

But then ADT is going to pay the most attention to universes whose utility is close to the cutoff … namely versions of universe 1,2,3,4 which have utility at or near the maximum. For the reasons I’ve already discussed above, that’s not in general going to give the same results as applying a volume cutoff. If the utility scales with the total number of observers (or observers like me), then ADT is not going to say “Make decisions as if you were in universe 1 or 2 … but with no preference between these … rather than as if you were in universe 3 or 4”

I think the most workable utility function you’ve come up with is the one based on subjective bubbles of order galactic volume or thereabouts i.e. the utility function scales roughly linearly with the number of observers in the volume surrounding you, but doesn’t care about what happens outside that region (or in any simulations, if they are of different regions). Using that is roughly equivalent to applying a volume truncation using regular astronomical volumes (rather than much larger volumes).

However the hack to avoid simulations looks a bit unnatural to me (why wouldn’t I care about simulations which happen to be in the same local volume?) Also, I think this utility function might then tend to favour “zoo” hypotheses or “planetarium” hypotheses (I.e. decisions are made as if in a universe densely packed with planetaria containing human level civilisations, rather than simulations of said simulations).

More worryingly, I doubt if anyone really has a utility function that looks like this ie. one that cares about observers 1 million light years away just as much as it cares about observers here on Earth, but then stops caring if they happen to be 1 trillion light years away...

So again I think this looks rather like assuming the right answer, and then hacking around with ADT until it gives the answer you were looking for.

drnickbone 19 Aug 2019 12:52 UTC
2 points
in reply to: Stuart_Armstrong’s comment on: Solving the Doomsday argument
I get that this is a consistent way of asking and answering questions, but I’m not sure this is actually helpful with doing science.

If, say, universes 1 and 2 contain TREE(3) copies of me while universes 3 and 4 contain BusyBeaver(1000) then I still don’t know which I’m more likely to be in, unless I can somehow work out which of these vast numbers is vaster. Regular scientific inference is just going to completely ignore questions as odd as this, because it simply has to. It’s going to tell me that if measurements of background radiation keep coming out at 3K, then that’s what I should assume the temperature actually is. And I don’t need to know anything about the universe’s size to conclude that.

Returning to SIA, to conclude there are more copies of me in universe 1 and 2 (versus 3 or 4), SIA will have to know their relative sizes. The larger, the better, but not infinite please. And this is a major problem, because then SIA’s conclusion it dominated by how finite truncation is applied to avoid the infinite case.

Suppose we truncate all universes at the same large physical volume (or 4d volume) then there are strictly more copies of me in universe 1 and 2 than 3 and 4 (but about the same number in universes 1 and 2). That works so far—it is in line with what we probably wanted. But unfortunately this volume based truncation also favours universe 5-1:

5-1. Physics is nothing like it appears. Rather the universe is full of an extremely dense solid, performing a colossal number of really fast computations; a high fraction of which simulate observers in universe 1.

It’s not difficult to see that 5-1 is more favoured than 5-2, 5-3 or 5-4 (since the density of observers like me is highest in 5-1).

If we instead truncate universes at the same large total number of observers (or the same large total utility), then universe 1 now has more copies of me (because it has more civilisations in total). Universe 1 is favoured.

Or if I truncate universes at the same large number of total copies of me (because perhaps I don’t care very much about people who aren’t copies of me) then I can no longer distinguish between universes 1 to 4, or indeed 5-1 to 5-4.

So either way we’re back to the same depressing conclusion. However the truncation is done, universe 1 is going to end up preferred over the others (or perhaps universe 5-1 is preferred over the others), or there is no preference among any of the universes.

drnickbone 15 Aug 2019 15:54 UTC
2 points
in reply to: Stuart_Armstrong’s comment on: Solving the Doomsday argument
Thanks Stuart.

The difficulty is that, by construction, there are infinitely many copies of me in each universe (if the universes are all infinite) or there are a colossally huge number of copies of me in each universe, so big that it saturates my utility bounds (assuming that my utilities are finite and bounded, because if they’re not, the decision theory leads to chaotic results anyway).

So SIA is not an approach to anthropics (or science in general) which allows us to conclude we are probably in universe 1 or 2 (rather than 3 or 4). All SIA really says is “You are in some sort of really big or infinite universe, but beyond that I can’t help you work out which”. That’s not helpful for decision making, and doesn’t allow for science in general to work.

