Please stop publishing ideas/insights/research about AI

I think this is undignified.

I agree that it would be safer if humanity were a collective hivemind that could coordinate to not build AI until we know how to build the best AI, and that people should differentially work on things that make the situation better rather than worse, and that this potentially includes keeping quiet about information that would make things worse.

The problem is—as you say—"[i]t's very rare that any research purely helps alignment"; you can't think about aligning AI without thinking about AI. In order to navigate the machine intelligence transition in the most dignified way, you want your civilization's best people to be doing their best thinking about the problem, and your best people can't do their best thinking under the conditions of paranoid secrecy.

Concretely, I've been studying some deep learning basics lately and have written a couple [LW · GW] posts [LW · GW] about things I've learned. I think this was good, not bad. I think I and my readers have a slightly better understanding of the technology in question than if I hadn't studied and hadn't written, and that better understanding will help us make better decisions in expectation.

This applies doubly so to work that aims to make AI understandable or helpful, rather than aligned—a helpful AI will help anyone

Sorry, what? I thought the fear was that we don't know how to make helpful AI at all. (And that people who think they're being helped by seductively helpful-sounding LLM assistants are being misled by surface appearances; the shoggoth underneath has its own desires that we won't like when it's powerful enough to persue them autonomously.) In contrast, this almost makes it sound like you think it is plausible to align AI to its user's intent, but that this would be bad if the users aren't one of "us"—you know, the good alignment researchers who want to use AI to take over the universe, totally unlike those evil capabilities researchers who want to use AI to produce economically valuable goods and services.

I'm very sympathetic to the idea of being careful about publishing things that could spread capabilities ideas. However, I think there are several important things missing from your world model, which cause me to believe that following your advice would substantially hurt alignment progress.

(To be clear, none of this applies to alignment people working directly on capabilities, who should, like, not. Rather, this is about alignment researchers accidentally advancing capabilities by talking to capabilities people)

• It's genuinely hard to come up with ideas that help capabilities a lot. I think you are severely underestimating how hard it is, and how much insight is required. I think one issue here is that most papers on arxiv are garbage and don't actually make any progress, but those papers are not the ones that are pushing AGI forward anyways.
• Even if you try very hard to do so, it's still very hard to convince people that you're right if you don't have a ton of clout via a legible reputation of being right a lot. Everyone has an agenda they're convinced will solve AGI and is too busy trying to convince everyone else to work on their agenda.
• High level ideas are generally not that valuable in and of themselves. People generally learn to ignore ideas unless they have strong empirical evidence of correctness (or endorsement of highly respected researchers) because there are simply too many ideas. The valuable thing is not the idea itself, but the knowledge of which ideas are actually correct.
• I think deeply understanding top tier capabilities researchers' views on how to achieve AGI is actually extremely valuable for thinking about alignment. Even if you disagree on object level views, understanding how very smart people come to their conclusions is very valuable.
• I think alignment discourse is greatly harmed by people being too scared to say things. When it bleeds over to being too scared to think about capabilities related topics for fear of accidentally generating something dangerous, I think this is even more harmful.

I agree with many of the points made in this post, especially the "But my ideas/insights/research is not likely to impact much!" point. I find it plausible that in some subfields, AI x-risk people are too prone to publishing due to historical precedent and norms (maybe mech interp? though little has actually come of that). I also want to point out that there are non-zero arguments to expect alignment work to help more with capabilties, relative to existing "mainstream" capabilities work, even if I don't believe this to be the case. (For example, you might believe that the field of deep learning spends too little time actually thinking about how to improve their models, and too much time just tinkering, in which case your thinking could have a disproportionate impact even after adjusting for the fact that you're not trying to do capabilities.) And I think that some of the research labeled "alignment" is basically just capabilities work, and maybe the people doing them should stop. 

I also upvoted the post because I think this attitude is pervasive in these circles, and it's good to actually hash it out in public. 

But as with most of the commenters, I disagree with the conclusion of the post. 

