Mikhail Samin's Shortform
post by Mikhail Samin (mikhail-samin) · 2023-02-07T15:30:24.006Z · LW · GW · 56 commentsContents
56 comments
56 comments
Comments sorted by top scores.
comment by Mikhail Samin (mikhail-samin) · 2025-02-01T18:49:13.641Z · LW(p) · GW(p)
Anthropic employees: stop deferring to Dario on politics. Think for yourself.
Do your company's actions actually make sense if it is optimizing for what you think it is optimizing for?
Anthropic lobbied against mandatory RSPs, against regulation, and, for the most part, didn't even support SB-1047. The difference between Jack Clark and OpenAI's lobbyists is that publicly, Jack Clark talks about alignment. But when they talk to government officials, there's little difference on the question of existential risk from smarter-than-human AI systems. They do not honestly tell the governments what the situation is like. Ask them yourself.
A while ago, OpenAI hired a lot of talent due to its nonprofit structure.
Anthropic is now doing the same. They publicly say the words that attract EAs and rats. But it's very unclear whether they institutionally care.
Dozens work at Anthropic on AI capabilities because they think it is net-positive to get Anthropic at the frontier, even though they wouldn't work on capabilities at OAI or GDM.
It is not net-positive.
Anthropic is not our friend. Some people there do very useful work on AI safety (where "useful" mostly means "shows that the predictions of MIRI-style thinking are correct and we don't live in a world where alignment is easy", not "increases the chance of aligning superintelligence within a short timeframe"), but you should not work there on AI capabilities.
Anthropic's participation in the race makes everyone fall dead sooner and with a higher probability.
Work on alignment at Anthropic if you must. I don't have strong takes on that. But don't do work for them that advances AI capabilities.
Replies from: Max Lee, jbash, nathan-helm-burger, Lanrian, AliceZ↑ comment by Knight Lee (Max Lee) · 2025-02-02T01:59:15.238Z · LW(p) · GW(p)
I think you should try to clearly separate the two questions of
- Is their work on capabilities a net positive or net negative for humanity's survival?
- Are they trying to "optimize" for humanity's survival, and do they care about alignment deep down?
I strongly believe 2 is true, because why on Earth would they want to make an extra dollar if misaligned AI kills them in addition to everyone else? Won't any measure of their social status be far higher after the singularity, if it's found that they tried to do the best for humanity?
I'm not sure about 1. I think even they're not sure about 1. I heard that they held back on releasing their newer models until OpenAI raced ahead of them.
You (and all the people who upvoted your comment) have a chance of convincing them (a little) in a good faith debate maybe. We're all on the same ship after all, when it comes to AI alignment.
PS: AI safety spending [? · GW] is only $0.1 billion while AI capabilities spending is $200 billion. A company which adds a comparable amount of effort on both AI alignment and AI capabilities should speed up the former more than the latter, so I personally hope for their success. I may be wrong, but it's my best guess...
Replies from: rhollerith_dot_com↑ comment by RHollerith (rhollerith_dot_com) · 2025-02-03T00:13:55.784Z · LW(p) · GW(p)
AI safety spending is only $0.1 billion while AI capabilities spending is $200 billion. A company which adds a comparable amount of effort on both AI alignment and AI capabilities should speed up the former more than the latter
There is very little hope IMHO in increasing spending on technical AI alignment because (as far as we can tell based on how slow progress has been on it over the last 22 years) it is a much thornier problem than AI capability research and because most people doing AI alignment research don't have a viable story about how they are going to stop any insights / progress they achieve from helping with AI capability research. I mean, if you have a specific plan that avoids these problems, then let's hear it, I am all ears, but advocacy in general of increasing work on technical alignment is counterproductive IMHO.
Replies from: Max Lee↑ comment by Knight Lee (Max Lee) · 2025-02-03T01:25:51.996Z · LW(p) · GW(p)
EDIT: thank you so much for replying to the strongest part of my argument, no one else tried to address it (despite many downvotes).
I disagree with the position that technical AI alignment research is counterproductive due to increasing capabilities, but I think this is very complicated and worth thinking about in greater depth.
Do you think it's possible, that your intuition on alignment research being counterproductive, is because you compared the plausibility of the two outcomes:
- Increasing alignment research causes people to solve AI alignment, and humanity survives.
- Increasing alignment research led to an improvement in AI capabilities, allowing AI labs to build a superintelligence which then kills humanity.
And you decided that outcome 2 felt more likely?
Well, that's the wrong comparison to make.
The right comparison should be:
- Increasing alignment research causes people to improve AI alignment, and humanity survives in a world where we otherwise wouldn't survive.
- Increasing alignment research led to an improvement in AI capabilities, allowing AI labs to build a superintelligence which then kills humanity in a world where we otherwise would survive.
In this case, I think even you would agree what P(1) > P(2).
P(2) is very unlikely because if increasing alignment research really would lead to such a superintelligence, and it really would kill humanity... then let's be honest, we're probably doomed in that case anyways, even without increasing alignment research.
If that really was the case, the only surviving civilizations would have had different histories, or different geographies (e.g. only a single continent with enough space for a single country), leading to a single government which could actually enforce an AI pause.
We're unlikely to live in a world so pessimistic that alignment research is counterproductive, yet so optimistic that we could survive without that alignment research.
Replies from: rhollerith_dot_com↑ comment by RHollerith (rhollerith_dot_com) · 2025-02-04T00:08:06.162Z · LW(p) · GW(p)
we're probably doomed in that case anyways, even without increasing alignment research.
I believe we're probably doomed anyways.
I think even you would agree what P(1) > P(2)
Sorry to disappoint you, but I do not agree.
Although I don't consider it quite impossible that we will figure out alignment, most of my hope for our survival is in other things, such as a group taking over the world and then using their power to ban AI research. (Note that that is in direct contradiction to your final sentence.) So for example, if Putin or Xi were dictator of the world, my guess is that there is a good chance he would choose to ban all AI research. Why? It has unpredictable consequences. We Westerners (particularly Americans) are comfortable with drastic change, even if that change has drastic unpredictable effects on society; non-Westerners are much more skeptical: there have been too many invasions, revolutions and peasant rebellions that have killed millions in their countries. I tend to think that the main reason Xi supports China's AI industry is to prevent the US and the West from superseding China and if that consideration were removed (because for example he had gained dictatorial control over the whole world) he'd choose to just shut it down (and he wouldn't feel that need to have a very strong argument for that shutting it down like Western decision-makers would: non-Western leader shut important things down all the time or at least they would if the governments they led had the funding and the administrative capacity to do so).
