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I was referring to McNamara’s government work, forgot about his corporate job before then. I agree there’s some SpaceX to (even pre-McDonnell Douglas merger?) Boeing axis that feels useful, but I’m not sure what to call it or what you’d do to a field (like US defence) to perpetuate the SpaceX end of it, especially over events like handovers from Kelly Johnson to the next generation.
That most developed countries, and therefore most liberal democracies, are getting significantly worse over time at building physical things seems like a Big Problem (see e.g. here). I’m glad this topic got attention on LessWrong through this post.
The main criticism I expect could be levelled on this post is that it’s very non-theoretical. It doesn’t attempt a synthesis of the lessons or takeaways. Many quotes are presented but not analysed.
(To take one random thing that occurred to me: the last quote from Anduril puts significant blame on McNamara. From my reading of The Wizards of Armageddon, McNamara seems like a typical brilliant twentieth century hard-charging modernist technocrat. Now, he made lots of mistakes, especially in the direction of being too quantitative / simplistic in the sorts of ways that Seeing Like a State dunks on. But say the rule you follow is “appoint some hard-charging brilliant technocrat and give them lots of power”; all of McNamara, Kelly Johnson, and Leslie Groves might seem very good by this light, even though McNamara’s (claimed) effect was to destroy the Groves/Johnson type of competence in US defence. How do you pick the Johnsons and Groveses over the McNamaras? What’s the difference between the culture that appoints McNamaras and one that appoints Groveses and Johnsons? More respect for hands-down engineering? Less politics, more brute need for competence and speed due to a war? Is McNamara even the correct person to blame here? Is the type of role that McNamara was in just fundamentally different from the Groves and Johnson roles such that the rules for who does well in the latter don’t apply to the former?)
(I was also concerned about the highly-upvoted critical comment, though it seems like Jacob did address the factual mistakes pointed out there.)
However, I think the post is very good and is in fact better off as a bunch of empirical anecdotes than attempting a general theory. Many things are best learnt by just being thrown a set of case studies. Clearly, something was being done at Skunk Works that the non-SpaceX American defence industry currently does not do. Differences like this are often hard-to-articulate intangible cultural stuff, and just being temporarily immersed in stories from the effective culture is often at least as good as an abstract description of what the differences were. I also appreciated the level of empiricism where Jacob was willing to drill down to actual primary sources like the rediscovered Empire State Building logbook.
This post rings true to me because it points in the same direction as many other things I’ve read on how you cultivate ideas. I’d like more people to internalise this perspective, since I suspect that one of the bad trends in the developed world is that it keeps getting easier and easier to follow incentive gradients, get sucked into an existing memeplex that stops you from thinking your own thoughts, and minimise the risks you’re exposed to. To fight back against this, ambitious people need to have in their heads some view of how uncomfortable chasing of vague ideas without immediate reward can be the best thing you can do, as a counter-narrative to the temptation of more legible opportunities.
In addition to Paul Graham’s essay that this post quotes, some good companion pieces include Ruxandra Teslo on the scarcity and importance of intellectual courage (emphasising the courage requirement), this essay (emphasising motivation and persistence), and this essay from Dan Wang (emphasising the social pulls away from the more creative paths).
It’s striking that there are so few concrete fictional descriptions of realistic AI catastrophe, despite the large amount of fiction in the LessWrong canon. The few exceptions, like Gwern’s here or Gabe’s here, are about fast take-offs and direct takeover.
I think this is a shame. The concreteness and specificity of fiction make it great for imagining futures, and its emotional pull can help us make sense of the very strange world we seem to be heading towards. And slower catastrophes, like Christiano’s What failure looks like, are a large fraction of a lot of people’s p(doom), despite being less cinematic.
One thing that motivated me in writing this was that Bostrom’s phrase “a Disneyland without children” seemed incredibly poetic. On first glance it’s hard to tell a compelling or concrete story about gradual goodharting: “and lo, many actors continued to be compelled by local incentives towards collective loss of control …”—zzzzz … But imagine a technological and economic wonderland rising, but gradually disfiguring itself as it does so, until you have an edifice of limitless but perverted plenty standing crystalline against the backdrop of a grey dead world—now that is a poetic tragedy. And that’s what I tried to put on paper here.
Did it work? Unclear. On the literary level, I’ve had people tell me they liked it a lot. I’m decently happy with it, though I think I should’ve cut it down in length a bit more.