I suspect the main cruxes between us are the following:

1. How much useful alignment work is actually being done? 

From paragraphs such as the following:

It's very rare that any research purely helps alignment, because any alignment design is a fragile target that is just a few changes away from unaligned. There is no alignment plan which fails harmlessly if you fuck up implementing it, and people tend to fuck things up unless they try really hard not to (and often even if they do), and people don't tend to try really hard not to. This applies doubly so to work that aims to make AI understandable or helpful, rather than aligned — a helpful AI will help anyone, and the world has more people trying to build any superintelligence (let's call those "capabilities researchers") than people trying to build aligned superintelligence (let's call those "alignment researchers").

And 

"But my ideas/insights/research is not likely to impact much!" — that's not particularly how it works? It needs to somehow be differenially helpful to alignment, which I think is almost never the case.

It seems that a big part of your world model is that ~no one who thinks they're doing "alignment" work is doing real alignment work, and are really just doing capabilities work. In particular, it seems that you think interp or intent alignment are basically just capabilities work, insofar as their primary effect is helping people build unsafe ASI faster. Perhaps you think that, in the case of interp, before we can understand the AI in a way that's helpful for alignment, we'll understand it in a way that allows us to improve it. I'm somewhat sympathetic to this argument. But I think making it requires arguing that interp work doesn't really contribute to alignment at all, and is thus better thought of as capabilities work (and same for intent alignment).

Perhaps you believe that all alignment work is useless, not because they're misguided and actually capabilities work, but because we're so far from building aligned ASI that ~all alignment work is useless, and in the intermediate regime where additional insights non-negligibly hasten the arrival of unaligned ASI. But I think you should argue for that explicitly (as say, Eliezer did in his death with dignity post), since I imagine most of the commenters here would disagree with this take. 

My guess is this is the largest crux between us; if I thought all "alignment" work did nothing for alignment, and was perhaps just capabilities work in disguise, then I would agree that people should stop. In fact, I might even argue that we should just stop all alignment work whatsoever! Insofar as I'm correct about this being a crux, I'd like to see a post explicitly arguing for the lack of alignment relevancy of existing 'alignment work', which will probably lead to a more constructive conversation than this post. 

2. How many useful capabilities insights incidentally come from "alignment" work? 

I think empirically, very few (if not zero) capabilities insights have come from alignment work. And a priori, you might expect that research that aims to solve topic X produces marginally more X than a related topic Y. Insofar as you think that current "alignment" work is more than epsilon useful, I think you would not argue that most alignment work is differentially negative. So insofar as you think a lot of "alignment" work is real alignment work, you probably believe that many capabilities insights have come from past alignment work. 

Perhaps you're reluctant to give examples, for fear of highlighting them. I think the math doesn't work out here -- having a few clear examples from you would probably be sufficient to significantly reduce the number of published insights from the community as a whole. But, if you have many examples of insights that help capabilities but are too dangerous to highlight, I'd appreciate if you would just say that (and maybe we can find a trusted third party to verify your claim, but not share the details?). 

Perhaps you might say, well, the alignment community is very small, so there might not be many examples that come to mind! To make this carry through, you'd still have to believe that the alignment community also hasn't produced much good research. (Even though, naively, you might expect higher returns from alignment due to there being more unpicked low-hanging fruit due to its small size.) But then again, I'd prefer if you explicitly argued that ~all alignment is either useless or capabilities instead of gesturing at a generic phenomenon.  

Perhaps you might say that capabilities insights are incredibly long tailed, and thus seeing no examples doesn't mean that the expected harm is low. But, I think you still need to make some sort of plausibility argument here, as well as a story for why the existing ML insights deserve a lot of Shapley for capabilities advances, even though most of the "insights" people had were useless if not actively misleading. 

I also think that there's an obvious confounder, if you believe something along the lines of "focusing on alignment is correlated with higher rationality". Personally, I also think the average alignment(-interested) researcher is more competent at machine learning or research in general than the average generic capabilities researcher (this probably becomes false once you condition on being at OAI, Anthropic, or another scaling lab). If you just count "how many good ideas came from 'alignment' researchers per capita" to the number for 'capability' researchers, you may find that the former is higher because they're just more competent. This goes back again into crux 1., where you then need to argue that competency doesn't help at all in doing actual alignment work, and again, I suspect it's more productive to just argue about the relevance and quality of alignment work instead of arguing about incidental capabilities insights. 