Of course Xi's acquiring dictatorial control over the whole world is extremely unlikely, but the magnitude of the technological changes and societal changes that are coming will tend to present opportunities for certain coalitions to gain and to keep enough power to shut AI research down worldwide. (Having power in all countries hosting leading-edge fabs is probably enough.) I don't think this ruling coalition necessarily need to believe that AI presents a potent risk of human extinction for them to choose to shut it down.
I am aware that some reading this will react to "some coalition manages to gain power over the whole world" even more negatively than to "AI research causes the extinction of the entire human race". I guess my response is that I needed an example of a process that could save us and that would feel plausible -- i.e., something that might actually happen. I hasten add that there might be other processes that save us that don't elicit such a negative reaction -- including processes the nature of which we cannot even currently imagine.
I'm very skeptical of any intervention that reduces the amount of time we have left in the hopes that this AI juggernaut is not really as potent a threat to us as it currently appears. I was much much less skeptical of alignment research 20 years ago, but since then a research organization has been exploring the solution space and the leader of that organization (Nate Soares) and its most senior researcher (Eliezer) are reporting that the alignment project is almost completely hopeless. Yes, this organization (MIRI) is kind of small, but it has been funded well enough to keep about a dozen top-notch researchers on the payroll and it has been competently led. Also, for research efforts like this, how many years the team had to work on the problem is more important than the size of the team, and 22 years is a pretty long time to end up with almost no progress other than some initial insights (around the orthogonality thesis, the fragility of value, convergent instrumental values, CEV as a solution to if the problem were solvable by the current generation of human beings.
OK, if I'm being fair and balanced, then I have to concede that it was probably only in 2006 (when Eliezer figured out how to write a long intellectually-dense blog post every day) or even only in 2008 (when Anna Salamon join the organization -- she was very good at recruiting and had a lot of energy to travel and to meet people) that Eliezer's research organization could start to pick and choose among a broad pool of very talented people, but still between 2008 and now is 17 years, which again is a long time for a strong team to fail to make even a decent fraction of the progress humanity would seem to need to make on the alignment problem if in fact the alignment problem is solvable by spending more money on it. It does not appear to me to be the sort of problem than can be solved with 1 or 2 additional insights; it seems a lot more like the kind of problem where insight 1 is needed, but before any mere human can find insight 1, all the researchers need to have already known insight 2, and to have any hope of finding insight 2, they all would have had to know insight 3, and so on.
Replies from: Max Lee↑ comment by Knight Lee (Max Lee) · 2025-02-04T03:31:11.751Z · LW(p) · GW(p)
I don't agree that the probability of alignment research succeeding is that low. 17 years or 22 years of trying and failing is strong evidence against it being easy, but doesn't prove that it is so hard that increasing alignment research is useless.
People worked on capabilities for decades, and never got anywhere until recently, when the hardware caught up, and it was discovered that scaling works unexpectedly well.
There is a chance that alignment research now might be more useful than alignment research earlier, though there is uncertainty in everything.
We should have uncertainty in the Ten Levels of AI Alignment Difficulty [LW · GW].
The comparison
It's unlikely that 22 years of alignment research is insufficient but 23 years of alignment research is sufficient.
But what's even more unlikely, is the chance that $200 billion on capabilities research plus $0.1 billion on alignment research is survivable, while $210 billion on capabilities research plus $1 billion on alignment research is deadly.
In the same way adding a little alignment research is unlikely to turn failure into success, adding a little capabilities research is unlikely to turn success into failure.
It's also unlikely that alignment effort is even deadlier than capabilities effort dollar for dollar. That would mean reallocating alignment effort into capabilities effort paradoxically slows down capabilities and saves everyone.
Even if you are right
Even if you are right that delaying AI capabilities is all that matters, Anthropic still might be a good thing.
Even if Anthropic disappeared, or never existed in the first place, the AI investors will continue to pay money for research, and the AI researchers will continue to do research for money. Anthropic was just the middleman.
If Anthropic never existed, the middlemen would consist of only OpenAI, DeepMind, Meta AI, and other labs. These labs will not only act as the middle man, but lobby against regulation far more aggressively than Anthropic, and may discredit the entire "AI Notkilleveryoneism" movement.
To continue existing at one of these middlemen, you cannot simply stop paying the AI researchers for capabilities research, otherwise the AI investors and AI customers will stop paying you in turn. You cannot stem the flow, you can only decide how much goes through you.
It's the old capitalist dilemma of "doing evil or getting out-competed by those who do."
For their part, Anthropic redirected some of that flow to alignment research, and took the small amount of precautions which they could afford to take. They were also less willing to publish capabilities research than other labs. That may be the best one can hope to accomplish against this unstoppable flow from the AI investors to AI researchers.
The small amount of precautions which Anthropic did take may have already costed them their first mover advantage. Had Anthropic raced ahead before OpenAI released ChatGPT, Anthropic may have stolen the limelight, got the early customers and investors, and been bigger than OpenAI.
Replies from: rhollerith_dot_com, rhollerith_dot_com↑ comment by RHollerith (rhollerith_dot_com) · 2025-02-05T00:11:29.545Z · LW(p) · GW(p)
But what's even more unlikely, is the chance that $200 billion on capabilities research plus $0.1 billion on alignment research is survivable, while $210 billion on capabilities research plus $1 billion on alignment research is deadly.
This assumes that alignment success is the mostly likely avenue to safety for humankind whereas like I said, I consider other avenues more likely. Actually there needs to be a qualifier on that: I consider other avenues more likely than the alignment project's succeeding while the current generation of AI researchers remain free to push capabilities: if the AI capabilities juggernaut could be stopped for 150 years, giving the human population time to get smarter and wiser, then alignment is likely (say p = .7) to succeed in my estimation. I am informed by Eliezer in his latest interview that such a success would probably use some technology other than deep learning to create the AI's capabilities; i.e., deep learning is particularly hard to align.