On the worldbuilding, I appreciated being questioned on the economic mechanics in the comments, and I think my exploration of this in the comments is a decent stab at what I think is a neglected set of questions about how much the current economy being fundamentally grounded in humans limits the scope of economic-goodharting catastrophes. Recently, I discovered earlier exploration of very similar questions in Scott Alexander’s 2016 “Ascended economy?”, and by Andrew Critch here. I also greatly appreciated Andrew Critch’s recent (2024) post raising very similar concerns about “extinction by industrial dehumanization”.
I continue to hope that more people work on this, and that this piece can help by concretising this class of risks in people’s minds (I think it is very hard to get people to grok a future scenario and care about it unless there is some evocative description of it!).
I’d also hope there was some way to distribute this story more broadly than just on LessWrong and my personal blog. Ted Chiang and the Arrival movie got lots of people exposed to the principle of least action—no small feat. It’s time for the perception of AI risk to break out of decades of Terminator comparisons, and move towards a basket of good fictional examples that memorably demonstrate subtle concepts.
Really like the song! Best AI generation I’ve heard so far. Though I might be biased since I’m a fan of Kipling’s poetry: I coincidentally just memorised the source poem for this a few weeks ago, and also recently named my blog after a phrase from Hymn of Breaking Strain (which was already nicely put to non-AI music as part of Secular Solstice).
I noticed you had added a few stanzas of your own:
As the Permian Era ended, we were promised a Righteous Cause,
To fight against Oppression or take back what once was ours.
But all the Support for our Troops didn’t stop us from losing the war
And the Gods of the Copybook Headings said “Be careful what you wish for.”In Scriptures old and new, we were promised the Good and the True
By heeding the Authorities and shunning the outcast few
But our bogeys and solutions were as real as goblins and elves
And the Gods of the Copybook Headings said “Learn to think for yourselves.”Kipling’s version has a particular slant to which vices it disapproves of, so I appreciate the expansion. The second stanza is great IMO, but the first stanza sounds a bit awkward in places. I had some fun messing with it:
As the Permian Era ended, we were promised the Righteous Cause.
In the fight against Oppression, we could ignore our cherished Laws,
Till righteous rage and fury made all rational thought uncouth.
And the Gods of the Copybook Headings said “The crowd is not the truth”
The AI time estimates are wildly high IMO, across basically every category. Some parts are also clearly optional (e.g. spending 2 hours reviewing). If you know what you want to research, writing a statement can be much shorter. I have previously applied to ML PhDs in two weeks and gotten an offer. The recommendation letters are the longest and most awkward to request at such notice, but two weeks isn’t obviously insane, especially if you have a good relationship with your reference letter writers (many students do things later than is recommended, no reference letter writer in academia will be shocked by this).
If you apply in 2025 December, you would start in 2026 fall. That is a very very long time from now. I think the stupidly long application cycle is pure dysfunction from academia, but you still need to take it into account.
(Also fyi, some UK programs have deadlines in spring if you can get your own funding)
You have restored my faith in LessWrong! I was getting worried that despite 200+ karma and 20+ comments, no one had actually nitpicked the descriptions of what actually happens.
The zaps of light are diffraction limited.
In practice, if you want the atmospheric nanobots to zap stuff, you’ll need to do some complicated mirroring because you need to divert sunlight. And it’s not one contiguous mirror but lots of small ones. But I think we can still model this as basic diffraction with some circular mirror / lens.
Intensity , where is the total power of sunlight falling on the mirror disk, is the radius of the Airy disk, and is an efficiency constant I’ve thrown in (because of things like atmospheric absorption (Claude says, somewhat surprisingly, this shouldn’t be ridiculuously large), and not all the energy in the diffraction pattern being in the Airy disk (about 84% is, says Claude), etc.)
Now, , where is the diameter of the mirror configuration, is the solar irradiance. And , where is the focal length (distance from mirror to target), and the angular size of the central spot.
So we have , so the required mirror configuration radius .
Plugging in some reasonable values like m (average incoming sunlight—yes the concentration suffers a bit because it’s not all this wavelength), W/m^2 (the level of an industrial laser that can cut metal), m (lower stratosphere), W/m^2 (solar irradiance), and a conservative guess that 99% of power is wasted so , we get m (and the resulting beam is about 3mm wide).
So a few dozen metres of upper atmosphere nanobots should actually give you a pretty ridiculous concentration of power!