3. How important are insights to alignment/capabilities work? 

From paragraphs such as the following:

Worse yet: if focusing on alignment is correlated with higher rationality and thus with better ability for one to figure out what they need to solve their problems, then alignment researchers are more likely to already have the ideas/insights/research they need than capabilities researchers, and thus publishing ideas/insights/research about AI is more likely to differentially help capabilities researchers. Note that this is another relative statement; I'm not saying "alignment researchers have everything they need", I'm saying "in general you should expect them to need less outside ideas/insights/research on AI than capabilities researchers".

it seems that you're working with a model of research output with two main components -- (intrinsic) rationality and (external) insights. But there's a huge component that's missing from this model: actual empirical experiments validating the insight, which is the ~bulk of actual capabilities work and a substantial fraction of alignment work. This matters both because ~no capabilities researchers will listen to you if you don't have empirical experiments, and because, if you believe that you can deduce more alignment research "on your own", you might also believe that you need to do more empirical experiments to do capabilities research (and thus that the contribution per insight is by default a lot smaller). 

Even if true insights are differentially more helpful for capabilities, the fact that it seems empirically difficult to know which insights are true means that a lot of the work in getting a true insight will involve things that look a lot more like normal capabilities work -- e.g. training more capable models. But surely then, the argument would be reducable to: if you do capabilities work, don't share it on pain of accelerating ASI progress -- which seems like something your audience already agrees with!

That being said, I think I might disagree with your premise here. My guess is that alignment, by being less grounded than capabilities, probably requires more oustide ideas/insights/research, just for sanity checking reasons (once you control for competence of researcher and the fact that there's probably more low-hanging fruit in alignment). After all, you can just make a change and see if your log loss on pretraining goes down, but it's a lot harder to know if your model of deceptive alignment actually is at all sensible. If you don't improve your model's performance on standard benchmarks, then this is evidence that your capability idea doesn't work, but there aren't even really any benchmarks for many of the problems alignment researchers think about. So it's easier to go astray, and therefore more important to get feedback from other researchers. 

Finally, to answer this question:

"So where do I privately share such research?" — good question!

I suspect that the way to go is to form working groups of researchers that stick together, and that maintain a high level of trust. e.g. a research organization. Then, do and share your research internally and think about possible externalities before publishing more broadly, perhaps doing a tiered release. (This is indeed the model used by many people in alignment orgs.)

"If nobody publishes anything, how will alignment get solved?" — sure, it's harder for alignment researchers to succeed if they don't communicate publicly with one another — but it's not impossible. That's what dignity is about. A

Huh, I have the opposite intuition. I was about to cite that exact same "Death with dignity" post as an argument for why you are wrong; it's undignified for us to stop trying to solve the alignment problem and publicly discussing the problem with each other, out of fear that some of our ideas might accidentally percolate into OpenAI and cause them to go slightly faster, and that this increased speedup might have made the difference between victory and defeat. The dignified thing to do is think and talk about the problem.

At the core, this is a reminder to not publish things that will help more with capabilities than alignment. That's perfectly reasonable.

The tone of the post suggests erring on the side of "safety" by not publishing things that have an uncertain safety/capabilities balance. I hope that wasn't the intent.

Because that does not make sense. Anything that advances alignment more than safety in expectation should be published.

You have to make a difficult judgment call for each publication. Be mindful of your bias in wanting to publish to show off your work and ideas. Get others' insights if you can do so reasonably quickly.

But at the end of the day, you have to make that judgment call. There's no consolation prize for saying "at least I didn't make the world end faster". If you're a utilitarian, winning the future is the only goal.

(If you're not a utilitarian, you might actually want a resolution faster so you and your loved ones have higher odds of surviving into the far future.)

I think the status quo around publishing safety research is mostly fine (though being a bit more careful seems good); more confidently, I think going as far as the vibe of this post suggests would be bad.