Central to my thinking is my belief that alignment is just a significantly harder problem than the problem of creating an AI capable of killing us all. Does any of the reasoning you do in your section "the comparision" change if you started believing that alignment is much much harder than creating a superhuman (unaligned) AI?
It will probably come as no great surprise that I am unmoved by the arguments I have seen (including your argument) that Anthropic is so much better than OpenAI that it helps the global situation for me to support Anthropic (if it were up to me, both would be shut down today if I couldn't delegate the decision to someone else and if I had to decide now with the result that there is no time for me to gather more information) but I'm not very certain and would pay attention to future arguments for supporting Anthropic or some other lab.
Thanks for engaging with my comments.
Replies from: Max Lee↑ comment by Knight Lee (Max Lee) · 2025-02-05T03:01:55.625Z · LW(p) · GW(p)
Thank you, I've always been curious about this point of view because a lot of people have a similar view to yours.
I do think that alignment success is the most likely avenue, but my argument doesn't require this assumption.
Your view isn't just that "alternative paths are more likely to succeed than alignment," but that "alternative paths are so much more likely to succeed than alignment, that the marginal capabilities increase caused by alignment research (or at least Anthropic), makes them unworthwhile."
To believe that alignment is that hopeless, there should be stronger proof than "we tried it for 22 years, and the prior probability of the threshold being between 22 years and 23 years is low." That argument can easily be turned around to argue why more alignment research is equally unlikely to cause harm (and why Anthropic is unlikely to cause harm). I also think multiplying funding can multiply progress (e.g. 4x funding 2x duration).
If you really want a singleton controlling the whole world (which I don't agree with), your most plausible path would be for most people to see AI risk as a "desperate" problem, and for governments under desperation to agree on a worldwide military which swears to preserve civilian power structures within each country.[1]
Otherwise, the fact that no country took over the world during the last centuries strongly suggests that no country will in the next few years, and this feels more solid than your argument that "no one figured out alignment in the last 22 years, so no one will in the next few years."
- ^
Out of curiosity, would you agree with this being the most plausible path, even if you disagree with the rest of my argument?
↑ comment by RHollerith (rhollerith_dot_com) · 2025-02-05T21:42:50.419Z · LW(p) · GW(p)
Out of curiosity, would you agree with this being the most plausible path, even if you disagree with the rest of my argument?
The most plausible story I can imagine quickly right now is the US and China fight a war and the US wins and uses some of the political capital from that win to slow down the AI project, perhaps through control over the world's leading-edge semiconductor fabs plus pressuring Beijing to ban teaching and publishing about deep learning (to go with a ban on the same things in the West). I believe that basically all the leading-edge fabs in existence or that will be built in the next 10 years are in the countries the US has a lot of influence over or in China. Another story: the technology for "measuring loyalty in humans" gets really good fast, giving the first group to adopt the technology so great an advantage that over a few years the group gets control over the territories where all the world's leading-edge fabs and most of the trained AI researchers are.
I want to remind people of the context of this conversation: I'm trying to persuade people to refrain from actions that on expectation make human extinction arrive a little quicker because most of our (sadly slim) hope for survival IMHO flows from possibilities other than our solving (super-)alignment in time.
Replies from: Max Lee↑ comment by Knight Lee (Max Lee) · 2025-02-05T21:58:17.078Z · LW(p) · GW(p)
I would go one step further and argue you don't need to take over territory to shut down the semiconductor supply chain, if enough large countries believed AI risk was a desperate problem they could convince and negotiate the shutdown of the supply chain.
Shutting down the supply chain (and thus all leading-edge semiconductor fabs) could slow the AI project by a long time, but probably not "150 years" since the uncooperative countries will eventually build their own supply chain and fabs.
Replies from: rhollerith_dot_com↑ comment by RHollerith (rhollerith_dot_com) · 2025-02-06T21:44:28.636Z · LW(p) · GW(p)
The ruling coalition can disincentivize the development of a semiconductor supply chain outside the territories it controls by selling world-wide semiconductors that use "verified boot" technology to make it really hard to use the semiconductor to run AI workloads similar to how it is really hard even for the best jailbreakers to jailbreak a modern iPhone.
Replies from: Max Lee↑ comment by Knight Lee (Max Lee) · 2025-02-06T23:46:49.689Z · LW(p) · GW(p)
That's a good idea! Even today it may be useful for export controls (depending on how reliable it can be made).
The most powerful chips might be banned from export, and have "verified boot" technology inside in case they are smuggled out.
The second most powerful chips might be only exported to trusted countries, and also have this verified boot technology in case these trusted countries end up selling them to less trusted countries who sell them yet again.
↑ comment by RHollerith (rhollerith_dot_com) · 2025-02-05T03:04:09.205Z · LW(p) · GW(p)
People worked on capabilities for decades, and never got anywhere until recently, when the hardware caught up, and it was discovered that scaling works unexpectedly well.
If I believed that, then maybe I'd believe (like you seem to do) that there is no strong reason to believe that alignment project cannot be finished successfully before the capabilities project creates an unaligned super-human AI. I'm not saying scaling and hardware improvement have not been important: I'm saying they were not sufficient: algorithmic improvements were quite necessary for the field to arrive at anything like ChatGPT, and at least as early as 2006, there were algorithm improvements that almost everyone in the machine-learning field recognized as breakthrough or important insights. (Someone more knowledgeable about the topic might be able to push the date back into the 1990s or earlier.)
After the publication 19 years ago by Hinton et al of "A Fast Learning Algorithm for Deep Belief Nets", basically all AI researchers recognized it as a breakthrough. Building on it, was AlexNet in 2012, again recognized as an important breakthrough by essentially everyone in the field (and if some people missed it then certainly generational adversarial networks, ResNets and AlphaGo convinced them). AlexNet was the first deep model trained on GPUs, a technique essential for the major breakthrough in 2017 reported in the paper "Attention is all you need".
