All of Denkenberger🔸's Comments + Replies

Let  be the number of parameters in the model,  be the number of data tokens it is trained on,  be the number of times the model is deployed (e.g. the number of questions it is asked) and  be the number of inference steps each time it is deployed (e.g. the number of tokens per answer). Then this approximately works out to:[9]

Note that scaling up the number of parameters, , increases both pre-training compute and inference compute, because you need to use those parameters each time you run a forward pass in your model.

Several variables a... (read more)

If AI systems replace humanity, that outcome would undoubtedly be an absolute disaster for the eight billion human beings currently alive on Earth. However, it would be a localized, short-term disaster rather than an astronomical one. Bostrom's argument, strictly interpreted, no longer applies to this situation. The reason is that the risk is confined to the present generation of humans: the question at stake is simply whether the eight billion people alive today will be killed or allowed to continue living. Even if you accept that killing eight billion pe

... (read more)
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Vasco Grilo🔸
Hi David! Would the dinossaurs have argued their extinction would be bad, although it may well have contributed to the emergence of mammals and ultimately humans? Would the vast majority of non-human primates have argued that humans taking over would be bad? Why? It could be that future value is not exactly the same if AI takes over or not by a given date, but that the longer difference in value is negligible.

Could you please explain your reasoning on 40 hours?

I think your formulation is elegant, but I think the real possibilities are lumpier and span many more orders of magnitude (OOMs). Here's a modification from a comment on a similar idea: 

I think there would be some probability mass that we have technological stagnation and population reductions, though the cumulative number of lives would be much larger than alive today. Then there would be some mass on maintaining something like 10 billion people for a billion years (no AI, staying on earth either due to choice or technical reasons). Then there would... (read more)

I didn't realize it was that much money. This has relevance to the debates about whether AI will value humans. Though EA has not focused as much on making mainstream money more effective, there have been some efforts.
But my major response is why the focus on cultivated meat? It seems like efforts on plant-based meat or fermentation or leaf protein concentrate have much greater likelihood of achieving parity in the near term. 

It could even be that mitigating existential risk is the most cost-effective way of saving species, though I realize that is pro... (read more)

1
David Goodman
Fermentation or leaf protein concentrate are other excellent ideas. The main reason I think lab-grown beef is the thing to focus in is simply because beef is the main issue. The elephant in the biodiversity room is primarily cattle-ranching. Any successful intervention, purely from a biodiversity perspective (the perspective of this pot of money) would have to address beef. I understand there are probably multiple avenues towards that goal, however, and would be very open to being persuaded that other methods could achieve it. 

Thanks for doing this and for pointing it out to me. Yeah, participation bias could be huge, but it's still good to get some idea.

=Confusion in What mildest scenario do you consider doom?=

My probability distribution looks like what you call the MIRI Torch, and what I call the MIRI Logo: Scenarios 3 to 9 aren't well described in the literature because they are not in a stable equilibrium. In the real world, once you are powerless, worthless and an obstacle to those in power, you just end up dead. 

This question was not about probability, but instead what one considers doom. But let's talk probability. I think Yudkowsky and Soares believe that one or more of 3-5 has decent likeliho... (read more)

I'm not sure if you consider LessWrong serious literature, but cryonically preserving all humans was mentioned here. I think nearly everyone would consider this doom, but there are people defending extinction (which I think is even worse) as not doom, so I included all them for completeness.

Yes, one could take many hours thinking through these questions (as I have), but even if one doesn't have that time, I think it's useful to get an idea how people are defining doom, because a lot of people use the term, and I suspect that there is a wide variety of defi... (read more)

1
Søren Elverlin
=Confusion in What mildest scenario do you consider doom?= My probability distribution looks like what you call the MIRI Torch, and what I call the MIRI Logo: Scenarios 3 to 9 aren't well described in the literature because they are not in a stable equilibrium. In the real world, once you are powerless, worthless and an obstacle to those in power, you just end up dead.  =Confusion in Minimum P(doom) that is unacceptable to develop AGI?= For non-extreme values, the concrete estimate and the most of the considerations you mention are irrelevant. The question is morally isomorphic to "What percentage of the worlds population am I willing to kill in expectation?". Answers such as "10^6 humans" and "10^9 humans" are both monstrous, even though your poll would rate them very differently. These possible answers don't become moral even if you think that it's really positive that humans don't have to work any longer. You aren't allowed to do something worse than the Holocaust in expectation, even if you really really like space travel or immortality, or ending factory farming, or whatever. You aren't allowed to unilaterally decide to roll the dice on omnicide even if you personally believe that global warming is an existential risk, or that it would be good to fill the universe with machines of your creation.   