Some possible cruxes, or reasons the post basically didn't move my view on that:

• Most importantly, I think the research published by people working on x-risk tends to overall help safety/alignment more than capabilities.
  • I suspect the main disagreement might be what kind of research is needed to make AI go well, and whether the research currently happening helps.
  • Probably less importantly, I disagree a bit about how helpful that research likely is for advancing capabilities. In particular, I don't buy the argument that safety researchers have unusually good ideas/research compared to capability researchers at top labs (part of this is that my impression is capabilities aren't mainly bottlenecked by ideas, though of course sufficiently good ideas would help).
  • It's getting harder to draw the boundary since people use "safety" or "alignment" for a lot of things now. So, to be clear, I'm talking about research published by people who think there are catastrophic risks from AI and care a lot about preventing those, it seems like that's your target audience.
• Secondarily, longer timelines are only helpful if useful things are happening, and I think if everyone working on x-risk stopped publishing their research, way fewer useful things would happen on the research side. Maybe the plan is to mostly use the additional time for policy interventions? I think that's also complicated though (so far, visibly advancing capabilities have been one of the main things making policy progress feasible). Overall, I think more time would help, but it's not clear how much and I'm not even totally sure about the sign (taking into account worries from hardware overhang).
• I think there are more structural downsides to not publishing anything. E.g. that makes it much harder to get academia on board (and getting academia on board has been pretty important for policy as far as I can tell, and I think getting them even more on board would be pretty good). Not sure this is an actual crux though, if I thought the research that's happening wasn't helpful enough, this point would also be weaker.

I think most of these are pretty long-standing disagreements, and I don't think the post really tries to argue its side of them, so my guess is it's not going to convince the main people it would need to convince (who are currently publishing prosaic safety/alignment research). That said, if someone hasn't thought at all about concepts like "differentially advancing safety" or "capabilities externalities," then reading this post would probably be helpful, and I'd endorse thinking about those issues. And I agree that some of the "But ..." objections you list are pretty weak.

Are there types of published alignment research that you think were (more likely to be) good to publish? If so, I'd be curious to see a list.

I would give examples of things that shouldn't have been published and are why I agree, but that would be missing the point, wouldn't it?

Let's put it this way: I think most "alignment" or "safety" research is in fact nothing of the kind, and most people responding are deluding themselves so as to avoid having to consider the possibility of needing to go back to the drawing board.

As usual, capability (ability to figure out things about ai) generalizes further than alignment (ability to aim your ability to understand ai at actually making your knowledge produce utilitarian(-prioritarian)-morally-good outcomes).

On infrastructures for private sharing:

Feature recommendation: Marked Posts (name intentionally bland. Any variant of "private" (ie, secret, sensitive, classified) would attract attention and partially negate the point) (alternate names: permissioned posts, declared posts)

This feature prevents leaks, without sacrificing openness.

A marked post will only be seen by members in good standing. They'll be able to see the title and abstract in their feed, but before they're able to read it, they have to click "I declare that I'm going to read this", and then they'll leave a read receipt (or a "mark") visible to the post creator, admins, other members in good standing. (these would also just serve a useful social function of giving us more mutual knowledge of who knows what, while making it easier to coordinate to make sure every post gets read by people who'd understand it and be able to pass it along to interested parties.)

If a member "reads" an abnormally high number of these posts, the system detects that, and they may have their ability to read more posts frozen. Admins, and members who've read many of the same posts, are notified, and you can investigate. If other members find that this person actually is reading this many posts, that they seem to truly understand the content, they can be given an expanded reading rate. Members in good standing should be happy to help with this, if that person is a leaker, well that's serious, if they're not a leaker, what you're doing in the interrogation setting is essentially you're just getting to know a new entrant to the community who reads and understands a lot, talking about the theory with them, and that is a happy thing to do.

Members in good standing must be endorsed by another member in good standing before they will be able to see Marked posts. The endorsements are also tracked. If someone issues too many endorsements too quickly (or the people downstream of their endorsements are collectively doing so in a short time window), this sends an alert. The exact detection algorithm here is something I have funding to develop so if you want to do this, tell me and I can expedite that project.

Note: Someone who reads and understands a lot of posts within a community will, if those posts are correct, end up being aligned with the community. Verify that they're actually reading the posts and not just the capabilities ones→verify unlikely to leak.