In contrast, we've seen nothing yet in the field of alignment that is as unambiguously a breakthrough as is the 2006 paper by Hinton et al or 2012's AlexNet or (emphatically) the 2017 paper "Attention is all you need". In fact I suspect that some researchers could tell that the attention mechanism reported by Bahdanau et al in 2015 or the Seq2Seq models reported on by Sutskever et al in 2014 was evidence that deep-learning language models were making solid progress and that a blockbuster insight like "attention is all you need" is probably only a few years away.
The reason I believe it is very unlikely for the alignment research project to succeed before AI kills us all is that in machine learning or the deep-learning subfield of machine learning, what was recognized by essentially everyone in the field as a minor or major breakthrough has occurred every few years. Many of these breakthrough rely on earlier breakthroughs (i.e., it is very unlikely for the sucessive breakthrough to have occurred if the earlier breakthrough had not been disseminated to the community of researcher). During this time, despite very talented people working on it, there has been zero results in alignment research that the entire field of alignment researchers would consider a breakthrough. That does not mean it is impossible for the alignment project to be finished in time, but it does IMO make it critical for the alignment project to be prosecuted in such a way that it does not inadvertently assist the capabilities project.
Yes, much more money has been spent on capability research the last 20 years than on alignment research, but money doesn't help all that much to speed up research in which to have any hope of solving the problem, the researchers need insight X or X2, and to have any hope of arriving at insight X, they need insights Y and Y2, and to have much hope at all of arriving at Y, they need insight Z.
Replies from: Max Lee↑ comment by Knight Lee (Max Lee) · 2025-02-05T03:17:50.058Z · LW(p) · GW(p)
Even if building intelligence requires solving many many problems, preventing that intelligence from killing you may just require solving a single very hard problem. We may go from having no idea to having a very good idea.
I don't know. My view is that we can't be sure of these things.
↑ comment by Nathan Helm-Burger (nathan-helm-burger) · 2025-02-02T02:57:13.709Z · LW(p) · GW(p)
Our worldviews do not match, and I fail to see how yours makes sense. Even when I relax my predictions about the future to take in a wider set of possible paths... I still don't get it.
AI is here. AGI is coming whether you like it or not. ASI will probably doom us.
Anthropic, as an org, seems to believe that there is a threshold of power beyond which creating an AGI more powerful than that would kill us all. OpenAI may believe this also, in part, but it seems like their expectation of where that threshold is is further away than mine. Thus, I think there is a good chance they will get us all killed. There is substantial uncertainty and risk around these predictions.
Now, consider that, before AGI becomes so powerful that utilizing it for practical purposes becomes suicide, there is a regime where the AI product gives its wielder substantial power. We are currently in that regime. The further AI gets advanced, the more power it grants.
Anthropic might get us all killed. OpenAI is likely to get us all killed. If you tryst the employees of Anthropic to not want to be killed by OpenAI... then you should realize that supporting them while hindering OpenAI is at least potentially a good bet.
Then we must consider probabilities, expected values, etc. Give me your model, with numbers, that shows supporting Anthropic to be a bad bet, or admit you are confused and that you don't actually have good advice to give anyone.
Replies from: adam_scholl, mikhail-samin, ozziegooen↑ comment by Adam Scholl (adam_scholl) · 2025-02-02T12:12:58.820Z · LW(p) · GW(p)
Give me your model, with numbers, that shows supporting Anthropic to be a bad bet, or admit you are confused and that you don't actually have good advice to give anyone.
It seems to me that other possibilities exist, besides "has model with numbers" or "confused." For example, that there are relevant ethical considerations here which are hard to crisply, quantitatively operationalize!
One such consideration which feels especially salient to me is the heuristic that before doing things, one should ideally try to imagine how people would react, upon learning what you did. In this case the action in question involves creating new minds vastly smarter than any person, which pose double-digit risk of killing everyone on Earth, so my guess is that the reaction would entail things like e.g. literal worldwide riots. If so, this strikes me as the sort of consideration one should generally weight more highly than their idiosyncratic utilitarian BOTEC.
Replies from: martin-randall, nathan-helm-burger, Max Lee↑ comment by Martin Randall (martin-randall) · 2025-02-03T04:34:34.288Z · LW(p) · GW(p)
Does your model predict literal worldwide riots against the creators of nuclear weapons? They posed a single-digit risk of killing everyone on Earth (total, not yearly).
It would be interesting to live in a world where people reacted with scale sensitivity to extinction risks, but that's not this world.
Replies from: mikhail-samin↑ comment by Mikhail Samin (mikhail-samin) · 2025-02-03T10:38:06.794Z · LW(p) · GW(p)
nuclear weapons have different game theory. if your adversary has one, you want to have one to not be wiped out; once both of you have nukes, you don't want to use them.
also, people were not aware of real close calls until much later.
with ai, there are economic incentives to develop it further than other labs, but as a result, you risk everyone's lives for money and also create a race to the bottom where everyone's lives will be lost.
Replies from: Max Lee↑ comment by Knight Lee (Max Lee) · 2025-02-04T04:14:57.886Z · LW(p) · GW(p)
I think you (or @Adam Scholl [LW · GW]) need to argue why people won't be angry at you if you developed nuclear weapons, in a way which doesn't sound like "yes, what I built could have killed you, but it has an even higher chance of saving you!"
Otherwise, it's hard to criticize Anthropic for working on AI capabilities without considering whether their work is a net positive. It's hard to dismiss the net positive arguments as "idiosyncratic utilitarian BOTEC," when you accept "net positive" arguments regarding nuclear weapons.
Allegedly, people at Anthropic have compared themselves to Robert Oppenheimer. Maybe they know that one could argue they have blood on their hands, the same way one can argue that about Oppenheimer. But people aren't "rioting" against Oppenheimer.
I feel it's more useful to debate whether it is a net positive, since that at least has a small chance of convincing Anthropic or their employees.
Replies from: mikhail-samin↑ comment by Mikhail Samin (mikhail-samin) · 2025-02-04T17:22:45.343Z · LW(p) · GW(p)
My argument isn’t “nuclear weapons have a higher chance of saving you than killing you”. People didn’t know about Oppenheimer when rioting about him could help. And they didn’t watch The Day After until decades later. Nuclear weapons were built to not be used.