(I did not know this when I wrote the story; I am quite surprised the required radius is this ridiculously tiny. But I had heard of the concept of a “weather machine” like this from the book Where is my flying car?, which I’ve reviewed here, which suggests that this is possible.)
Partly because it’s hard to tell between an actual animal and a bunch of nanobots pretending to be an animal. So you can’t zap the nanobots on the ground without making the ground uninhabitable for humans.
I don’t really buy this, why is it obvious the nanobots could pretend to be an animal so well that it’s indistinguishable? Or why would targeted zaps have bad side-effects?
The “California red tape” thing implies some alignment strategy that stuck the AI to obey the law, and didn’t go too insanely wrong despite a superintelligence looking for loopholes
Yeah, successful alignment to legal compliance was established without any real justification halfway through. (How to do this is currently an open technical problem, which, alas, I did not manage to solve for my satirical short story.)
Convince humans that dyson sphere are pretty and don’t block the view?
This is a good point, especially since high levels of emotional manipulation was an established in-universe AI capability. (The issue described with the Dyson sphere was less that it itself would block the view, and more that building it would require dismantling the planets in a way that ruins the view—though now I’m realising that “if the sun on Earth is blocked, all Earthly views are gone” is a simpler reason and removes the need for building anything on the other planets at all.)
There is also no clear explanation of why someone somewhere doesn’t make a non-red-taped AI.
Yep, this is a plot hole.
Do the stories get old? If it’s trying to be about near-future AI, maybe the state-of-the-art will just obsolete it. But that won’t make it bad necessarily, and there are many other settings than 2026. If it’s about radical futures with Dyson spheres or whatever, that seems like at least a 2030s thing, and you can easily write a novel before then.
Also, I think it is actually possible to write pretty fast. 2k/day is doable, which gets you a good length novel in 50 days; even x3 for ideation beforehand and revising after the first draft only gets you to 150 days. You’d have to be good at fiction beforehand, and have existing concepts to draw on in your head though
Good list!
I personally really like Scott Alexander’s Presidential Platform, it hits the hilarious-but-also-almost-works spot so perfectly. He also has many Bay Area house party stories in addition to the one you link (you can find a bunch (all?) linked at the top of this post). He also has this one from a long time ago, which has one of the best punchlines I’ve read.
Thanks for advertising my work, but alas, I think that’s much more depressing than this one.
Could make for a good Barbie <> Oppenheimer combo though?
Agreed! Transformative AI is hard to visualise, and concrete stories / scenarios feel very lacking (in both disasters and positive visions, but especially in positive visions).
I like when people try to do this—for example, Richard Ngo has a bunch here, and Daniel Kokotajlo has his near-prophetic scenario here. I’ve previously tried to do it here (going out with a whimper leading to Bostrom’s “disneyland without children” is one of the most poetic disasters imaginable—great setting for a story), and have a bunch more ideas I hope to get to.
But overall: the LessWrong bubble has a high emphasis on radical AI futures, and an enormous amount of fiction in its canon (HPMOR, Unsong, Planecrash). I keep being surprised that so few people combine those things.
I did not actually consider this, but that is a very reasonable interpretation!
(I vaguely remember reading some description of explicitly flat-out anthropic immortality saving the day, but I can’t seem to find it again now)
I’ve now posted my entries on LessWrong:
I’d also like to really thank the judges for their feedback. It’s a great luxury to be able to read many pages of thoughtful, probing questions about your work. I made several revisions & additions (and also split the entire thing into parts) in response to feedback, which I think improved the finished sequence a lot, and wish I had had the time to engage even more with the feedback.
Sorry about that, fixed now
[...] instead I started working to get evals built, especially for situational awareness
I’m curious what happened to the evals you mention here. Did any end up being built? Did they cover, or plan to cover, any ground that isn’t covered by the SAD benchmark?
On a meta level, I think there’s a difference in “model style” between your comment, some of which seems to treat future advances as a grab-bag of desirable things, and our post, which tries to talk more about the general “gears” that might drive the future world and its goodness. There will be a real shift in how progress happens when humans are no longer in the loop, as we argue in this section. Coordination costs going down will be important for the entire economy, as we argue here (though we don’t discuss things as galaxy-brained as e.g. Wei Dai’s related post). The question of whether humans are happy self-actualising without unbounded adversity cuts across every specific cool thing that we might get to do in the glorious transhumanist utopia.