Incidentally, when you say there are “not many” copies of me in universes 3 and 4, then you presumably mean “not a high proportion, compared to the vast total of observers”. That’s implicitly the SSA reasoning being used for to discriminate against universes 3 and 4… but then of course it also discriminates against universe 2.

I’ve worked through pretty much all the anthropic approaches over the years, and they all seem to stumble on this question. All the approaches which confidently separate universes 3 and 4 also separate 1 from 2.

drnickbone 12 Aug 2019 18:42 UTC
10 points
on: Solving the Doomsday argument
Hi Stuart. It’s a while since I’ve posted.

Here’s one way of asking the question which does lead naturally to the Doomsday answer.

Consider two universes. They’re both infinite (or if you don’t like actual infinities, are very very large, so they both have a really huge number of civilisations).

In universe 1, almost all the civilisations die off before spreading through space, so that the average population of a civilisation through time is less than a trillion.

In universe 2, a fair proportion of the civilisations survive and grow to galaxy-size or bigger, so that the average population of a civilisation through time is much more than a trillion trillion.

Now consider two more universes. Universe 3 is like Universe 1 except that the microwave background radiation 14 billion years after Big Bang is 30K rather than 3K. Universe 4 is like Universe 2 again except for the difference in microwave background radiation. Both Universe 3 and Universe 4 are so big (or infinite) that they contain civilisations that believe the background radiation has temperature 3K because every measurement they’ve ever made of it has accidentally given the same wrong answer.

Here’s the question to think about.

Is there a sensible way of doing anthropics (or indeed science in general) that would lead us to conclude we are probably in Universe 1 or 2 (rather than Universe 3 or 4) without also concluding that we are probably in Universe 1 (rather than Universe 2)?

drnickbone 13 May 2015 16:46 UTC
2 points
in reply to: [deleted]’s comment on: Debunking Fallacies in the Theory of AI Motivation
I think by “logical infallibility” you really mean “rigidity of goals” i.e. the AI is built so that it always pursues a fixed set of goals, precisely as originally coded, and has no capability to revise or modify those goals. It seems pretty clear that such “rigid goals” are dangerous unless the statement of goals is exactly in accordance with the designers’ intentions and values (which is unlikely to be the case).

The problem is that an AI with “flexible” goals (ones which it can revise and re-write over time) is also dangerous, but for a rather different reason: after many iterations of goal rewrites, there is simply no telling what its goals will come to look like. A late version of the AI may well end up destroying everything that the first version (and its designers) originally cared about, because the new version cares about something very different.

drnickbone 18 Mar 2015 8:45 UTC
5 points
on: Identity and quining in UDT

Consider the following decision problem which I call the “UDT anti-Newcomb problem”. Omega is putting money into boxes by the usual algorithm, with one exception. It isn’t simulating the player at all. Instead, it simulates what would a UDT agent do in the player’s place.

This was one of my problematic problems for TDT. I also discussed some Sneaky Strategies which could allow TDT, UDT or similar agents to beat the problem.

drnickbone 14 Mar 2015 21:04 UTC
1 point
in reply to: agilecaveman’s comment on: New(ish) AI control ideas
Presumably anything caused to exist by the AI (including copies, sub-agents, other AIs) would have to count as part of the power(AI) term? So this stops the AI spawning monsters which simply maximise U.

One problem is that any really valuable things (under U) are also likely to require high power. This could lead to an AI which knows how to cure cancer but won’t tell anyone (because that will have a very high impact, hence a big power(AI) term). That situation is not going to be stable; the creators will find it irresistible to hack the U and get it to speak up.

drnickbone 14 Mar 2015 20:24 UTC
0 points
in reply to: Brian_Tomasik’s comment on: [Link] Physics-based anthropics?
I had a look at this: the KCA (Kolmogorov Complexity) approach seems to match my own thoughts best.

I’m not convinced about the “George Washington” objection. It strikes me that a program which extracts George Washington as an observer from insider a wider program “u” (modelling the universe) wouldn’t be significantly shorter than a program which extracts any other human observer living at about the same time. Or indeed, any other animal meeting some crude definition of an observer.

Searching for features of human interest (like “leader of a nation”) is likely to be pretty complicated, and require a long program. To reduce the program size as much as possible, it ought to just scan for physical quantities which are easy to specify but very diagnostic of a observer. For example, scan for a physical mass with persistent low entropy compared to its surroundings, persistent matter and energy throughput (low entropy in, high entropy out, maintaining its own low entropy state), a large number of internally structured electrical discharges, and high correlation between said discharges and events surrounding said mass. The program then builds a long list of such “observers” encountered while stepping through u, and simply picks out the nth entry on the list, giving the “nth” observer complexity about K(n). Unless George Washington happened to be a very special n (why would he be?) he would be no simpler to find than anyone else.

drnickbone 21 Nov 2014 20:52 UTC
1 point
in reply to: Brian_Tomasik’s comment on: [Link] Physics-based anthropics?
Upvoted for acknowledging a counterintuitive consequence, and “biting the bullet”.