With AI, companies don’t build nukes to not use them; they build larger and larger weapons because if your latest nuclear explosion is the largest so far, the universe awards you with gold. The first explosion past some unknown threshold will ignite the atmosphere and kill everyone, but some hope that it’ll instead just award them with infinite gold.
Anthropic could’ve been a force of good. It’s very easy, really: lobby for regulation instead of against it so that no one uses the kind of nukes that might kill everyone.
In a world where Anthropic actually tries to be net-positive, they don’t lobby against regulation and instead try to increase the chance of a moratorium on generally smarter-than-human AI systems until alignment is solved.
We’re not in that world, so I don’t think it makes as much sense to talk about Anthropic’s chances of aligning ASI on first try.
(If regulation solves the problem, it doesn’t matter how much it damaged your business interests (which maybe reduced how much alignment research you were able to do). If you really care first and foremost about getting to aligned AGI, then regulation doesn't make the problem worse. If you’re lobbying against it, you really need to have a better justification than completely unrelated “if I get to the nuclear banana first, we’re more likely to survive”.)
Replies from: Max Lee↑ comment by Knight Lee (Max Lee) · 2025-02-04T20:56:16.431Z · LW(p) · GW(p)
Hi,
I've just read this post [LW · GW], and it is disturbing what arguments Anthropic made about how the US needs to be ahead of China.
I didn't really catch up to this news, and I think I know where the anti-Anthropic sentiment is coming from now.
I do think that Anthropic only made those arguments in the context of GPU export controls, and trying to convince the Trump administration to do export controls if nothing else. It's still very concerning, and could undermine their ability to argue for strong regulation in the future.
That said, I don't agree with the nuclear weapon explanation.
Suppose Alice and Bob were each building a bomb. Alice's bomb has a 10% chance of exploding and killing everyone, and a 90% chance of exploding into rainbows and lollipops and curing cancer. Bob's bomb has a 10% chance of exploding and killing everyone, and a 90% chance of "never being used" and having a bunch of good effects via "game theory."
I think people with ordinary moral views will not be very angry at Alice, but forgive Bob because "Bob's bomb was built to not be used."
Replies from: mikhail-samin, nathan-helm-burger↑ comment by Mikhail Samin (mikhail-samin) · 2025-02-05T03:01:46.561Z · LW(p) · GW(p)
(Dario’s post did not impact the sentiment of my shortform post.)
↑ comment by Nathan Helm-Burger (nathan-helm-burger) · 2025-02-04T22:41:14.507Z · LW(p) · GW(p)
I don't believe the nuclear bomb was truly built to not be used from the point of view of the US gov. I think that was just a lie to manipulate scientists who might otherwise have been unwilling to help.
I don't think any of the AI builders are anywhere close to "building AI not to be used". This seems even more clear than with nuclear, since AI has clear beneficial peacetime economically valuable uses.
Regulation does make things worse if you believe the regulation will fail to work as intended for one reason or another. For example, my argument that putting compute limits on training runs (temporarily or permanently) would hasten progress to AGI by focusing research efforts on efficiency and exploring algorithmic improvements.
↑ comment by Nathan Helm-Burger (nathan-helm-burger) · 2025-02-05T03:46:57.265Z · LW(p) · GW(p)
It has been pretty clearly announced to the world by various tech leaders that they are explicitly spending billions of dollars to produce "new minds vastly smarter than any person, which pose double-digit risk of killing everyone on Earth". This pronouncement has not yet incited riots. I feel like discussing whether Anthropic should be on the riot-target-list is a conversation that should happen after the OpenAI/Microsoft, DeepMind/Google, and Chinese datacenters have been burnt to the ground.
Once those datacenters have been reduced to rubble, and the chip fabs also, then you can ask things like, "Now, with the pressure to race gone, will Anthropic proceed in a sufficiently safe way? Should we allow them to continue to exist?" I think that, at this point, one might very well decide that the company should continue to exist with some minimal amount of compute, while the majority of the compute is destroyed. I'm not sure it makes sense to have this conversation while OpenAI and DeepMind remain operational.
↑ comment by Knight Lee (Max Lee) · 2025-02-02T20:24:42.503Z · LW(p) · GW(p)
That's a very good heuristic. I bet even Anthropic agrees with it. Anthropic did not release their newer models until OpenAI released ChatGPT and the race had already started.
That's not a small sacrifice. Maybe if they released it sooner, they would be bigger than OpenAI right now due to the first mover advantage.
I believe they want the best for humanity, but they are in a no-win situation, and it's a very tough choice what they should do. If they stop trying to compete, the other AI labs will build AGI just as fast, and they will lose all their funds. If they compete, they can make things better.
AI safety spending [? · GW] is only $0.1 billion while AI capabilities spending is $200 billion. A company which adds a comparable amount of effort on both AI alignment and AI capabilities should speed up the former more than the latter.
Even if they don't support all the regulations you believe in, they're the big AI company supporting relatively much more regulation than all the others.
I don't know, I may be wrong. Sadly it is so very hard to figure out what's good or bad for humanity in this uncertain time.
Replies from: aysja↑ comment by aysja · 2025-02-02T23:20:44.714Z · LW(p) · GW(p)
I don't think that most people, upon learning that Anthropic's justification was "other companies were already putting everyone's lives at risk, so our relative contribution to the omnicide was low" would then want to abstain from rioting. Common ethical intuitions are often more deontological than that, more like "it's not okay to risk extinction, period." That Anthropic aims to reduce the risk of omnicide on the margin is not, I suspect, the point people would focus on if they truly grokked the stakes; I think they'd overwhelmingly focus on the threat to their lives that all AGI companies (including Anthropic) are imposing.
Replies from: Max Lee↑ comment by Knight Lee (Max Lee) · 2025-02-03T01:43:04.341Z · LW(p) · GW(p)
Regarding common ethical intuitions, I think people in the post singularity world (or afterlife, for the sake of argument) will be far more forgiving of Anthropic. They will understand, even if Anthropic (and people like me) turned out wrong, and actually were a net negative for humanity.
Many ordinary people (maybe most) would have done the same thing in their shoes.
Ordinary people do not follow the utilitarianism that the awkward people here follow. Ordinary people also do not follow deontology or anything that's the opposite of utilitarianism. Ordinary people just follow their direct moral feelings. If Anthropic was honestly trying to make the future better, they won't feel that outraged at their "consequentialism." They may be outraged an perceived incompetence, but Anthropic definitely won't be the only one accused of incompetence.