Thinking about the general gears here matters. First, because they’re, well, general (e.g. if humans were not happy self-actualising without unbounded adversity, suddenly the entire glorious transhumanist utopia seems less promising). Second, because I expect that incentives, feedback loops, resources, etc. will continue mattering. The world today is much wealthier and better off than before industrialisation, but the incentives / economics / politics / structures of the industrial world let you predict the effects of it better than if you just modelled it as “everything gets better” (even though that actually is a very good 3-word summary). Of course, all the things that directly make industrialisation good really are a grab-bag list of desirable things (antibiotics! birth control! LessWrong!). But there’s structure behind that that is good to understand (mechanisation! economies of scale! science!). A lot of our post is meant to have the vibe of “here are some structural considerations, with near-future examples”, and less “here is the list of concrete things we’ll end up with”. Honestly, a lot of the reason we didn’t do the latter more is because it’s hard.
Your last paragraph, though, is very much in this more gears-level-y style, and a good point. It reminds me of Eliezer Yudkowsky’s recent mini-essay on scarcity.
Regarding:
In my opinion you are still shying away from discussing radical (although quite plausible) visions. I expect the median good outcome from superintelligence involves everyone being mind uploaded / living in simulations experiencing things that are hard to imagine currently. [emphasis added]
I agree there’s a high chance things end up very wild. I think there’s a lot of uncertainty about what timelines that would happen under; I think Dyson spheres are >10% likely by 2040, but I wouldn’t put them >90% likely by 2100 even conditioning on no radical stagnation scenario (which I’d say are >10% likely on their own). (I mention Dyson spheres because they seem more a raw Kardashev scale progress metric, vs mind uploads which seem more contingent on tech details & choices & economics for whether they happen)
I do think there’s value in discussing the intermediate steps between today and the more radical things. I generally expect progress to be not-ridiculously-unsmooth, so even if the intermediate steps are speedrun fairly quickly in calendar time, I expect us to go through a lot of them.
I think a lot of the things we discuss, like lowered coordination costs, AI being used to improve AI, and humans self-actualising, will continue to be important dynamics even into the very radical futures.
Re your specific list items:
Listen to new types of music, perfectly designed to sound good to you.
Design the biggest roller coaster ever and have AI build it.
Visit ancient Greece or view all the most important events of history based on superhuman AI archeology and historical reconstruction.
Bring back Dinosaurs and create new creatures.
Genetically modify cats to play catch.
Design buildings in new architectural styles and have AI build them.
Use brain computer interfaces to play videogames / simulations that feel 100% real to all senses, but which are not constrained by physics.
Go to Hogwarts (in a 100% realistic simulation) and learn magic and make real (AI) friends with Ron and Hermione.
These examples all seem to be about entertainment or aesthetics. Entertainment and aesthetics things are important to get right and interesting. I wouldn’t be moved by any description of a future that centred around entertainment though, and if the world is otherwise fine, I’m fairly sure there will be good entertainment.
To me, the one with the most important-seeming implications is the last one, because that might have implications for what social relationships exist and whether they are mostly human-human or AI-human or AI-AI. We discuss why changes there are maybe risky in this section.
Use AI as the best teacher ever to learn maths, physics and every subject and language and musical instruments to super-expert level.
We discuss this, though very briefly, in this section.
Take medication that makes you always feel wide awake, focused etc. with no side effects.
Engineer your body / use cybernetics to make yourself never have to eat, sleep, wash, etc. and be able to jump very high, run very fast, climb up walls, etc.
Modify your brain to have better short term memory, eidetic memory, be able to calculate any arithmetic super fast, be super charismatic.
I think these are interesting and important! I think there isn’t yet a concrete story for why AI in particular enables these, apart from the general principle that sufficiently good AI will accelerate all technology. I think there’s unfortunately a chance that direct benefits to human biology lag other AI effects by a lot, because they might face big hurdles due to regulation and/or getting the real-world data the AI needs. (Though also, humans are willing to pay a lot for health, and rationally should pay a lot for cognitive benefits, so high demand might make up for this).
Ask AI for way better ideas for this list.
I think the general theme of having the AIs help us make more use of AIs is important! We talk about it in general terms in the “AI is the ultimate meta-technology” section.
Thanks for the review! Curious what you think the specific fnords are—the fact that it’s very space-y?
What do you expect the factories to look like? I think an underlying assumption in this story is that tech progress came to a stop on this world (presumably otherwise it would be way weirder, and eventually spread to space).