Minimum P(doom) that is unacceptable to develop AGI

80%: I think even if we were disempowered, we would likely get help from the AGI to quickly solve problems like poverty, factory farming, aging, etc. and I do think that is valuable. If humanity were disempowered, I think there would still be some value in expectation of the AGI settling the universe. I am worried that a pause before AGI could become permanent (until there is population and economic collapse due to fertility collapse, after which it likely doesn’t matter), and that could prevent the settle... (read more)

P(doom)

75%: Simple sum of catastrophe and disempowerment because I don't think inequality is that bad.

P(disempowerment|AGI)

60%: If humans stay biological, it's very hard for me to imagine in the long run ASI with its vastly superior intelligence and processing speed still taking direction from feeble humans. I think if we could get human brain emulations going before AGI got too powerful, perhaps by banning ASI until it is safe, then we have some chance. You can see for someone like me with much lower P(catastrophe|AGI) than disempowerment why it’s very important to know whether disempowerment is considered doom!

P(catastrophe|AGI)

15%: I think it would only take around a month's delay of AGI settling the universe to spare earth from overheating, which is something like one part in 1 trillion of the value lost, if there is no discounting, due to receding galaxies. The continuing loss of value by sparing enough sunlight for the earth (and directing the infrared radiation from the Dyson swarm away from Earth so it doesn't overheat) is completely negligible compared to all the energy/mass available in the galaxies that could be settled. I think it is relatively un... (read more)

What mildest scenario do you consider doom?

“AGI takes control bloodlessly and prevents competing AGI and human space settlement in a light touch way, and human welfare increases rapidly:” I think this would result in a large reduction in long-term future expected value, so it qualifies as doom for me.

Seeing the amount of private capital wasted on generative AI has been painful. (OpenAI alone has raised about $80 billion and the total, global, cumulative investment in generative AI seems like it’s into the hundreds of billions.) It’s made me wonder what could have been accomplished if that money had been spent on fundamental AI research instead. Maybe instead of being wasted and possibly even nudging the U.S. slightly toward a recession (along with tariffs and all the rest), we would have gotten the kind of fundamental research progress needed for usefu

... (read more)
2
Yarrow Bouchard 🔸
That’s an important point of clarification, thanks. I always appreciate your comments, Mr. Denkenberger. There’s the idea of economic stimulus. John Maynard Keynes said that it would be better to spend stimulus money on useful projects (e.g. building houses), but as an intellectual provocation to illustrate his point, he said that if there were no better option, the government should pay people to dig holes in the ground and fill them back up again. Stimulating the economy is its own goal distinct from what the money actually gets spent to directly accomplish. AI spending is an economic stimulus. Even if the data centres sit idle and never do anything economically valuable or useful — the equivalent of holes dug in the ground that were just filled up again — it could have a temporarily favourable effect on the economy and help prevent a recession. That seems like it’s probably been true so far. The U.S. economy looks recessarionary if you subtract the AI numbers. However, we have to consider the counterfactual. If investors didn’t put all this money into AI, what would have happened? Of course, it’s hard to say. Maybe they just would have sat on their money, in which case the stimulus wouldn’t have happened, and maybe a recession would have begun by now. That’s possible. Alternatively, investors might have found a better use for their money, could have found more productive investments. Regardless of what happens in the future, I don’t know if we’ll ever be able to know for sure what would have happened if there hadn’t been this AI investment craze. So, who knows. (I think there are many things to invest in that would have been better choices than AI, but the question is whether, in a counterfactual scenario without the current AI exuberance, investors actually would have gone for any of them. Would they have invested enough in other things to stimulate the economy enough to avoid a recession?) The stronger point, in my opinion, is that I don’t think anyone wo

Here's my attempt at percentile of job preference.