This style of thinking seems illogical to me. It has already clearly resulted in a sort of evaporative cooling in OpenAI. At a high level, is it possible you have the opposite of a wishful thinking bias you claim OpenAI researchers have? I won't go into too much detail about why this post doesn't make sense to me. as others already have. 
But broadly speaking:

• I doubt rationality gives you too much of an advantage in capabilities research, and believing this when on a site full of rationalists seems a little pretentious almost. 
• I also have no idea how any alignment research so far has helped capabilities in any way.  I don't even know how RLHF has helped capabilities. If anything, it's well documented that RLHF diminishes capabilities (base models can for example play chess very well). The vast majority of alignment research, especially research before LLMs,  isn't even useful to alignment (a lot of it seems far too ungrounded).   
• There was never a real shot of solving alignment until LLMs became realized either.  The world has changed and it seems like foom priors are wrong, but most here haven't updated. It increasingly seems like we'll get strong precursor models so we will have ample time to engineer solutions and it won't be like trying to build a working rocket on the first try. (The reasons being we are rapidly approaching the limits of energy constraints and transistor density without really being close to fooming). This mental model is still popular when reality seems to diverge.

Well I actually have a hunch to why, many holding on to the above priors don't want to let them go because that means this problem they have dedicated a lot of mental space to will seem more feasible to solve. 

If it's instead a boring engineering problem, this stops being a quest to save the world or an all consuming issue. Incremental alignment work might solve it, so in order to preserve the difficulty of the issue, it will cause extinction for some far-fetched reason. Building precursor models then bootstrapping alignment might solve it, so this "foom" is invented and held on to (for a lot of highly speculative assumptions), because that would stop it from being a boring engineering problem that requires lots of effort and instead something a lone genius will have to solve. The question that maybe energy constraints will limit AI progress from here on out was met with a maybe response [LW(p) · GW(p)], but the number of upvotes make me think most readers just filed it as an unconditional "no, it won't" in their minds.

There is a good reason to think like this - if boring engineering really does solve the issue, then this community is better off assuming it won't. In that scenario, boring engineering work is being done by the tech industry anyways, so no need to help there. But I hope if people adopt the mindset of assuming the worst case scenario to have the highest expected effects of research, they realize the assumption they are making is an assumption, and not let the mental effects consume them.
 

Idea:

Have everyone who wants to share and recieve potentially exfohazardous ideas/research send out a 4096-bit RSA public key.

Then, make a clone of the alignment forum, where every time you make a post, you provide a list of the public keys of the people who you want to see the post. Then, on the client side, it encrypts the post using all of those public keys. The server only ever holds encrypted posts.

Then, users can put in their own private key to see a post. The encrypted post gets downloaded to the user's machine and is decrypted on the client side. Perhaps require users to be on open-source browsers for extra security.

Maybe also add some post-quantum thing like what Signal uses so that we don't all die when quantum computers get good enough.

Should I build this?

Is there someone else here more experienced with csec who should build this instead?

I think this post would be much more effective in achieving its goal if it would provide alternatives.

What are the advantages of posting your research ideas on LessWrong? Are there other ways in which you can get these advantages? Are there maybe even alternatives that give you more of the thing you want?

I expect telling people about these alternatives (if they exist) would make them more likely to make use of them.

One of the main things I think people can get by publishing their research is to get feedback. But you could also search for people who are interested in what you are working on. Then you can send your write-ups only to these people.

Also seeing people engage with things that you write is very motivating.

These are just some rough examples as I don't think I have very good models about what you can get out of LessWrong and how to get the same benefits in different ways.

In computer security, there is an ongoing debate about vulnerability disclosure, which at present seems to have settled on 'if you aren't running a bug bounty program for your software you're irresponsible, project zero gets it right, metasploit is a net good, and it's ok to make exploits for hackers ideologically aligned with you'.  

The framing of the question for decades was essentially "do you tell the person or company 

 with the vulnerable software, who may ignore you or sue you because they don't want to spend money?  Do you tell the public, where someone might adapt your report into an attack?  