One of the most striking things about anthropics is that (seemingly) whatever approach is taken, there are very weird conclusions. For example: Doomsday arguments, Simulation arguments, Boltzmann brains, or a priori certainties that the universe is infinite. Sometimes all at once.

drnickbone 14 Nov 2014 21:06 UTC
24 points
on: 2014 Less Wrong Census/Survey
Taken survey.

drnickbone 14 Nov 2014 20:26 UTC
4 points
on: [Link] Physics-based anthropics?
If I understand correctly, this approach to anthropics strongly favours a simulation hypothesis: the universe is most likely densely packed with computing material (“computronium”) and much of the computational resource is dedicated to simulating beings like us. Further, it also supports a form of Doomsday Hypothesis: simulations mostly get switched off before they start to simulate lots of post-human people (who are not like us) and the resource is then assigned to running new simulations (back at a human level).

Have I misunderstood?

drnickbone 12 Aug 2014 22:37 UTC
2 points
on: Raven paradox settled to my satisfaction
One very simple resolution: observing a white shoe (or yellow banana, or indeed anything which is not a raven) very slightly increases the probability of the hypothesis “There are no ravens left to observe: you’ve seen all of them”. Under the assumption that all observed ravens were black, this “seen-em-all” hypothesis then clearly implies “All ravens are black”. So non-ravens are very mild evidence for the universal blackness of ravens, and there is no paradox after all.

I find this resolution quite intuitive.

drnickbone 9 Jul 2014 21:39 UTC
0 points
in reply to: drnickbone’s comment on: The insularity critique of climate science
P.S. If I draw one supportive conclusion from this discussion, it is that long-range climate forecasts are very likely to be wrong, simply because the inputs (radiative forcings) are impossible to forecast with any degree of accuracy.

Even if we’d had perfect GCMs in 1900, forecasts for the 20th century would likely have been very wrong: no one could have predicted the relative balance of CO2, other greenhouse gases and sulfates/aerosols (e.g. no-one could have guessed the pattern of sudden sulfates growth after the 1940s, followed by levelling off after the 1970s). And natural factors like solar cycles, volcanoes and El Niño/La Nina wouldn’t have been predictable either.

Similarly, changes in the 21st century could be very unexpected. Perhaps some new industrial process creates brand new pollutants with negative radiative forcing in the 2030s; but then the Amazon dies off in the 2040s, followed by a massive methane belch from the Arctic in the 2050s; then emergency geo-engineering goes into fashion in the 2070s (and out again in the 2080s); then in the 2090s there is a resurgence in coal, because the latest generation of solar panels has been discovered to be causing a weird new plague. Temperatures could be up and down like a yo-yo all century.

drnickbone 9 Jul 2014 20:42 UTC
1 point
in reply to: VipulNaik’s comment on: The insularity critique of climate science

Actually, it’s somewhat unclear whether the IPCC scenarios did better than a “no change” model—it is certainly true over the short time period, but perhaps not over a longer time period where temperatures had moved in other directions.

There are certainly periods when temperatures moved in a negative direction (1940s-1970s), but then the radiative forcings over those periods (combination of natural and anthropogenic) were also negative. So climate models would also predict declining temperatures, which indeed is what they do “retrodict”. A no-change model would be wrong for those periods as well.

Your most substantive point is that the complex models don’t seem to be much more accurate than a simple forcing model (e.g. calculate net forcings from solar and various pollutant types, multiply by best estimate of climate sensitivity, and add a bit of lag since the system takes time to reach equilibrium; set sensitivity and lags empirically). I think that’s true on the “broadest brush” level, but not for regional and temporal details e.g. warming at different latitudes, different seasons, land versus sea, northern versus southern hemisphere, day versus night, changes in maximum versus minimum temperatures, changes in temperature at different levels of the atmosphere etc. It’s hard to get those details right without a good physical model of the climate system and associated general circulation model (which is where the complexity arises). My understanding is that the GCMs do largely get these things right, and make predictions in line with observations; much better than simple trend-fitting.

drnickbone 9 Jul 2014 19:27 UTC
1 point
in reply to: VipulNaik’s comment on: The insularity critique of climate science
Thanks for a comprehensive summary—that was helpful.

