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We mention the threat of coups—and Davidson et. al.'s paper on it—several times.
Regarding the weakness or slow-actingness of economic effects: it is true that the fundamental thing that forces the economic incentives to percolate to the surface and actually have an effect is selection pressure, and selection pressure is often slow-acting. However: remember that the time that matters is not necessarily calendar time.
- Most basically, the faster the rate of progress and change, the faster selection pressures operate.
- As MacInnes et. al. point out in Anarchy as Architect, the effects of selection pressures often don't manifest for a long time, but then appear suddenly in times of crisis—for example, the World Wars leading to a bunch of industrialization-derived state structure changes happening very quickly. The more you believe that takeoff will be chaotic and involve crises and tests of institutional capacity, the more you should believe that unconscious selection pressures will operate quickly.
- You don't need to wait for unconscious selection to work, if the agents in charge of powerful actors can themselves plan and see the writing on the wall. And the more planning capacity you add into the world (a default consequence of AI!), the more effectively you should expect competing agents (that do not coordinate) to converge on the efficient outcome.
Of course, it's true that if takeoff is fast enough then you might get a singleton and different strategies apply—though of course singletons (whether human organizations or AIs) immediately create vast risk if they're misaligned. And if you have enough coordination, then you can in fact avoid selection pressures (but a world with such effective coordination seems to be quite an alien world from ours or any that historically existed, and unlikely to be achieved in the short time remaining until powerful AI arrives, unless some incredibly powerful AI-enabled coordination tech arrives quickly). But this requires not just coordination, but coordination between well-intentioned actors who are not corrupted by power. If you enable perfect coordination between, say, the US and Chinese government, you might just get a dual oligarchy controlling the world and ruling over everyone else, rather than a good lightcone.
If humanity loses control and it's not due to misaligned AI, it's much more likely to be due to an AI enabled coup, AI propaganda or AI enabled lobbying than humans having insufficient economic power.
AI-enabled coups and AI-enabled lobbying all get majorly easier and more effective the more humanity's economic role have been erased. Fixing them is also all part of maintaining the balance of power in society.
I agree that AI propaganda, and more generally AI threats to the information environment & culture, are a big & different deal that intelligence-curse.ai don't address except in passing. You can see the culture section of Gradual Disempowerment (by @Jan_Kulveit @Raymond D & co.) for more on this.
There's a saying "when all you have is a hammer, everything looks like a nail" that I think applies here. I'm bearish on [approaches] opposed to multi-disciplinary approaches that don't artificially inflate particular factors.
I share the exact same sentiment, but for me it applies in reverse. Much "basic" alignment discourse seems to admit exactly two fields—technical machine learning and consequentialist moral philosophy—while sweeping aside considerations about economics, game theory, politics, social changes, institutional design, culture, and generally the lessons of history. A big part of what intelligence-curse.ai tries to do is take this more holistic approach, though of course it can't focus on everything, and in particular neglects the culture / info environment / memetics side. Things that try to be even more holistic are my scenario and Gradual Disempowerment.
I don’t believe the standard story of the resource curse.
What do you think is the correct story for the resource curse?
I find the scenario implausible.
This is not a scenario, it is a class of concerns about the balance of power and economic misalignment that we expect to be a force in many specific scenarios. My actual scenario is here.
The “social-freeze and mass-unemployment” narrative seems to assume that AI progress will halt exactly at the point where AI can do every job but is still somehow not dangerous.
We do not assume AI progress halts at that point. We say several times that we expect AIs to keep improving. They will take the jobs, and they will keep on improving beyond that. The jobs do not come back if the AI gets even smarter. We also have an entire section dedicated to mitigating the risks of AIs that are dangerous, because we believe that is a real and important threat.
More directly, full automation of the economy would mean that AI can perform every task in companies already capable of creating military, chemical, or biological threats. If the entire economy is automated, AI must already be dangerously capable.
Exactly!
I expect reality to be much more dynamic, with many parties simultaneously pushing for ever-smarter AI while understanding very little about its internals.