Right - only 5% of EA Forum users surveyed want to accelerate AI:

"13% want AGI never to be built, 26% said to pause AI now in some form, and another 21% would like to pause AI if there is a particular event/threshold. 31% want some other regulation, 5% are neutral and 5% want to accelerate AI in a safe US lab."

9
Elityre
This post is not (mainly) calling out EA and EAs for wanting to accelerate AI. It's calling out those of us who do think that the AGI labs are developing a technology that will literally kill us and destroy everything we love with double digit probability, but are still friendly with the labs and people who work at the labs. And it's calling out those people who think the above, and take a salary from the AGI labs anyway. I read this post as saying something like,  I don't overall agree with this take, at this time. But I'm not very confident in my disagreement. I think Holly might basically be right here, and on further reflection I might come to agree with her. I definitely agree that the major reason why there's not more vocal opposition to working at an AGI lab is social conformity and fear of social risk. (Plus most of us are not well equipped to evaluated whether it possibly makes sense to try to "make things better from the inside", and so we defer to others who are broadly pro some version of that plan.)  

Quoting myself:

So I do think that it is a vocal minority in EA and LW that have median timelines before 2030.

Now we have some data on AGI timelines for EA (though it was only 34 responses, so of course there could be large sample bias): about 15% expect it by 2030 or sooner.

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Yarrow Bouchard 🔸
But 47% (16 out of 34) put their median year no later than 2032 and 68% (23 out of 34) put their median year no later than 2035, so how significant a finding this is depends how much you care about those extra 2-5 years, I guess. Only 12% (4 out of 34) of respondents to the poll put their median year after 2050. So, overall, respondents overwhelmingly see relatively near-term AGI (within 25 years) as at least 50% likely.

Wow - @Toby_Ord then why did you have such a high existential risk for climate? Did you have large likelihoods that AGI would take 100 or 200 years despite a median date of 2032?

Most of these statistics (I haven't read the links) don't necessarily imply that they are unsustainable. The soil degradation sounds bad, but how much has it actually reduced yields? Yields have ~doubled in the last ~70 years despite soil degradation. I talk some about supporting 10 billion people sustainably at developed country standards of living in my second 80,000 Hours podcast.

So you don't think that cultivated pork would qualify because the cell culture would not come from a halal animal?

7
zeshen🔸
Yes. If the source of the cell is from an animal that is haram (i.e. non-halal), then it cannot be considered halal. 

Yeah, and there are lots of influences. I got into X risk in large part due to Ray Kurzweil's The Age of Spiritual Machines (1999) as it said "My own view is that a planet approaching its pivotal century of computational growth - as the Earth is today - has a better than even chance of making it through. But then I have always been accused of being an optimist."

Interesting idea.

As we switch to wind/solar, you can get the same energy services with less primary energy, something like a factor of 2.

We’re a factor ~500 too small to be type I.

  • Today: 0.3 VPP
  • Type I: 40 VPP

 

But 40 is only ~130X 0.3.

There is some related discussion here about distribution.

I'm not sure exactly, but ALLFED and GCRI have had to shrink, and ORCG, Good Ancestors, Global Shield, EA Hotel, Institute for Law & AI (name change from Legal Priorities Project), etc have had to pivot to approximately all AI work. SFF is now almost all AI.

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Yarrow Bouchard 🔸
That’s deeply disturbing.

I agree, though I think the large reduction in EA funding for non-AI GCR work is not optimal (but I'm biased with my ALLFED association).

2
Yarrow Bouchard 🔸
How much reduction in funding for non-AI global catastrophic risks has there been…?

Ah... now I see you above and I realized I could mouse over - it is year of crazy. So you think the world will get crazy two years after AGI.

Was your model informed by @Arepo 's similar models? I believe he was considering rerunning the time of perils because of a catastrophe before AGI. Either way, catastrophic risk becomes much more important to the long-run future than with a simple analysis.

2
Arepo
Thanks for the shout-out :) If you mentally replace the 'multiplanetary' state with 'post-AGI' in this calculator, I do think it models the set of concerns Will's talking about here pretty well.