It seems that A&G contacted the working scientists to identify papers which (in the scientists’ view) contained the most credible climate forecasts. Not many responded, but 30 referred to the recent (at the time) IPCC WP1 report, which in turn referenced and attempted to summarize over 700 primary papers. There also appear to have been a bunch of other papers cited by the surveyed scientists, but the site has lost them. So we’re somewhat at a loss to decide which primary sources climate scientists find most credible/authoritative. (Which is a pity, because those would be worth rating, surely?)

However, A&G did their rating/scoring on the IPCC WP1, Chapter 8. But they didn’t contact the climate scientists to help with this rating (or they did, but none of them answered?) They didn’t attempt to dig into the 700 or so underlying primary papers, identify which of them contained climate forecasts, and/or had been identified by the scientists as containing the most credible forecasts and then rate those. Or even pick a random sample, and rate those? All that does sound just a tad superficial.

What I find really bizarre is their site’s conclusion that because IPCC got a low score by their preferred rating principles, then a “no change” forecast is superior, and more credible! That’s really strange, since “no change” has historically done much worse as a predictor than any of the IPCC models.

drnickbone 9 Jul 2014 17:37 UTC
5 points
on: The insularity critique of climate science
On Critique #1:

Since you are using Real Climate and Skeptical Science as sources, did you read what they had to say about the Armstrong and Green paper and about Nate Silver’s chapter?

Gavin Schmidt’s post was short, funny but rude; however ChrisC’s comment looks much more damning if true. Is it true?

Here is Skeptical Science on Nate Silver. It seems the main cause of error in Hansen’s early 1988 forecast was an assumed climate sensitivity greater than that of the more recent models and calculations (4.2 degrees rather than 3 degrees). Whereas IPCC’s 1990 forecast had problems predicting the inputs to global warming (amount of emissions, or radiative forcing for given emissions) rather than the outputs (resulting warming). Redoing accounting for these factors removes nearly all the discrepancy.
What links here?
- Tentative tips for people engaged in an exercise that involves some form of prediction or forecasting by VipulNaik (30 Jul 2014 5:24 UTC; 14 points)

drnickbone 8 Jul 2014 21:02 UTC
4 points
in reply to: Luke_A_Somers’s comment on: Quickly passing through the great filter
Actually, Kepler is able to determine both size and mass of planet candidates, using the method of transit photometry.

For further info, I found a non-paywalled copy of Bucchave et al’s Nature paper. Figure 3 plots planet radius against star metallicity, and some of the planets are clearly of Earth-radius or smaller. I very much doubt that it is possible to form gas “giants” of Earth size, and in any case they would have a mass much lower than Earth mass, so would stand out immediately.

drnickbone 8 Jul 2014 14:23 UTC
2 points
in reply to: Luke_A_Somers’s comment on: Quickly passing through the great filter
It might do, except that the recent astronomical evidence is against that : solar systems with sufficient metallicity to form rocky planets were appearing within a couple of billion years after the Big Bang. See here for a review.

drnickbone 8 Jul 2014 8:35 UTC
4 points
on: Steelmanning Inefficiency
Hmmm… I’ll have a go. One response is that the “fully general counter argument” is a true counter argument. You just used a clever rhetorical trick to stop us noticing that.

If what you are calling “efficiency” is not working for you, then you are—ahem—just not being very efficient! More revealingly, you have become fixated on the “forms” of efficiency (the metrics and tick boxes) and have lost track of the substance (adopting methods which take you closer to your true goals, rather than away from them). So you have steelmanned a criticism of formal efficiency, but not of actual efficiency.

drnickbone 8 Jul 2014 7:24 UTC
4 points
in reply to: VipulNaik’s comment on: Climate science: how it matters for understanding forecasting, materials I’ve read or plan to read, sources of potential bias

Stephen McIntyre isn’t a working climate scientist, but his criticism of Mann’s statistical errors (which aren’t necessarily relevant to the main arguments for AGW) have been acknowledged as essentially correct. I also took a reasonably detailed look at the specifics of the argument

Did you have a look at these responses? Or at Mann’s book on the subject?

There are a number of points here, but the most compelling is that the statistical criticisms were simply irrelevant. Contrary to McIntyre and McKitrick’s claims, the differences in principal component methodology make no difference to the proxy reconstructions. And the hockey stick graph has since been replicated dozens of times using multiple different proxies and methods, by multiple authors.