"Reality will be dynamic, with many parties simultaneously pushing for ever-smarter AI [and their own power & benefit] while understanding very little about [AI] internals [or long-term societal consequences]" is something I think we both agree with.
I expect that approaching superintelligence without any deeper understanding of the internal cognition this way will give us systems that we cannot control and that will get rid of us. For these reasons, I have trouble worrying about job replacement.
If we hit misaligned superintelligence in 2027 and all die as a result, then job replacement, long-run trends of gradual disempowerment, and the increased chances of human coup risks indeed do not come to pass. However, if we don't hit misaligned superintelligence immediately, and instead some humans pull a coup with the AIs, or the advanced AIs obsolete humans very quickly (very plausible if you think AI progress will be fast!) and the world is now states battling against each other with increasingly dangerous AIs while feeling little need to care for collateral damage to humans, then it sure will have been a low dignity move from humanity if literally no one worked on those threat models!
You also seem to avoid mentioning the extinction risk in this text.
The audience is primarily not LessWrong, and the arguments for working on alignment & hardening go through based on merely catastrophic risks (which we do mention many times). Also, the series is already enough of an everything-bagel as it is.
The scenario does not say that AI progress slows down. What I imagined to be happening is that after 2028 or so, there is AI research being done by AIs at unprecedented speeds, and this drives raw intelligence forward more and more, but (1) the AIs still need to run expensive experiments to make progress sometimes, and (2) basically nothing is bottlenecked by raw intelligence anymore so you don't really notice it getting even better.
I will admit I'm not an expert here. The intuition behind this is that if you grant extreme performance at mathsy things very soon, it doesn't seem unreasonable that the AIs will make some radical breakthrough in the hard sciences surprisingly soon, while still being bad at many other things. In the scenario, note that it's a "mathematical framework" (implicitly a sufficiently big advance in what we currently have such that it wins a Nobel) but not the final theory of everything, and it's explicitly mentioned empirical data bottlenecks it.
Thanks for these speculations on the longer-term future!
while I do think Mars will be exploited eventually, I expect the moon to be first for serious robotics effort
Maybe! My vague Claude-given sense is that the Moon is surprisingly poor in important elements though.
not being the fastest amongst them all (because replicating a little better will usually only get a little advantage, not an utterly dominant one), combined with a lot of values being compatible with replicating fast, so value alignment/intent alignment matters more than you think
This is a good point! However, more intelligence in the world also means we should expect competition to be tighter, reducing the amount of slack by which you can deviate from the optimal. In general, I can see plausible abstract arguments for the long-run equilibrium being either Hansonian zero-slack Malthusian competition or absolute unalterable lock-in.
Given no nationalization of the companies has happened, and they still have large freedoms of action, it's likely that Google Deepmind, OpenAI and Anthropic have essentially supplanted the US as the legitimate government, given their monopolies on violence via robots.
I expect the US government to be competent enough to avoid being supplanted by the companies. I think politicians, for all their flaws, are pretty good at recognising a serious threat to their power. There's also only one government but several competing labs.
(Note that the scenario doesn't mention companies in the mid and late 2030s)
the fact that EA types got hired to some of the most critical positions on AI was probably fairly critical in this timeline for preventing the worst outcomes from the intelligence curse from occurring.
In this timeline, a far more important thing is the sense among American political elite that they are freedom-loving people and that they should act in accordance with that, and a similar sense among Chinese political elite that they are a civilised people and that Chinese civilisational continuity is important. A few EAs in government, while good, will find it difficult to match the impact of the cultural norms that a country's leaders inherit and that proscribe their actions.
For example: I've been reading Christopher Brown's Moral Capital recently, which looks at how opposition to slavery rose to political prominence in 1700s Britain. It claims that early strong anti-slavery attitudes were more driven by a sense that slavery was insulting to Britons' sense of themselves as a uniquely liberal people, than by arguments about slave welfare. At least in that example, the major constraint on the treatment of a powerless group of people seems to have been in large part the political elite managing its own self-image.
I built this a few months ago: https://github.com/LRudL/devcon
Definitely not production-ready and might require some "minimal configuration and tweaking" to get working.