For which event? I'm not seeing you on the poll above.

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Denkenberger🔸
Ah... now I see you above and I realized I could mouse over - it is year of crazy. So you think the world will get crazy two years after AGI.

Interesting. The claim I heard was that some rationalists anticipated that there would be a lockdown in the US and figured out who they wanted to be locked down with, especially to keep their work going. That might not have been put on LW when it was happening. I was skeptical that the US would lock down.

50% of my income for the 11th year to ALLFED.

3
NickLaing
Now that's putting your money where your mouth is - Love it!

Yes, one or more of the "crazy" things happening by 2029. Good suggestion: I have edited the post and my comments to include the year. 

Slow things down 10 to how many years?

2
NickLaing
sorry edited

Good question. For personal planning purposes, I think all causes would make sense. But the title is AI, so maybe just significantly associated with AI? I think these polls are about how the future is different because of AI.

Denkenberger🔸
*2
0
0
70% disagree

Year of Crazy (2029)

I'm using a combination of scenarios in the post - one or more of these happen significantly before AGI.

2
Yarrow Bouchard 🔸
Help me make sure I’m understanding this right. You’re at position #4 from left to right, so this means 2029 according to your list. So, this means you think there’s a 50% chance of a combination of the "crazy" scenarios happening by 2029, right? Unfortunately, the EA Forum polls software makes it hard to ask certain kinds of questions. Your prediction is listed as "70% 2026", but that’s just an artifact of the poll software. To make it clear to readers what people are actually predicting, and to make sure people giving predictions understand the system properly, you might want to add instructions for people to say something like '50% chance the Year of Crazy happens by 2029’ at the top of their comments. That would at least save readers the trouble of cross-referencing the list for every single prediction. I tried to do a poll on people’s AI bubble predictions and I ran into a similar issue with the poll software displaying the results confusingly.
Denkenberger🔸
*2
0
0
20% disagree

Year of Singularity (2040)

Though I think we could get explosive economic growth with AGI or even before, I'm going to interpret this as explosive physical growth, that we could double physical resources every year or less. I think that will take years after AGI to, e.g., crack robotics/molecular manufacturing.

Denkenberger🔸
*2
2
0
40% disagree

Year of AGI (2035)

Extrapolating the METR graph here <https://www.lesswrong.com/posts/6KcP7tEe5hgvHbrSF/metr-how-does-time-horizon-vary-across-domains> means soon for super-human coder, but I think it's going to take years after that for the tasks that are slower on that graph, and many tasks are not even on that graph (despite the speedup from having a superhuman coder).

Here's another example of someone in the LessWrong community thinking that LLMs won't scale to AGI.

2
Yarrow Bouchard 🔸
Was there another example before this? Steven Byrnes commented on one of my posts from October and we had an extended back-and-forth, so I’m a little bit familiar with his views.
3
Sanu 🔸
Full fatwa here (Malay): https://ciri.islam.gov.my/view/fatwa_cetak.php?id=16914 Cultivated meat can be declared halal as long as the cell culture comes from a halal animal that has been slaughtered according to Islamic law, and as long as the media is halal (so not derived from blood or other haram substances) Note: I do not speak Malay, nor am I Muslim, so further confirmation from someone who fits either of those demographics would be beneficial

Welcome, Denise! You may be interested in ALLFED, as one of the things we investigate is resilience to tail end climate catastrophes.

"I don't want to encourage people to donate (even to the same places as I did) unless you already have a few million dollars in assets"

I do see advantages of the abundance mindset, but your threshold is extremely high-it excludes nearly everyone in developed countries, let alone the world. Plenty of people without millions of dollars of assets have an abundance mindset (including myself).

Some say (slight hyperbole), "Teaching a child to not step on bugs is as valuable to the child as it is to the bug." So I think there is some mainstream caring about bugs.

3
JessMasterson
Perhaps, but I suspect they care a lot more about building empathy and compassion in children than they do about the actual well-being of bugs - I'd imagine that avoiding stepping on them is more of a means to an (anthropocentric) end.