↑ comment by Mikhail Samin (mikhail-samin) · 2025-02-02T10:28:17.051Z · LW(p) · GW(p)
If you trust the employees of Anthropic to not want to be killed by OpenAI
In your mind, is there a difference between being killed by AI developed by OpenAI and by AI developed by Anthropic? What positive difference does it make, if Anthropic develops a system that kills everyone a bit earlier than OpenAI would develop such a system? Why do you call it a good bet?
AGI is coming whether you like it or not
Nope.
You’re right that the local incentives are not great: having a more powerful model is hugely economically beneficial, unless it kills everyone.
But if 8 billion humans knew what many of LessWrong users know, OpenAI, Anthropic, DeepMind, and others cannot develop what they want to develop, and AGI doesn’t come for a while.
From the top of my head, it actually likely could be sufficient to either (1) inform some fairly small subset of 8 billion people of what the situation is or (2) convince that subset that the situation as we know it is likely enough to be the case that some measures to figure out the risks and not be killed by AI in the meantime are justified. It’s also helpful to (3) suggest/introduce/support policies that change the incentives to race or increase the chance of (1) or (2).
A theory of change some have for Anthropic is that Anthropic might get in position to successfully do one of these two things.
My shortform post says that the real Anthropic is very different from the kind of imagined Anthropic that would attempt to do these nope. Real Anthropic opposes these things.
↑ comment by ozziegooen · 2025-02-04T19:42:52.853Z · LW(p) · GW(p)
Then we must consider probabilities, expected values, etc. Give me your model, with numbers, that shows supporting Anthropic to be a bad bet, or admit you are confused and that you don't actually have good advice to give anyone.
Are there good models that support that Anthropic is a good bet? I'm genuinely curious.
I assume that naively, if any side had more of the burden of proof, it would be Anthropic. They have many more resources, and are the ones doing the highly-impactful (and potentially negative) work.
My impression was that there was very little probablistic risk modeling here, but I'd love to be wrong.
↑ comment by Nathan Helm-Burger (nathan-helm-burger) · 2025-02-04T22:22:19.890Z · LW(p) · GW(p)
I don't feel free to share my model, unfortunately. Hopefully someone else will chime in. I agree with your point and that this is a good question!
I am not trying to say I am certain that Anthropic is going to be net positive, just that that's my view as the higher probability.
Replies from: ozziegooen↑ comment by ozziegooen · 2025-02-04T23:05:54.739Z · LW(p) · GW(p)
I think it's totally fine to think that Anthropic is a net positive. Personally, right now, I broadly also think it's a net positive. I have friends on both sides of this.
I'd flag though that your previous comment suggested more to me than "this is just you giving your probability"
> Give me your model, with numbers, that shows supporting Anthropic to be a bad bet, or admit you are confused and that you don't actually have good advice to give anyone.
I feel like there are much nicer ways to phase that last bit. I suspect that this is much of the reason you got disagreement points.
↑ comment by Nathan Helm-Burger (nathan-helm-burger) · 2025-02-04T23:23:45.481Z · LW(p) · GW(p)
Fair enough. I'm frustrated and worried, and should have phrased that more neutrally. I wanted to make stronger arguments for my point, and then partway through my comment realized I didn't feel good about sharing my thoughts.
I think the best I can do is gesture at strategy games that involve private information and strategic deception like Diplomacy and Stratego and MtG and Poker, and say that in situations with high stakes and politics and hidden information, perhaps don't take all moves made by all players at literally face value. Think a bit to yourself about what each player might have in their uands, what their incentives look like, what their private goals might be. Maybe someone whose mind is clearer on this could help lay out a set of alternative hypotheses which all fit the available public data?
Replies from: mikhail-samin↑ comment by Mikhail Samin (mikhail-samin) · 2025-02-05T03:07:40.760Z · LW(p) · GW(p)
The private data is, pretty consistently, Anthropic being very similar to OpenAI where it matters the most and failing to mention in private policy-related settings its publicly stated belief on the risk that smarter-than-human AI will kill everyone.
↑ comment by Lukas Finnveden (Lanrian) · 2025-02-02T17:36:40.059Z · LW(p) · GW(p)
lobbied against mandatory RSPs
What is this referring to?
Replies from: mikhail-samin, Zach Stein-Perlman↑ comment by Mikhail Samin (mikhail-samin) · 2025-02-02T20:39:51.543Z · LW(p) · GW(p)
People representing Anthropic argued against government-required RSPs. I don’t think I can share the details of the specific room where that happened, because it will be clear who I know this from.
Ask Jack Clark whether that happened or not.
Replies from: nathan-helm-burger↑ comment by Nathan Helm-Burger (nathan-helm-burger) · 2025-02-03T00:21:06.627Z · LW(p) · GW(p)
Anthropic ppl had also said approximately this publicly. Saying that it's too soon to make the rules, since we'd end up mispecifying due to ignorance of tomorrow's models.
Replies from: zac-hatfield-dodds↑ comment by Zac Hatfield-Dodds (zac-hatfield-dodds) · 2025-02-03T06:32:45.905Z · LW(p) · GW(p)
There's a big difference between regulation which says roughly "you must have something like an RSP", and regulation which says "you must follow these specific RSP-like requirements", and I think Mikhail is talking about the latter.
I personally think the former is a good idea, and thus supported SB-1047 along with many other lab employees. It's also pretty clear to me that locking in circa-2023 thinking about RSPs would have been a serious mistake, and so I (along with many others) am generally against very specific regulations because we expect they would on net increase catastrophic risk.
Replies from: adam_scholl, mikhail-samin↑ comment by Adam Scholl (adam_scholl) · 2025-02-03T07:31:00.743Z · LW(p) · GW(p)
When do you think would be a good time to lock in regulation? I personally doubt RSP-style regulation would even help, but the notion that now is too soon/risks locking in early sketches, strikes me as in some tension with e.g. Anthropic trying to automate AI research ASAP, Dario expecting ASL-4 systems between 2025—the current year!—and 2028, etc.