Includes a "device constitution" that you set; if you visit a website, Claude will judge whether the page follows that written document, and if not it will block you, and the only way past it is winning a debate with it about why your website visit is in-line with your device constitution.
I found it too annoying but some of my friends liked it.
However, I think there is a group of people who over-optimize for Direction and neglect the Magnitude. Increasing Magnitude often comes with the risk of corrupting the Direction. For example, scaling fast often makes it difficult to hire only mission-aligned people, and it requires you to give voting power to investors that prioritizes profit. To increase Magnitude can therefore feel risky, what if I end up working at something that is net-negative for the world? Therefore it might be easier for one's personal sanity to optimize for Direction, to do something that is unquestionably net-positive. But this is the easy way out, and if you want to have the highest expected value of your Impact, you cannot disregard Magnitude.
You talk here about an impact/direction v ambition/profit tradeoff. I've heard many other people talking about this tradeoff too. I think it's overrated; in particular, if you're constantly having to think about it, that's a bad sign.
- It's rare that you have a continuous space of options between lots of impact and low profit, and low/negative impact and high profit.
- If you do have such a continuous space of options then I think you are often just screwed and profit incentives will win.
- The really important decision you make is probably a discrete choice: do you start an org trying to do X, or an org trying to do Y? Usually you can't (and even if you can, shouldn't) try to interpolate between these things, and making this high-level strategy call will probably shape your impact more than any later finetuning of parameters within that strategy.
- Often, the profit incentives point towards the more-obvious, gradient-descent-like path, which is usually very crowded and leads to many "mediocre" outcomes (e.g. starting a $10M company), but the biggest things come from doing "Something Else Which Is Not That" (as is said in dath ilan). For example, SpaceX (ridiculously hard and untested business proposition) and Facebook (started out seeing very small and niche and with no clue of where the profit was).
Instead, I think the real value of doing things that are startup-like comes from:
- The zero-to-one part of Peter Thiel's zero-to-one v one-to-n framework: the hardest, progress-bottlenecking things usually look like creating new things, rather than scaling existing things. For example, there is very little you can do today in American politics that is as impactful or reaches as deep into the future as founding America in the first place.
- In the case of AI safety: neglectedness. Everyone wants to work at a lab instead, humans are too risk averse in general, etc. (I've heard many people in AI safety say that neglectedness is overrated. There are arguments like this one that replaceability/neglectedness considerations aren't that major: job performance is heavy-tailed, hiring is hard for orgs, etc. But such arguments seem like weirdly myopic parameter-fiddling, at least when the alternative is zero-to-one things like discussed above. Starting big things is in fact big. Paradigm shifts matter because they're the frame that everything else takes place in. You either see this or you don't.)
- To the extent you think the problem is about economic incentives or differential progress, have you considered getting your hands dirty and trying to change the actual economy or the direction of the tech tree? There are many ways to do this, including some types of policy and research. But I think the AI safety scene has a cultural bias towards things that look like research or information-gathering, and away from being "builders" in the Silicon Valley sense. One of the things that Silicon Valey does get right is that being a builder is very powerful. If the AI debate comes down to a culture/influence struggle between anti-steering, e/acc-influenced builder types and pro-steering EA-influenced academic types, it doesn't look good for the world.
1Thanks for the heads-up, that looks very convenient. I've updated the post to link to this instead of the scraper repo on GitHub.
As far as I know, my post started the recent trend you complain about.
Several commenters on this thread (e.g. @Lucius Bushnaq here and @MondSemmel here) mention LessWrong's growth and the resulting influx of uninformed new users as the likely cause. Any such new users may benefit from reading my recently-curated review of Planecrash, the bulk of which is about summarising Yudkowsky's worldview.
i continue to feel so confused at what continuity led to some users of this forum asking questions like, "what effect will superintelligence have on the economy?" or otherwise expecting an economic ecosystem of superintelligences
If there's decision-making about scarce resources, you will have an economy. Even superintelligence does not necessarily imply infinite abundance of everything, starting with the reason that our universe only has so many atoms. Multipolar outcomes seem plausible under continuous takeoff, which the consensus view in AI safety (as I understand it) sees as more likely than fast takeoff. I admit that there are strong reasons for thinking that the aggregate of a bunch of sufficiently smart things is agentic, but this isn't directly relevant for the concerns about humans within the system in my post.