Shameless plug for ALLFED: Four of our former volunteers moved into paid work in biosecurity, and they were volunteers before we did much direct work in biosecurity. Now we are doing more directly. Since ALLFED has had to shrink, the contribution from volunteers has become relatively more important. So I think ALLFED is a good place for young people to skill up in biosecurity and have impact.

Here are some probability distributions from a couple of them.

2
Yarrow Bouchard 🔸
Thanks. Do they actually give probability distributions for deep learning being the wrong paradigm for AGI, or anything similar to that? It looks Ege Erdil said 50% for that question, or something close to that question. Ajeya Cotra said much less than 50%, but she didn't say how much less. I didn't see Daniel Kokotajlo give a number in that post, but then we have the 30-40% number he gave above, on the 80,000 Hours Podcast. The probability distributions shown in the graphs at the top of the post are only an indirect proxy for that question. For example, despite Kokotajlo's percentage being 30-40%, he still thinks that will most likely only slow down AGI by 5-10 years. I'm just looking at the post very briefly and not reading the whole thing, so I might have missed the key parts you're referring to.

I have a very hard time believing that the average or median person in EA is more aware of issues like P hacking (or the replication crisis in psychology, or whatever) than the average of median academic working professionally in the social sciences. I don't know why you would think that.

 

Maybe aware is not the right word now. But I do think that EAs updated more quickly that the replication crisis was a big problem. I think this is somewhat understandable, as the academics have strong incentives to get a statistically significant result to publish pa... (read more)

2
Yarrow Bouchard 🔸
Thank you for clarifying your views and getting into the weeds. I don't know how you would go about proving that to someone who (like me) is skeptical.   The sort of problems with Yudkowsky's epistemic practices that I'm referring to have existed for much longer than the last few years. Here's an example from 2017. Another significant example from around 2015-2017 is that he quietly changed his view from skeptical of deep learning as a path to AGI and still leaning toward symbolic AI or GOFAI as the path of AGI to all-in on deep learning, but never publicly explained why.[1] This couldn't be more central to his life's work, so that's very odd. [Edited on 2026-01-18 at 20:54 UTC to add: I misremembered some important details about my exchanges on Facebook with Eliezer Yudkowsky and another person at MIRI, Rob Bensinger, about deep learning and other AI paradigms around 2016-2018. Take my struckthrough recollections above as unreliable memory. I went through the trouble of digging up some old Facebook comments and detailed what I found here.] This blog post from 2015 criticizes some of the irrationalities in Yudkowsky's Sequences, which were written in 2006-2009.  If you go back to Yudkowsky's even earlier writings from the late 1990s and early 2000s, some of the very same problems are there.  So, really, these are problems that go back at least 7 years or so and arguably much longer than that, even as long as about 25 years. 1. ^ Around 2015-2017, I talked to Yudkowsky about this in a Facebook group about AI x-risk, which is part of why I remember it so vividly.

You said:

I see no evidence that effective altruism is any better at being unbiased than anyone else.

 

So that's why I compared to non-EAs. But ok, let's compare to academia. As you pointed out, there are many different parts of academia. I have been a graduate student or professor at five institutions, but only two countries and only one field (engineering, though I have published some outside of engineering). As I said in the other comment, academia is much more rigorously referenced than the EA Forum, but the disadvantage of this is that academia pus... (read more)

2
Yarrow Bouchard 🔸
Yes, I said "anyone else", but that was in the context of discussing academic research. But if we were to think more broadly and adjust for demographic variables like level of education (or years of education) and so on, as well as maybe a few additional variables like how interested someone is in science or economics, I don't really believe that people in effective altruism would do particularly better in terms of reducing their own bias.  I don't think people in EA are, in general or across the board, particularly good at reducing their bias. If you do something like bring up a clear methodological flaw in a survey question, there is a tendency of some people to circle the wagons and try to deflect or downplay criticism rather than simply acknowledge the mistake and try to correct it.  I think some people (not all and not necessarily most) in EA sometimes (not all the time and not necessarily most of the time) criticize others for perceived psychological bias or poor epistemic practices and act intellectually superior, but then make these sort of mistakes (or worse ones) themselves, and there's often a lack of self-reflection or a resistance to criticism, disagreement, and scrutiny.  I worry that perceiving oneself as intellectually superior can lead to self-licensing, that is, people think of themselves as more brilliant and unbiased than everyone else, so they are overconfident in their views and overly dismissive of legitimate criticism and disagreement. They are also less likely to examine themselves for psychological bias and poor epistemic practices.  But what I just said about self-licensing is just a hunch. I worry that it's true. I don't know whether it's true or not. I have a very hard time believing that the average or median person in EA is more aware of issues like P hacking (or the replication crisis in psychology, or whatever) than the average or median academic working professionally in the social sciences. I don't know why you would think tha