Of course, there is the (generally believed to be) unethical option chosen by many "sell it to someone who will use it, and will protect your identity as the author from people who might retaliate"

There was an alternative called 'antisec': https://en.m.wikipedia.org/wiki/Antisec_Movement which basically argued 'dont tell people about exploits, they're expensive to make, very few people develop the talents to smash the stack for fun and profit, and once they're out, they're easy to use to cause mayhem'.  

They did not go anywhere, and the antisec viewpoint is not present in any mainstream discussion about vulnerability ethics.

Alternatively, nations have broadly worked together to not publicly disclose technical data that would make building nuclear bombs simple.  It is an exercise for the reader to determine whether it has worked.  

So, the ideas here have been tried in different fields, with mixed results.  

If people don’t publish their findings and make contributions in public, how are they supposed to establish themselves as researchers in the first place?

"So where do I privately share such research?" — good question! There is currently no infrastructure for this.

This is why I currently think you're completely wrong about this. There never will be an infrastructure for this. Privacy of communities isn't a solvable problem in general, as soon as your community is large enough to compete with the adversary, it's large enough and conspicuous enough that the adversary will pay attention to it and send in spies and extract leaks. If you make it compartmented enough to prevent leaks/weed out the spies, it wont have enough intellectual liveliness to solve the alignment problem.

There is nothing that makes differentially helping capabilities "fine if you're only differentially helping them a little bit".

If your acceptable lower limit for basically anything is zero you wont be allowed to do anything, really anything. You have to name some quantity of capabilities progress that's okay to do before you'll be allowed to talk about AI in a group setting.

"So where do I privately share such research?" — good question! There is currently no infrastructure for this.

I'd really like to have such a place, or even a standard policy how to do this.

I feel like the aintelope I'm working on has to secure it's stuff from scratch. Yes, it's early, but it is difficult to engineer security in later. You have to start with something. I'd really like to have a standard for AI Safety projects to follow or join.

Good day!

I fully share the views expressed in your article. Indeed, the ideal solution would be to delete many of the existing materials and to reformat the remaining ones into a format understandable to every novice programmer, transhumanist, or even an average person.

As a poker player and a lawyer assisting consumers who have suffered from the consequences of artificial intelligence, as well as someone interested in cryptocurrencies and existential risks, I first invested in Eliezer Yudkowsky's ideas many years ago. At that time, I saw how generative-predictive models easily outplayed poker players, and I wondered whether it was possible to counteract this. Since then, I have not seen a single serious security study conducted by not the players themselves, but any non-response system up question could it research even self data

and in the realm of cryptocurrencies, money continues to be stolen with the help of AI, with no help or refund in sight. 

I see prediction we have already lost the battle against GAI, but in the next 12 years, we have a chance to make the situation a bit better. To create conditions of the game where this player or his precursor (AI-users) will have more aligned (lawful good) elements. 

It seems that very intelligent also very stubborn, see no doubts in position, such high IQs are very dangerous. Think they are right about everything, that understood it all, but we are just few perspectives in a vast, incomprehensible world where we understand nothing. We all wrong.

Yes, you're probably a couple of sigmas smarter than the median person, but you need to convince exactly such a person, the median, or even dumper on a couple of IQ sigmas not to launch anything. It's not just OpenAI developing GAI, 

others are too, make research, decisions but they might not even know who Eliezer Yudkowsky is or what the lesswrong website is. They might visit pepper copy of the site, see that it's clear we shouldn't let GAI emerge, think about graphic boards, and where there are many graphic boards, in decentralized mining, they might decide to take control of them. 

If we're lucky, their master slaves will just steal them and use them for mining, and everything will be fine then. 

But various research like changing the sign of a function and creating something dangerous, that's better removed. 