Replies from: zac-hatfield-dodds↑ comment by Zac Hatfield-Dodds (zac-hatfield-dodds) · 2025-02-10T04:09:24.366Z · LW(p) · GW(p)
Here I am on record supporting SB-1047, along with many of my colleagues. I will continue to support specific proposed regulations if I think they would help, and oppose them if I think they would be harmful; asking "when" independent of "what" doesn't make much sense to me and doesn't seem to follow from anything I've said.
My claim is not "this is a bad time", but rather "given the current state of the art, I tend to support framework/liability/etc regulations, and tend to oppose more-specific/exact-evals/etc regulations". Obviously if the state of the art advanced enough that I thought the latter would be better for overall safety, I'd support them, and I'm glad that people are working on that.
↑ comment by Mikhail Samin (mikhail-samin) · 2025-02-03T10:34:11.848Z · LW(p) · GW(p)
AFAIK Anthropic has not unequivocally supported the idea of "you must have something like an RSP" or even SB-1047 despite many employees, indeed, doing so.
Replies from: zac-hatfield-dodds↑ comment by Zac Hatfield-Dodds (zac-hatfield-dodds) · 2025-02-10T04:13:57.256Z · LW(p) · GW(p)
To quote from Anthropic's letter to Govenor Newsom,
Replies from: mikhail-saminAs you may be aware, several weeks ago Anthropic submitted a Support if Amended letter regarding SB 1047, in which we suggested a series of amendments to the bill. ... In our assessment the new SB 1047 is substantially improved, to the point where we believe its benefits likely outweigh its costs.
...
We see the primary benefits of the bill as follows:
- Developing SSPs and being honest with the public about them. The bill mandates the adoption of safety and security protocols (SSPs), flexible policies for managing catastrophic risk that are similar to frameworks adopted by several of the most advanced developers of AI systems, including Anthropic, Google, and OpenAI. However, some companies have still not adopted these policies, and others have been vague about them. Furthermore, nothing prevents companies from making misleading statements about their SSPs or about the results of the tests they have conducted as part of their SSPs. It is a major improvement, with very little downside, that SB 1047 requires companies to adopt some SSP (whose details are up to them) and to be honest with the public about their SSP-related practices and findings.
...
We believe it is critical to have some framework for managing frontier AI systems that roughly meets [requirements discussed in the letter]. As AI systems become more powerful, it's crucial for us to ensure we have appropriate regulations in place to ensure their safety.
↑ comment by Mikhail Samin (mikhail-samin) · 2025-02-10T08:58:12.075Z · LW(p) · GW(p)
“we believe its benefits likely outweigh its costs” is “it was a bad bill and now it’s likely net-positive”, not exactly unequivocally supporting it. Compare that even to the language in calltolead.org.
Edit: AFAIK Anthropic lobbied against SSP-like requirements in private.
↑ comment by Zach Stein-Perlman · 2025-02-02T20:12:05.963Z · LW(p) · GW(p)
My guess is it's referring to Anthropic's position on SB 1047, or Dario's and Jack Clark's statements that it's too early for strong regulation, or how Anthropic's policy recommendations often exclude RSP-y stuff (and when they do suggest requiring RSPs, they would leave the details up to the company).
Replies from: Lanrian↑ comment by Lukas Finnveden (Lanrian) · 2025-02-02T20:15:14.437Z · LW(p) · GW(p)
SB1047 was mentioned separately so I assumed it was something else. Might be the other ones, thanks for the links.
↑ comment by ZY (AliceZ) · 2025-02-04T08:14:37.948Z · LW(p) · GW(p)
I wonder if this is due to
- funding - the company need money to perform research on safety alignment (X risks, and assuming they do want to to this), and to get there they need to publish models so that they can 1) make profits from them, 2) attract more funding. A quick look on the funding source shows Amazon, Google, some other ventures, and some other tech companies
- empirical approach - they want to take empirical approach to AI safety and would need some limited capable models
But both of the points above are my own speculations
comment by Mikhail Samin (mikhail-samin) · 2025-02-28T03:24:35.957Z · LW(p) · GW(p)
Since this seems to be a crux, I propose a bet to @Zac Hatfield-Dodds [LW · GW] (or anyone else at Anthropic): someone shows random people in San-Francisco Anthropic’s letter to Newsom on SB-1047. I would bet that among the first 20 who fully read at least one page, over half will say that Anthropic’s response to SB-1047 is closer to presenting the bill as 51% good and 49% bad than presenting it as 95% good and 5% bad.
Zac, at what odds would you take the bet?
(I would be happy to discuss the details.)
Replies from: zac-hatfield-dodds, MathiasKirkBonde, yonatan-cale-1↑ comment by Zac Hatfield-Dodds (zac-hatfield-dodds) · 2025-02-28T06:55:22.329Z · LW(p) · GW(p)
Sorry, I'm not sure what proposition this would be a crux for?
More generally, "what fraction good vs bad" seems to me a very strange way to summarize Anthropic's Support if Amended letter or letter to Governor Newsom. It seems clear to me that both are supportive in principle of new regulation to manage emerging risks, and offering Anthropic's perspective on how best to achieve that goal. I expect most people who carefully read either letter would agree with the preceeding sentence and would be open to bets on such a proposition.
Personally, I'm also concerned about the downside risks discussed in these letters - because I expect they both would have imposed very real costs, and reduced the odds of the bill passing and similar regulations passing and enduring in other juristictions. I nonetheless concluded that the core of the bill was sufficiently important and urgent, and downsides manageable, that I supported passing it.
Replies from: mikhail-samin↑ comment by Mikhail Samin (mikhail-samin) · 2025-02-28T17:32:49.199Z · LW(p) · GW(p)
I refer to the second letter.
I claim that a responsible frontier AI company would’ve behaved very differently from Anthropic. In particular, the letter said basically “we don’t think the bill is that good and don’t really think it should be passed” more than it said “please sign”. This is very different from your personal support for the bill; you indeed communicated “please sign”.
Sam Altman has also been “supportive of new regulation in principle”. These words sadly don’t align with either OpenAI’s or Anthropic’s lobbying efforts, which have been fairly similar. The question is, was Anthropic supportive of SB-1047 specifically? I expect people to not agree Anthropic was after reading the second letter.