Daniel said "I would say that there’s like maybe a 30% or 40% chance that something like this is true, and that the current paradigm basically peters out over the next few years."

It might have been Carl on the Dwarkesh podcast, but I couldn't easily find a transcript. But I've heard from several others (maybe Paul Christiano?) that they have 10-40% chance that AGI is going to take much longer (or is even impossible), either because the current paradigm doesn't get us there, or because we can't keep scaling compute exponentially as fast as we have in the last decade once it becomes a significant fraction of GDP.

2
Yarrow Bouchard 🔸
Yes, Daniel Kokotajlo did say that, but then he also said if that happens, all the problems will be solved fairly quickly anyway (within 5-10 years), so AGI will be only be delayed from maybe 2030 to 2035, or something like that. Overall, I find his approach to this question to be quite dismissive of possibilities or scenarios other than near-term AGI and overzealous in his belief that either scaling or sheer financial investment (or utterly implausible scenarios about AI automating AI research) will assuredly solve all roadblocks on the way to AGI in very short order. This is not really a scientific approach, but just hand-waving conceptual arguments and overconfident gut intuition. So, because he doesn't really think the consequences of even fundamental problems with the current AI paradigm could end up being particularly significant, I give Kokotajlo credit for thinking about this idea in the first place (which is like saying I give a proponent of the covid lab leak hypothesis credit for thinking about the idea that the virus could have originated naturally), but I don't give him credit for a particularly good or wise consideration of this issue. I'd be very interested in seeing the discussions of these topics from Carl Schulman and/or Paul Christiano you are remembering. I am curious to know how deeply they reckon with this uncertainty. Do they mostly dismiss it and hand-wave it away like Kokotajlo? Or do they take it seriously?  In the latter case, it could be helpful for me because I'd have someone else to cite when I'm making the argument that these fundamental, paradigm-level considerations around AI need to be taken seriously when trying to forecast AGI.

Wouldn’t a global totalitarian government — or a global government of any kind — require advanced technology and a highly developed, highly organized society? So, this implies a high level of recovery from a collapse, but, then, why would global totalitarianism be more likely in such a scenario of recovery than it is right now? 

Though it may be more likely for the world to go to global totalitarianism after recovery from collapse, I was referring to a scenario where there was not collapse, but the catastrophe pushed us towards totalitarianism. Some pe... (read more)

2
Yarrow Bouchard 🔸
Thank you for sharing your perspective. I appreciate it.  I definitely misunderstood what you were saying about global totalitarianism. Thank you for clarifying. I will say I have a hard time guessing how global totalitarianism might result from a near-miss or a sub-collapse disaster involving one of the typical global catastrophe scenarios, like nuclear war, pandemics (natural or bioengineered), asteroids, or extreme climate change. (Maybe authoritarianism or totalitarianism within some specific countries, sure, but a totalitarian world government?) To be clear, are you saying that your own paper about storing data on the Moon is also a Plan F? I was curious what you thought of the Arch Mission Foundation because your paper proposes putting data on the Moon and someone has actually done that! They didn't execute your specific idea, of course, but I wondered how you thought their idea stacked up against yours. I definitely agree that putting data on the Moon should be at best a Plan F, our sixth priority, if not even lower! I think the chances of data on the Moon ever being useful are slim, and I don't want the world to ever get into a scenario where it would be useful! Ah, I agree, this is correct, but I meant the idea of value lock-in is inherited from a very specific way of thinking about AGI primarily popularized by MIRI and its employees but also popularized by people like Nick Bostrom (e.g. in his 2014 book Superintelligence). Thinking value lock-in is a serious and likely concern with regard to AGI does not require you to subscribe to MIRI's specific worldview or Bostrom's on AGI. So, you're right in that respect.  But I think if recent history had played a little differently and ideas about AGI had been formed imagining that human brain emulation would be the underlying technological paradigm, or that it would be deep learning and deep reinforcement learning, then the idea of value lock-in would not be as popular in current discussions of AGI as it is.