Another strange thing is the super-ethical laws for Europe and the US. A lot of jurisdictions. Even convention of cybercrime not universal. And in universal jurisdiction cybercrimes there is no crimes about existential risks. So many of international media laws just declarations without real procedures without any real power 

Many laws aren't adhered to in practice, there are different kinds of people, for some, the criminal code is like a menu, and if you don't have to pay for that menu, it's doubly bad

There are individualists, and among transhumanists, I'm sure there are many who would choose their life and the life of a close million over the rest of humanity. And that's not good, unfair. System should be for all billions of people

But there are also those in the world who, if presented with a "shut down server" button, will eventually press it. There are many such buttons in various fields worldwide. If we take predictions for a hundred years, unless something radically changes, the likelihood of "server shutdown" approaches 1.

So it's interesting whether through GAI open source or any other framework or model, we could create some universal platform with a rule system that on one hand does universal monitoring of all existential problems, but also provides clear, beneficial instructions for the median voter, as well as for the median worker and their masters. 

Culture is created by the spoon. Give us a normal, unified system that encourages correct behavior for adhering to existential risks, since you've won the genetic and event lottery by intelligence and were born with high IQ and social skills. 

Usually, the median person is interested in: jobs, a full fridge, rituals, culture, the spread of their opinion leader's information, dopamine, political and other random and inherited values, life, continuation of life, and the like. 

Provide a universal way of obtaining this and just monitor it calmly. And it touched on the problem of all existential risks: ecology, physics, pandemics, volcanic activity, space, nanobots, atom.

Doomclock 23:55 is not only because of the GAI risk, what selfishness. 

Sometimes it seems that Yudkowsky is the Girolamo Savonarola of our days. And the system of procedures that Institute of Future Life and Eliezar already invented, their execution is important!

Sadly in humanity now it's profitable to act, and then ask for forgiveness. So many businesses are built the same as nowadays Binance without responsibility, 'don't FUD just build', same way work all AI and others powerful startups. Many experimental researches not 100% sure that they are safe for planet. In 20th and 21th centuary it's became normal. But it shouldn't.

And these real condition of problem, real pattern of life. And yet in crypto, there are many graphics cards, collected in decentralized networks, and they gather in large decentralized, unturnoffable nodes and clusters. Are they danger?

We need systems of cheap protection, brakes, and incentives for their use! And like with seat belts, teach from childhood. Something even simpler than Khan Academy. HPMOR was great. Do we have anything for next Generations? That didn't see or like Harry Potter? What is it? To explain problem.

Laws and rules just for show, unenforceable, are only harmful. Since ancient times it's known that any rules consist of three things: hypothesis, disposition, and sanction. Without powerful procedural law, all these material legal norms are worthless, more precisely, a boon for the malefactor. If we don't procedurally protect people from wrongful AI, introducing soothing, non-working ethical rules will only increase volatility and the likelihood of wrongful AI, his advantage, even if we are lucky to have its element (it's alighment) in principle.

I apologize if there were any offensive remarks in the text or if it seemed like an unstructured rant expressing incorrect thoughts, that how my brain work. Hope I wrong, point please. Thank you for any comments and for your attention!

"But my ideas are likely to fail! Can I share failed ideas?": If you share a failed idea, that saves the other person time/effort they would've spent chasing that idea. This, of course, speeds up that person's progress, so don't even share failed ideas/experiments about AI, in the status quo.

"So where do I privately share such research?" — good question! There is currently no infrastructure for this. I suggest keeping your ideas/insights/research to yourself. If you think that's difficult for you to do, then I suggest not thinking about AI, and doing something else with your time, like getting into factorio 2 or something.

"But I'm impatient about the infrastructure coming to exist!": Apply for a possibly-relevant grant and build it! Or build it in your spare time. Or be ready to help out if/when someone develops this infrastructure.

"But I have AI insights and I want to convert them into money/career-capital/personal-gain/status!": With that kind of brainpower/creativity, you can get any/all of those things pretty efficiently without publishing AI research, working at a lab, advancing a given SOTA, or doing basically (or literally) anything that differentially speeds up AI capabilities. This, of course, means "work on the object-level problem, without routing that work through AI capabilities", which is often as straightforward "do it yourself".

"But I'm wasting my time if I don't get involved in something related to AGI!": "I want to try LSD, but it's only available in another country. I could spend my time traveling to that country, or looking for mushrooms, or even just staying sober. Therefore, I'm wasting my time unless I immediately inject 999999 fentanyl."