Replies from: zac-hatfield-dodds↑ comment by Zac Hatfield-Dodds (zac-hatfield-dodds) · 2025-03-01T22:25:06.696Z · LW(p) · GW(p)
I strongly disagree that OpenAI's and Anthropic's efforts were similar (maybe there's a bet there?). OpenAI formally opposed the bill without offering useful feedback; Anthropic offered consistent feedback to improve the bill, pledged to support it if amended, and despite your description of the second letter Senator Wiener describes himself as having Anthropic's support.
I also disagree that a responsible company would have behaved differently. You say "The question is, was Anthropic supportive of SB-1047 specifically?" - but I think this is the wrong question, implying that lack of support is irresponsible rather than e.g. due to disagreements about the factual question of whether passing the bill in a particular state would be net-helpful for mitigating catastrophic risks. The Support if Amended letter, for example, is very clear:
Anthropic does not support SB 1047 in its current form. However, we believe the bill's core aims to ensure the safe development of AI technologies are worthy, and that it is possible to achieve these aims while eliminating most of the current bill's substantial drawbacks, as we will propose here. ... We are committed to supporting the bill if all of our proposed amendments are made.
I don't expect further discussion to be productive though; much of the additional information I have is nonpublic, and we seem to have different views on what constitutes responsible input into a policy process as well as basic questions like "is Anthropic's engagement in the SB-1047 process well described as 'support' when the letter to Governor Newsom did not have the word 'support' in the subject line". This isn't actually a crux for me, but I and Senator Wiener seem to agree yes, while you seem to think no.
↑ comment by MathiasKB (MathiasKirkBonde) · 2025-02-28T10:45:46.144Z · LW(p) · GW(p)
One thing to highlight, which I only learned recently, is that the norm when submitting letters to the governor on any bill in California is to include: "Support" or "Oppose" in the subject line to clearly state the company's position.
Anthropic importantly did NOT include "support" in the subject line of the second letter. I don't know how to read this as anything else than that Anthropic did not support SB1047.
↑ comment by Mikhail Samin (mikhail-samin) · 2025-03-01T01:56:22.768Z · LW(p) · GW(p)
Good point! That seems right; advocacy groups seem to think staff sorts letters by support/oppose/request for signature/request for veto in the subject line and recommend adding those to the subject line. Examples: 1, 2.
Anthropic has indeed not included any of that in their letter to Gov. Newsom.
↑ comment by Yonatan Cale (yonatan-cale-1) · 2025-02-28T05:08:38.782Z · LW(p) · GW(p)
(Could you link to the context?)
comment by Mikhail Samin (mikhail-samin) · 2024-03-28T22:06:53.516Z · LW(p) · GW(p)
People are arguing about the answer to the Sleeping Beauty! I thought this was pretty much dissolved with this post's title [LW · GW]! But there are lengthy posts [LW · GW] and even a prediction market!
Sleeping Beauty is an edge case where different reward structures are intuitively possible, and so people imagine different game payout structures behind the definition of “probability”. Once the payout structure is fixed, the confusion is gone. With a fixed payout structure&preference framework rewarding the number you output as “probability”, people don’t have a disagreement about what is the best number to output. Sleeping beauty is about definitions.)
And still, I see posts arguing that if a tree falls on a deaf Sleeping Beauty, in a forest with no one to hear it, it surely doesn’t produce a sound, because here’s how humans perceive sounds, which is the definition of a sound, and there are demonstrably no humans around the tree. (Or maybe that it surely produces the sound because here’s the physics of the sound waves, and the tree surely abides by the laws of physics, and there are demonstrably sound waves.)
This is arguing about definitions. You feel strongly that “probability” is that thing that triggers the “probability” concept neuron in your brain. If people have a different concept triggering “this is probability”, you feel like they must be wrong, because they’re pointing at something they say is a sound and you say isn’t.
Probability is something defined in math by necessity. There’s only one way to do it to not get exploited in natural betting schemes/reward structures that everyone accepts when there are no anthropics involved. But if there are multiple copies of the agent, there’s no longer a single possible betting scheme defining a single possible “probability”, and people draw the boundary/generalise differently in this situation.
You all should just call these two probabilities two different words instead of arguing which one is the correct definition for "probability".
Replies from: martin-randall↑ comment by Martin Randall (martin-randall) · 2025-02-03T04:51:32.588Z · LW(p) · GW(p)
As the creator of the linked market, I agree it's definitional. I think it's still interesting to speculate/predict what definition will eventually be considered most natural.
comment by Mikhail Samin (mikhail-samin) · 2023-02-07T15:30:24.267Z · LW(p) · GW(p)
[RETRACTED after Scott Aaronson’s reply by email]
I'm surprised by Scott Aaronson's approach to alignment. He has mentioned in a talk that a research field needs to have at least one of two: experiments or a rigorous mathematical theory, and so he's focusing on the experiments that are possible to do with the current AI systems.
The alignment problem is centered around optimization producing powerful consequentialist agents appearing when you're searching in spaces with capable agents. The dynamics at the level of superhuman general agents are not something you get to experiment with (more than once); and we do indeed need a rigorous mathematical theory that would describe the space and point at parts of it that are agents aligned with us.
[removed]
I'm disappointed that, currently, only Infra-Bayesianism tries to achieve that[1], that I don't see dozens of other research directions trying to have a rigorous mathematical theory that would provide desiderata for AGI training setups, and that even actual scientists entering the field [removed].
- ^
Infra-Bayesianism is an approach that tries to describe agents in a way that would closely resemble the behaviour of AGIs, starting with a way you can model them having probabilities about the world in a computable way that solves non-realizability in RL (short explanation [LW · GW], a sequence with equations and proofs [? · GW]) and making decisions in a way that optimization processes would select for, and continuing with a formal theory of naturalized induction [LW · GW] and, finally, a proposal for alignment protocol [LW · GW].
To be clear, I don't expect Infra-Bayesianism to produce an answer to what loss functions should be used to train an aligned AGI in the time that we have remaining; but I'd expect that if there were a hundred research directions like that, trying to come up with a rigorous mathematical theory that successfully attacks the problem, with thousands of people working on them, some would succeed.