a value-aligned superintelligence directly creates utopia
In his review of Peter Singer's commentary on Marx, Scott Alexander writes:
[...] Marx was philosophically opposed, as a matter of principle, to any planning about the structure of communist governments or economies. He would come out and say it was irresponsible to talk about how communist governments and economies will work. He believed it was a scientific law, analogous to the laws of physics, that once capitalism was removed, a perfect communist government would form of its own accord. There might be some very light planning, a couple of discussions, but these would just be epiphenomena of the governing historical laws working themselves out.
Peter Thiel might call this "indefinite optimism": delay all planning or visualisation because there's some later point where it's trusted things will all sort themselves out. Now, if you think that takeoff will definitely be extremely hard and the resulting superintelligence will effortlessly take over the world, then obviously it makes sense to focus on what that superintelligence will want to do. But what if takeoff lasts months or years or decades? (Note that there can be lots of change even within months if the stakes look extreme to powerful actors!) Aren't you curious about what an aligned superintelligence will end up deciding about society and humans? Are you so sure about the transition period being so short and the superintelligence being so unitary and multipolar outcomes being so unlikely that we'll never have to worry about problems downstream of the incentive issues and competitive pressures that I discuss (which Beren recently had an excellent post on)? Are you so sure that there is not a single interesting, a priori deducible fact about the superintelligent economy beyond "a singleton is in charge and everything is utopia"?
Thanks a lot for this post! I appreciate you taking the time to engage, I think your recommendations are good, and I agree with most of what you say. Some comments below.
Intelligence curse != Gradual disempowerment
The intelligence curse and GD are not equivalent. In particular, I expect @Jan_Kulveit & co. would see GD as a broader bucket including also various subtle forms of cultural misalignment (which tbc I think also matter!), whereas IC is more specifically about things downstream of economic (and hard power, and political power) incentives. (And I would see e.g. @Tom Davidson's AI-enabled coup risk work as a subset of IC, as representing the most sudden and dramatic way that IC incentives could play out)
On the stakes
I think if you follow the arguments, disempowerment of all humans is plausible, and disempowerment of the vast majority even more so. I agree that technical misalignment is more likely to lead to high casualty counts if it happens (and I think the technical misalignment --> x-risk pathway is possible and incredibly urgent to make progress on).
I think there's also a difference between working on mitigating very clear sequences of steps that lead to catastrophe (e.g. X --> Y --> everyone drops dead), and working on maintaining the basic premises that make things not broken (e.g. for the last 200 years when things have been getting much better, the incentives of power and humans have been remarkably correlated, and maybe we should try to not decorrelate them). The first is more obvious, but I think you should also be able to admit theories of change of the second type at least sufficiently that, for example, you would've decided to resist communism in the 1950s ("freedom good" is vague, and there wasn't yet consensus that market-based economies would provide better living standards in the long run, but it was still correct to bet against the communists if you cared about human welfare! basic liberalism is very powerful!).
The proposals
Yep, this is a big part of the future I'm excited to build towards.
Prioritization of proposals
I think there are two basic factors that affect uplift chances:
(More fundamentally, there's also the question of how high you think human/AI complementarity at cognitive skills to be—right now it's surprisingly high IMO)
I'm curious what your take on the basic Hayek point is?
I expect a track record of trying out some form of coordination at scale is really helpful for later getting it into government / into use by more "serious" actors. I think it's plausible that it's really hard to get governments to try any new coordination or governance mechanism before it's too late, but if you wanted to increase the odds, I think you should just very clearly be trying them out in practice.
I agree these are hard, and also like an area where it's unclear if cracking R&D automation to the point where we can hill-climb on ML performance metrics gets you AI that does non-fake work on these questions. I really want very good AI representatives that are very carefully aligned to individual people if we're going to have the AIs work on this.