The movie's reviews and ratings have been hurt by its rather frustrating ending, but I think that's unfair to its overall dramatic excellence.

The link didn't work. 

Spoilers: the fatality estimate is ~1 order of magnitude too high. It's true that if there are lots of nukes headed towards your missile silos, there is great urgency to launch before being destroyed. However, there is not that urgency to launch if a city is targeted, so it seemed contrived. I was not aware that ground based interceptors have to physically hit the ICBM, instead of having an... (read more)

I agree that extinction has been overemphasized in the discussion of existential risk. I would add that it's not just irrecoverable collapse, but the potential increased risk of subsequent global totalitarianism or worse values ending up in AI. Here are some papers that I have been on that have addressed some of these issues: 1, 2, 3, 4. And here is another relevant paper: 1, and very relevant project 2.

2
Yarrow Bouchard 🔸
Thanks for sharing the papers. Some of those look really interesting. I’ll try to remember to look at these again when I think of it and have time to absorb them.  What do you think of the Arch Mission Foundation's Nanofiche archive on the Moon? Wouldn’t a global totalitarian government — or a global government of any kind — require advanced technology and a highly developed, highly organized society? So, this implies a high level of recovery from a collapse, but, then, why would global totalitarianism be more likely in such a scenario of recovery than it is right now?  I have personally never bought the idea of “value lock-in” for AGI. It seems like an idea inherited from the MIRI worldview, which is a very specific view on AGI with some very specific and contestable assumptions of what AGI will be like and how it will be built. For instance, the concept of “value lock-in” wouldn’t apply to AGI created through human brain emulation. And for other technological paradigms that could underlie AGI, are they like human brain emulation in this respect or unlike it? But this is starting to get off-topic for this post. 

I think where academic publishing would be most beneficial for increasing the rigour of EA’s thinking would be AGI.

AGI is a subset of global catastrophic risks, so EA-associated people have extensively academically published on AGI - I personally have about 10 publications related to AI.

 

Examples of scandalously bad epistemic practices include many people in EA apparently never once even hearing that an opposing point of view on LLMs scaling to AGI even exists, despite it being the majority view among AI experts, let alone understanding the reasons be

... (read more)
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Yarrow Bouchard 🔸
Somewhat different point being made here. Publications on existential risk from AI generally just make some assumptions about AGI with some probability, maybe deferring to some survey or forecast. What I meant is academic publishing about the object-level, technical questions around AGI. For example, what the potential obstacles are to LLMs scaling to AGI. Things like that.  That's interesting. I really don't get the impression that this concept is commonly discussed in EA or something people are widely aware of — at least not beyond a surface level. I searched for "paradigm" in the Daniel Kokotajlo interview and was able to find it. This is actually one of the only discussions of this question I've seen in EA beyond a surface gloss. So, thank you for that. I do think Daniel Kokotajlo's arguments are incredibly hand-wavy though. To give my opinionated, biased summary: * AI experts in the past said deep learning couldn't do certain things and now it can do them, so he doesn't trust experts predicting limits to deep learning progress involving things like data efficiency and continual learning * The amount of money being invested in AI will most likely within 5-10 years solve all those limits (such as data efficiency and continual learning) in any case * Continual learning or online learning will probably be solved relatively soon (no further explanation) * Continual learning or online learning probably isn't necessary for an intelligence explosion (no further explanation) * The job of AI researchers at OpenAI, Anthropic, DeepMind, etc. does not require human-level general intelligence but is automatable by relatively narrow and unpowerful AI systems without first solving limitations like data inefficiency and a lack of continual learning (extremely dubious and implausible, I don't buy this for a second)   I'd appreciate a pointer of what to look for in the Carl Schulman interviews, if you can remember a search term that might work. I searched for "paradigm
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